id
string | status
string | inserted_at
timestamp[us] | updated_at
timestamp[us] | _server_id
string | doi
string | section
string | text
string | links
string | span_label.responses
list | span_label.responses.users
sequence | span_label.responses.status
sequence | assess_ner.responses
sequence | assess_ner.responses.users
sequence | assess_ner.responses.status
sequence | assess_nel.responses
sequence | assess_nel.responses.users
sequence | assess_nel.responses.status
sequence | comments.responses
sequence | comments.responses.users
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null | span_label.suggestion.score
null |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
b14e4946-863e-4a50-b8cb-2c9e73464e60
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:52.499000 |
29ddeee8-b984-49e7-a886-3dbbaff99398
|
[10.35784/iapgos.932](https://doi.org/10.35784/iapgos.932)
|
abstract
|
In the article the researches of the use of electronic meters with standard nominal parameters for metering of substation own electric energy in the schemes of high and low voltage networks simultaneously with the use of the corresponding calculated coefficients on voltage for the purpose of operational control and determination of the reliability of measurement of electricity parameters.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"electric energy"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
d222fd81-09fa-46ce-aec4-cd86761a1aa4
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:52.791000 |
a761ceaf-f2e7-4bfc-a3e9-bd2697a798a6
|
[10.35784/iapgos.932](https://doi.org/10.35784/iapgos.932)
|
XI. Pliki "cookies"
|
1. Platforma wykorzystuje mechanizm plików "cookies" ("ciasteczka").Pliki te mogą zawierać dane osobowe w postaci adresu IP urządzenia wykorzystywanego przez Usługobiorcę podczas korzystania z Platformy oraz unikatowego identyfikatora tego urządzenia.Pliki te nie są przechowywane na serwerach Usługodawcy, a istotą ich działania jest zapis ich zawartości podczas wizyty na stronie na urządzeniu wykorzystywanym do korzystania z Platformy.Więcej informacji o plikach "cookies" można znaleźć na stronie: https://www.aboutcookies.org/. 2. Ze względu na okres przechowywania (retencji) pliki "cookies" wykorzystywane przez Platformę mogą mieć charakter: 1) cookies "sesyjnych" lub "tymczasowych", związanych z sesją przeglądania serwisu, które przechowywane są na urządzeniu użytkownika do momentu opuszczenia witryny internetowej; 2) cookies "trwałych", zapisywanych na urządzeniu użytkownika i pozostających w pamięci przeglądarki po zakończeniu sesji, o ile nie zostaną one usunięte na żądanie Usługobiorcy; 3) cookies podmiotów zewnętrznych (tzw.third parties cookies), pochodzące z serwerów reklamowych podmiotów współpracujących z serwisem. 3. Ze względu na cel ich wykorzystywania, pliki "cookies" wykorzystywane przez Platformę mogą mieć charakter: 1) niezbędny do właściwego funkcjonowania strony i jej poszczególnych elementów; 2) funkcjonalny, umożliwiają witrynie zapamiętywanie wyborów dokonanych na stronach serwisu, w tym zapamiętywanie haseł Usługobiorcy wykorzystywanych do logowania do konta Usługobiorcy; 3) wydajnościowy, których celem jest gromadzenie informacji i o tym, jak są wykorzystywane strony internetowe; 4) reklamowy, wykorzystywane w celu świadczenia usług reklamowych; 5) analityczny, wykorzystywane w celach statystycznych.4. Podstawą prawną dla zbierania danych odczytywanych z plików "cookies" jest art.6 ust. 1 lit.f RODO, rozumiany jako realizacja usprawiedliwionego interesu administratora danych w postaci utrzymania funkcjonalności Platformy oraz dostosowanie strony do indywidualnych ustawień Usługobiorcy, jak również zapamiętywanie wprowadzanych przez Usługobiorcę danych związanych z korzystaniem z Platformy oraz prowadzenie analiz statystycznych dotyczących Usługobiorców. 5. Usługobiorca może zrezygnować ze zbierania plików "cookies", zmieniając ustawienia przeglądarki wykorzystywanej do korzystania z Platformy, w sposób odpowiedni dla tej przeglądarki: Chrome, Firefox, Internet Explorer, Opera, Safari, Microsoft Edge.6. Usługobiorca może uzyskać dostęp do zgromadzonych plików "cookies" znajdujących się na dysku lub w pamięci urządzenia, wykorzystywanego do korzystania z Platformy, poprzez analizę zawartości plików "cookies" w ustawieniach przeglądarki.7. Usługodawca nie łączy danych eksploatacyjnych oraz informacji zawartych w plikach "cookies" z żadnymi innymi danymi, w których posiadanie wejdzie lub do których może mieć dostęp.
|
None
|
[
[],
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"discarded"
] |
[
"Correct",
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"discarded"
] |
[
"Correct",
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"discarded"
] |
[
null,
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"discarded"
] |
[] | null | null |
08d70539-4a03-4e0e-8547-1812adcea38f
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-05T07:47:31.059000 |
79abeb0f-511c-404b-81ad-fa14fb20af43
|
[10.3846/16484142.2004.9637980](https://doi.org/10.3846/16484142.2004.9637980)
|
abstract
|
The development of fuel sort of vehicles assumes a wide spectrum of application in America and Europe. Safety assessment is needed for car exploitation using hydrogen fuel. Therefore this article covers the control methodology of defects adapting the science advancement for hydrogen fuel operation. To achieve this aim the damage prevention methodology of mechanic phenomena and damage modeling for hydrogen fuel cells is suggested. In the presented methodology the methods and steps of safety assessment are discussed.
|
<li> <b>hydrogen fuel:</b> Biohydrogen (263320)
|
[
[
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"label": "energyType",
"start": 158
},
{
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"label": "energyType",
"start": 275
},
{
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"label": "energyStorage",
"start": 400
}
],
[
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{
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},
{
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[
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[
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"submitted"
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[
"Partially correct",
"Correct"
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[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
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[
"submitted",
"submitted"
] |
[
"Partially correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"The last one is a form of storage technically",
null
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
{
"end": 171,
"label": "energyType",
"start": 158
},
{
"end": 288,
"label": "energyType",
"start": 275
},
{
"end": 413,
"label": "energyType",
"start": 400
}
] | null | null |
b906b5d7-6be3-4444-9c6a-097342dd3961
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:52.969000 |
21016608-afcf-4ade-9dbb-57d09d137050
|
[10.3846/16484142.2004.9637980](https://doi.org/10.3846/16484142.2004.9637980)
|
Introduction
|
In principle, a fuel cell operates like a battery.Unlike a battery, a fuel cell does not run down or require recharging.It will produce energy in the form of electricity and heat as long as fuel is supplied. A fuel cell consists of two electrodes sandwiched around an electrolyte.Oxygen passes over one electrode and hydrogen over the other, generating electricity, water and heat. Hydrogen fuel is fed into the anode of the fuel cell.Oxygen (or air) enters the fuel cell through the cathode.Encouraged by a catalyst, the hydrogen atom splits into a proton and an electron, which take the different paths to the cathode.The proton passes through the electrolyte.The electrons create a separate current that can be utilized before they return to the cathode, to be reunited with the hydrogen and oxygen in a molecule of water. A fuel cell system which includes a fuel reformer can utilize the hydrogen from any hydrocarbon fuel -from natural gas to methanol, and even gasoline.Since the fuel cell relies on chemistry and not on combustion, the emissions from this type of a system would still be much smaller than the emissions from the cleanest fuel combustion processes [1]. Proton Exchange Membrane (PEM).These cells operate at relatively low temperatures (about 175 degrees .or 80 degrees C), have high power density, can vary their output quickly to meet shifts in power demand and are suited for application such as in automobiles -where quick start is required.The proton exchange membrane is a thin plastic sheet that allows hydrogen ions to pass through it.The membrane is coated on both sides with highly dispersed metal alloy particles (mostly platinum) that are active catalysts.The electrolyte used is a solid organic polymer poly-perflourosulfonic acid.The solid electrolyte is an advantage because it reduces corrosion and management problems.Hydrogen is fed to the anode side of the fuel cell where the catalyst encourages the hydrogen atoms to release electrons and become hydrogen ions (protons).The electrons travel in the form of an electric current that can be utilized before it returns to the cathode side of the fuel cell where oxygen has been fed.At the same time the protons diffuse through the membrane (electrolyte) to the cathode where the hydrogen atom is recombined and reacted with oxygen to produce water, thus completing the overall process.This type of fuel cell is, however, sensitive to fuel impurities.Cell outputs generally range from 50 to 250 kW. Direct Methanol .uelCells (DM.C).These cells are similar to PEM cells as they both use a polymer membrane as the electrolyte.However, in DM.C the anode catalyst itself draws the hydrogen from the liquid methanol, eliminating the need for a fuel reformer.Efficiencies of about 40 % are expected with this type of fuel cell, which would typically operate at a temperature between 120190 degrees .or 50100 degrees C.This is a relatively low range, making this fuel cell attractive for tiny to mid-sized applications to power cellular phones and laptops.Higher efficiencies are achieved at higher temperatures.A major problem, however, is fuel crossing from the anode to the cathode without producing electricity.Many com-panies said they solved this problem, however. A protonic ceramic fuel cell (PC.C), a new type of fuel cell is based on ceramic electrolyte material that exhibits high protonic conductivity at elevated temperatures.PC.Cs share the thermal and kinetic advantages of high temperature operation at 700 degrees Celsius with molten carbonate and solid oxide fuel cells, while exhibiting all of the intrinsic benefits of proton conduction in polymer electrolyte and phosphoric acid fuel cells (PA.Cs).The high operating temperature is necessary to achieve very high electrical fuel efficiency with hydrocarbon fuels.PC.Cs can operate at high temperatures and electrochemically oxidize fossil fuels directly to the anode.This eliminates the intermediate step of producing hydrogen by a costly reforming process.Gaseous molecules of the hydrocarbon fuel are absorbed on the surface of the anode in the presence of water vapor and hydrogen atoms are efficiently stripped off to be absorbed into the electrolyte, with carbon dioxide as the primary reaction product.Additionally, PC.Cs have a solid electrolyte so the membrane cannot dry out as with PEM fuel cells, or liquid cant leak out as with PA.Cs.
|
<li> <b>hydrogen fuel:</b> Biohydrogen (263320)<li> <b>natural gas:</b> Natural gas (113000)<li> <b>methanol:</b> Biomethanol (262110)<li> <b>gasoline:</b> Gasolines (114550)
|
[
[
{
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"label": "energyType",
"start": 382
},
{
"end": 944,
"label": "energyType",
"start": 933
},
{
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"label": "energyType",
"start": 948
},
{
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"label": "energyType",
"start": 2494
},
{
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"label": "energyType",
"start": 2690
},
{
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"label": "energyType",
"start": 967
}
]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
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[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
{
"end": 395,
"label": "energyType",
"start": 382
},
{
"end": 944,
"label": "energyType",
"start": 933
},
{
"end": 956,
"label": "energyType",
"start": 948
},
{
"end": 2502,
"label": "energyType",
"start": 2494
},
{
"end": 2698,
"label": "energyType",
"start": 2690
},
{
"end": 975,
"label": "energyType",
"start": 967
}
] | null | null |
ec16f9f5-8bb8-4d72-bf64-4f0a35ff7369
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-08T14:49:15.358000 |
3c22a0b8-8ebd-430e-b0d7-7503824f8637
|
[10.3389/fenrg.2022.850431](https://doi.org/10.3389/fenrg.2022.850431)
|
abstract
|
Blockage of the U-type channel exacerbates the intermittency of production, and clarifying the channel heat transfer characteristics and pressure drop is an effective way to address this problem. The channel heat transfer and flow characteristics of the fluid in the channel are experimentally investigated in this study. According to the experiments, the heat transfer coefficient is between 59.95 and 200.29 W/m2⋅K and increases with the flow velocity and fluid temperature. Because the pressure drop is usually accompanied by a change in the energy loss of the fluid, the energy loss is evaluated experimentally. The results demonstrate that the friction loss in the straight tube section accounts for 80% of the energy loss. A bent tube of 90° is recommended instead of a right-angle tube to reduce the pressure drop. A dimensionless relation regarding the Nusselt number is presented to predict the heat transfer characteristics. We provided proposals to address the problem of blockage of the U-type channel, this is helpful to reduce production energy consumption and improve the quality of titanium sponge.
|
None
|
[
[],
[]
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
2f501fd1-cf36-4031-bc40-146227ca9159
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:53.152000 |
b965c71c-9f36-46c7-97bb-67d84036a982
|
[10.3389/fenrg.2022.850431](https://doi.org/10.3389/fenrg.2022.850431)
|
Heat Transfer Coefficient
|
The heat transfer coefficient inside the whole channel is not constant, and the heat transfer coefficient in this study is mean heat transfer coefficient.Figure 3 shows the variation in the heat transfer coefficient with fluid velocity.The heat transfer coefficient increased as the Reynolds number increased because the flow velocity increased, resulting in an increase in the intensity of convective heat transfer.The extent of the increase in the heattransfer coefficient also increased with a further increase in the flow velocity.Furthermore, as observed in Figure 3, the heat transfer coefficient is between 59.95 and 200.29 W/m 2 •K. In addition, the effect of the fluid temperature on heat transfer was investigated.The temperature difference decreases as the fluid temperature increases.An increase in the fluid temperature increases the thermal conductivity and reduces the dynamic viscosity of the fluid.Therefore, the heat transfer coefficient increases and boosts the intensity of the convective heat transfer.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
13aaa83b-a7e1-47b7-a9d1-150166ae01eb
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:53.275000 |
0db19699-9bec-4794-a158-38219ea728db
|
[10.3390/en16217286](https://doi.org/10.3390/en16217286)
|
abstract
|
Photovoltaic (PV) power generation is considered to be a clean energy source. Solar modules suffer from nonlinear behavior, which makes the maximum power point tracking (MPPT) technique for efficient PV systems particularly important. Conventional MPPT techniques are easy to implement but require fine tuning of their fixed step size. Unlike conventional MPPT, the MPPT based on reinforcement learning (RL-MPPT) has the potential to self-learn to tune step size, which is more adaptable to changing environments. As one of the typical RL algorithms, the Q-learning algorithm can find the optimal control strategy through the learned experiences stored in a Q-table. Thus, as the cornerstone of this algorithm, the Q-table has a significant impact on control ability. In this paper, a novel Q-table of reinforcement learning is proposed to maximize tracking efficiency with improved Q-table update technology. The proposed method discards the traditional MPPT idea and makes full use of the inherent characteristics of the Q-learning algorithm such as its fast dynamic response and simple algorithm principle. By establishing six kinds of Q-tables based on the RL-MPPT method, the optimal discretized state of a photovoltaic system is found to make full use of the energy of the photovoltaic system and reduce power loss. Therefore, under the En50530 dynamic test standard, this work compares the simulation and experimental results and their tracking efficiency using six kinds of Q-table, individually.
|
<li> <b>Photovoltaic (PV) power generation:</b> Solar photovoltaic (241000)
|
[
[
{
"end": 34,
"label": "energyType",
"start": 0
}
]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
{
"end": 34,
"label": "energyType",
"start": 0
}
] | null | null |
44a111b2-f0e1-44b5-92e2-e136b4013c5e
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:53.365000 |
6b71391f-79a9-4112-bf75-a6d920cd9c28
|
[10.3390/en11071845](https://doi.org/10.3390/en11071845)
|
abstract
|
In recent years, Hydro-pneumatic cycling compressed air energy storage (HC-CAES) has become an important topic in compressed air energy storage (CAES) technology research. In HC-CAES, air is compressed by liquid and driven by electrical equipment when energy is stored, and then, liquid is used to drive the water conservancy equipment to generate electricity. In this study, adaptive hydraulic potential energy transfer technology is proposed to solve a series of problems in the HC-CAES system, including the high fluctuation range of gas potential energy, poor operating stability, low efficiency, and so on. Therefore, fluctuating potential energy can be stably transferred through the variable area hydraulic devices, which can be controlled with an on–off valve. The structure and operation scheme of the adaptive hydraulic potential energy transfer device used in the HC-CAES system are explained in detail; the device can provide a stable water head range for the highly efficient operation of water conservancy equipment. Moreover, an optimal operation scheme was determined through simulation analysis; a physical experiment platform was built to verify the feasibility of the design and stability of system operation.
|
<li> <b>compressed air energy storage (CAES):</b> Compressed fluids (342000)<li> <b>Hydro-pneumatic cycling compressed air energy storage (HC-CAES):</b> Compressed fluids (342000)
|
[
[
{
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"label": "energyStorage",
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},
{
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},
{
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},
{
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},
{
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]
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[
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[
"submitted"
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[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
{
"end": 150,
"label": "energyStorage",
"start": 114
},
{
"end": 80,
"label": "energyStorage",
"start": 17
}
] | null | null |
2a8594fa-ded1-4125-a27e-8c4433bc4a00
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:53.440000 |
f6548b8d-974d-4120-8b1c-211c80afd8cc
|
[10.3390/en11071845](https://doi.org/10.3390/en11071845)
|
Volume of Air in Liquamatic
|
Piston/m Multiple equivalent-area selection schemes could be obtained according to the principle and initial parameters of the system.However, a reasonable selection of schemes should meet the following on, when an equivalent area ratio is fixed.The equivalent area ratio is changed when the compensation pressure reaches its upper limit, which changes the pressure of the hydraulic compensation system back to the lower value so that it can be used again.The output power of the hydraulic compensation system in both the energy storage and power generation processes are shown in Figure 9.It can be seen that the faster the piston rod moves, the higher the compensation pressure, which produces higher output power of the hydraulic compensation system.
|
None
|
[
[
{
"end": 536,
"label": "energyStorage",
"start": 522
}
]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"energy storage missed"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
1cb34ec5-54fc-40a4-b914-f1ba0b9a4556
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:53.526000 |
4478c134-7301-4141-84b5-64fc45a06c12
|
[10.3390/en5103874](https://doi.org/10.3390/en5103874)
|
abstract
|
Currently, floating wind turbines (FWTs) may be the more economical and suitable systems with which to exploit offshore wind energy in deep waters. Among the various types of floating foundations for offshore wind farms, a tension leg platform (TLP) foundation can provide a relatively stable platform for currently available offshore wind turbines without requiring major modifications. In this study, a new multi-column TLP foundation (WindStar TLP) was developed for the NREL 5-MW offshore wind turbine according to site-specific environmental conditions, which are the same as the OC3-Hywind (NREL) conditions. The general arrangement, main structure and mooring system were also designed and investigated through hydrodynamic and natural frequency analyses. The complete system avoids resonance through the rotor excitations. An aero-hydro-servo-elastic coupled analysis was carried out in the time domain with the numerical tool FAST. Statistics of the key parameters were obtained and analysed and comparisons to MIT/NREL TLP are made. As a result, the design requirements were shown to be satisfied, and the proposed WindStar TLP was shown to have favourable motion characteristics under extreme wind and wave conditions with a lighter and smaller structure. The new concept holds great potential for further development.
|
<li> <b>offshore wind energy:</b> Offshore wind energy (232000)<li> <b>wind turbines:</b> Wind energy (230000)
|
[
[
{
"end": 131,
"label": "energyType",
"start": 111
},
{
"end": 33,
"label": "energyType",
"start": 20
},
{
"end": 348,
"label": "energyType",
"start": 335
}
]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
{
"end": 131,
"label": "energyType",
"start": 111
},
{
"end": 33,
"label": "energyType",
"start": 20
},
{
"end": 348,
"label": "energyType",
"start": 335
}
] | null | null |
aea11259-7c43-4342-aeb7-03d71b530713
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:53.612000 |
65de6bb6-b439-4a39-9f2b-baa51341c2df
|
[10.3390/en5103874](https://doi.org/10.3390/en5103874)
|
Hydrodynamic Characteristics
|
To calculate the hydrodynamic characteristics of the WindStar TLP, the SESAM/Wadam software program was applied in this study [20].The software uses the three-dimensional boundary integral equation method to solve the linearized hydrodynamic radiation and diffraction problems for the interaction of free surface waves with zero-forward-speed floating structures in the frequency domain.According to the geometric symmetry of the supporting platform, four different wave directions, 0°, 15°, 30°, and 45°, were selected to perform the hydrodynamic analysis.The panelised view of the WindStar TLP wetted hull and the definition of the coordinate system are shown in Figure 9.The added mass properties in the surge, sway, and heave directions are shown in Figure 10.With three large pontoons, the heave added mass has an average value of 3.53 × 10 6 kg and varies less with frequency.However, the added mass in surge and sway tend to decrease with increasing frequency.The computed added-mass and damping coefficients, as well as the wave excitation forces, are used as inputs to the fully coupled time-domain simulation program FAST [21].Figure 11 presents heave and pitch RAOs for WindStar TLP calculated both in frequency domain (Wadam) and in time domain (FAST with elastic and rigid turbine).The RAOs obtained in FAST with rigid turbine are in good arrangement with Wadam RAOs.This model consistency ensures the accuracy of the following load analysis in FAST.As depicted in the figure, the turbine elasticity has minor effect on the heave resonant response.However, with flexible turbine, the pitch natural frequency is shifted from 1.84 rad/s to 1.65 rad/s.The shift pitch natural frequency primarily due to the turbine elasticity consists of the positive platform pitch with positive 1st tower fore-aft deflection mode and vice versa [22].This result is further compared with a fully-flexible model including platform elasticity by FE methods in the following section.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
01484df9-ea42-4083-a0c4-809dc8b59f9f
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-08T14:05:32.394000 |
49a2bc4f-4b44-4601-b317-f9174d884fa5
|
[10.3390/met13030481](https://doi.org/10.3390/met13030481)
|
abstract
|
The influence of samarium, as an additional alloying element, on the morphology and corrosion performance of the Zn-Co-Sm alloy electrodeposited coatings, was investigated by scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM/EDS) and electrochemical impedance spectroscopy (EIS) measurements. The Zn-Co-Sm coatings were electrodeposited from the aqueous solution containing Sm(NO3)3, ZnCl2, and CoCl2 as the metal ion source. The percentage of Sm in the coating may be very finely tuned by setting electrodeposition parameters, including cathodic current density, glycine concentration in the electroplating solution, and the solution temperature. The coatings with Sm content from 0.5 to 18.5 wt.% were produced. Since low deposition current densities (10–50 mA cm−2) were applied, the samples obtained were of good adhesion and compact. The presence of Sm2O3 inclusion was verified by XRD as the Sm2O3 crystalline phase. Samarium is incorporated in the coatings through the mechanism of oxide/hydroxide formation during the electroreduction of Zn and Co. Corrosion tests in NaCl solution show that the presence of Sm significantly increases the polarization resistance for the corrosion process of Zn-Co-Sm coatings (one order of magnitude, i.e., from ~500 Ω cm2 measured without Sm to 2000–3000 Ω cm2 with 12 wt.% Sm), giving evidence of the self-healing action that is provided by Sm particles in the coatings. This effect is more pronounced in the case when the coatings contain a higher Sm percentage.
|
None
|
[
[],
[]
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
ce269a8b-1ef6-45bf-ae6a-e80efc61d404
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-20T09:37:08.165000 |
b38f97bc-377c-4d58-929b-9bbc99bd39d2
|
[10.3390/met13030481](https://doi.org/10.3390/met13030481)
|
Chemical Composition of Zn-Co-Sm Coatings
|
The chemical composition of Zn-Co-Sm deposits was analyzed by EDS, and the ED spectra for two samples with different Sm content are presented in Figure 1. Figure 2 depicts the dependence of samarium, oxygen, and cobalt content in the coa ings, on the applied current density and the glycine presence as an additive.A sharp de rement in the Sm and O content, and a sharp increase in cobalt content, may be notic with the increase in the applied current density, due to the reasons explained below.It also clear that glycine facilitates the deposition of coatings containing higher Sm and content, and this phenomenon will also be explained.Figure 2 depicts the dependence of samarium, oxygen, and cobalt content in the coatings, on the applied current density and the glycine presence as an additive.A sharp decrement in the Sm and O content, and a sharp increase in cobalt content, may be noticed with the increase in the applied current density, due to the reasons explained below.It is also clear that glycine facilitates the deposition of coatings containing higher Sm and O content, and this phenomenon will also be explained. Due to the standard electrode potential (<-2.3V vs. SHE) which is far more negative than the potential of water degradation, the electroreduction of rare earth elements (Ce, Nd, Sm, Gd) to their metallic form (oxidation state zero) is thermodynamically impossible in aqueous media [17].However, rare earth elements still may be incorporated from the electrolyte into coatings by electrochemical deposition, in two distinct ways. The first way is the formation of alloy deposits containing rare earth elements in metallic form when the electroreduction of rare metal ions to their zero oxidation state occurs along with the electroreduction of other species, the process called an induced codeposition [18].In this manner, the Ce, Nd, Sm, and Gd-containing alloys [18], ZnCo-CeO 2 [19], and Sm-Se [16] alloys were obtained.A mechanism for aqueous codeposition of rare earth elements containing alloys has been proposed [18], where glycine takes the key role as a complexing agent.Dinuclear coordination complexes are formed, containing iron group element cation and rare earth element cation as nuclei, and glycine ions as ligands.These complex structures, with proper surface orientation, may expose both cations to electroreduction [18]. Figure 2 depicts the dependence of samarium, oxygen, and cobalt content in the coatings, on the applied current density and the glycine presence as an additive.A sharp decrement in the Sm and O content, and a sharp increase in cobalt content, may be noticed with the increase in the applied current density, due to the reasons explained below.It is also clear that glycine facilitates the deposition of coatings containing higher Sm and O content, and this phenomenon will also be explained.Due to the standard electrode potential (<-2.3V vs SHE) which is far more negative than the potential of water degradation, the electroreduction of rare earth elements (Ce, Nd, Sm, Gd) to their metallic form (oxidation state zero) is thermodynamically impossible in aqueous media [17].However, rare earth elements still may be incorporated from the electrolyte into coatings by electrochemical deposition, in two distinct ways. The first way is the formation of alloy deposits containing rare earth elements in metallic form when the electroreduction of rare metal ions to their zero oxidation state occurs along with the electroreduction of other species, the process called an induced codeposition [18].In this manner, the Ce, Nd, Sm, and Gd-containing alloys [18], ZnCo-CeO2 [19], and Sm-Se [16] alloys were obtained.A mechanism for aqueous codeposition of rare earth elements containing alloys has been proposed [18], where glycine takes the key role as a complexing agent.Dinuclear coordination complexes are formed, containing iron group element cation and rare earth element cation as nuclei, and glycine ions as ligands.These complex structures, with proper surface orientation, may expose both cations to electroreduction [18]. The second way of RE incorporation in coatings is characteristic of composite coating containing RE, where the rare earth element hydroxide/oxide particles are trapped and surrounded by other elements.The formation of rare element hydroxide occurs through the pH-driven process, where the pH increment in the near-cathodic layer results in the rare element hydroxide precipitation [17].For example, the Ni coating with Sm(III) and Sm(II) oxides [13], or Ni-cerium oxide coating [14] has been reported. What is more, the single rare earth element oxide conversion films, resembling the behavior of chromate film, for example, samarium [17], yttrium [20], and cerium [21] conversion coatings, have also been reported.The hydroxide precipitation occurs independently of the cathodic process that causes the pH increment, i.e., the oxygen reduction or hydrogen evolution.However, the morphology of the hydroxide formed depends on the cathodic process inducing the pH increment: the oxygen reduction causes the for- The second way of RE incorporation in coatings is characteristic of composite coating containing RE, where the rare earth element hydroxide/oxide particles are trapped and surrounded by other elements.The formation of rare element hydroxide occurs through the pH-driven process, where the pH increment in the near-cathodic layer results in the rare element hydroxide precipitation [17].For example, the Ni coating with Sm(III) and Sm(II) oxides [13], or Ni-cerium oxide coating [14] has been reported. What is more, the single rare earth element oxide conversion films, resembling the behavior of chromate film, for example, samarium [17], yttrium [20], and cerium [21] conversion coatings, have also been reported.The hydroxide precipitation occurs independently of the cathodic process that causes the pH increment, i.e., the oxygen reduction or hydrogen evolution.However, the morphology of the hydroxide formed depends on the cathodic process inducing the pH increment: the oxygen reduction causes the formation of thin, dense, and non-porous hydroxide deposit, while the hydroxide precipitate formed as a result of hydrogen evolution is a thicker, yet porous, with pores of 100 µm in diameter, due to the gas evolution [17]. The dependence of Sm content on the deposition current density, observed in our and previous works [13,22], is understandable bearing in mind the process that enables the Sm incorporation into the coating.At low plating current densities, i.e., up to 50 mA cm -2 , oxygen reduction occurs along with Zn and Co plating.The oxygen reduction is a diffusioncontrolled process, it drives the constant pH increment regardless of the current density applied, and so the Sm hydroxide deposition rate is constant.On the other hand, the rate of Zn and Co electroreduction increases with the applied current density which, in turn, causes a decrement in Sm hydroxide content (Figure 2). However, as the current density, i.e., the overpotential increases, the more intense hydrogen evolution takes part, and this reaction, contrary to the oxygen reduction, is activation controlled: its rate increases with the applied current.Consequently, the Sm Metals 2023, 13, 481 5 of 14 hydroxide precipitates in higher quantities at higher current densities, so the Sm amount in the coating increases as well, as reported in [13,22]. In this work, low current densities have been applied, that enable oxygen reduction under diffusion control and hydrogen evolution with low intensity, causing the Sm hydroxide precipitation on one side, but also the electroreduction of Zn and Co cations on the other side.The result is a compact Zn-Co-Sm hydroxide composite coating, with Sm content reaching 11 wt.%.The EDS analysis shows that the O:Sm ratio is close to 3:1 for all current densities, pointing to the fact that Sm(OH) 3 particles are incorporated in the Zn-Co coating. The glycine has been utilized as a complexing agent in our experiments, to elucidate whether it may enable the formation of oxygen-free, ternary Zn-Co-Sm alloy, i.e., the electrochemical reduction of Sm ion through the mechanism proposed by Schwartz et al. [18].However, the EDS analysis still depicts the Sm hydroxide incorporation in the coating.It is obvious from our results that glycine, as a complexing agent, inhibits the Zn and Co ion reduction, resulting in an increment in Sm hydroxide content.So, as a result, the glycine presence in the plating electrolyte (Figure 3) increases the Sm content in the coating.To sum up, the electroreduction of the Sm(III) ion to its metallic state (oxidation state zero) has not been recorded in our work. In this work, low current densities have been applied, that e under diffusion control and hydrogen evolution with low intens droxide precipitation on one side, but also the electroreduction o the other side.The result is a compact Zn-Co-Sm hydroxide com content reaching 11 wt.%.The EDS analysis shows that the O:Sm all current densities, pointing to the fact that Sm(OH)3 particles Zn-Co coating. The glycine has been utilized as a complexing agent in our e whether it may enable the formation of oxygen-free, ternary Zn-C trochemical reduction of Sm ion through the mechanism propose However, the EDS analysis still depicts the Sm hydroxide incorp is obvious from our results that glycine, as a complexing agent, in reduction, resulting in an increment in Sm hydroxide content.So presence in the plating electrolyte (Figure 3) increases the Sm co sum up, the electroreduction of the Sm(III) ion to its metallic sta has not been recorded in our work.The temperature effect on the chemical composition of the investigated, and Figure 3 shows that the Sm content in an alloy trolyte of higher temperature is applied, as also observed earlie that the higher temperature enables faster oxygen diffusion to which indirectly increases the rate of Sm deposition, bearing in m current densities, the Sm precipitation is oxygen driven process.
|
None
|
[
[],
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
4bfce037-5b1e-44ab-b2f4-6269404945ff
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:53.770000 |
3b2df8d7-4f61-45d7-9685-4b7291ed259b
|
[10.3390/en7042658](https://doi.org/10.3390/en7042658)
|
abstract
|
Microgrids are a highly efficient means of embedding distributed generation sources in a power system. However, if a fault occurs inside or outside the microgrid, the microgrid should be immediately disconnected from the main grid using a static switch installed at the secondary side of the main transformer near the point of common coupling (PCC). The static switch should have a reliable module implemented in a chip to detect/locate the fault and activate the breaker to open the circuit immediately. This paper proposes a novel approach to design this module in a static switch using the discrete wavelet transform (DWT) and adaptive network-based fuzzy inference system (ANFIS). The wavelet coefficient of the fault voltage and the inference results of ANFIS with the wavelet energy of the fault current at the secondary side of the main transformer determine the control action (open or close) of a static switch. The ANFIS identifies the faulty zones inside or outside the microgrid. The proposed method is applied to the first outdoor microgrid test bed in Taiwan, with a generation capacity of 360.5 kW. This microgrid test bed is studied using the real-time simulator eMegaSim developed by Opal-RT Technology Inc. (Montreal, QC, Canada). The proposed method based on DWT and ANFIS is implemented in a field programmable gate array (FPGA) by using the Xilinx System Generator. Simulation results reveal that the proposed method is efficient and applicable in the real-time control environment of a power system.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
4c940a80-98ea-4e29-a266-8ea913e8bf2f
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-20T09:33:06.966000 |
9b1dedc9-ba05-4208-bedc-d1e95a684d10
|
[10.3390/en7042658](https://doi.org/10.3390/en7042658)
|
Outline
|
Fault detection and location problems for both distribution and transmission systems have been extensively studied [15][16][17][18].The harmonic impedance [15], wavelet singular entropy [16], automated graph [17], and three different structures of neural networks incorporating with the negative current [18] were employed in these methods.However, since the inverter-based power converter in distributed generations is used, the fault current is not large and may not be easily detected if a fault occurs inside a microgrid.ANFIS, DWT and FPGA are used herein to cope with the above dilemma for the following reasons: (1) The small disturbance caused by faults inside a microgrid is detected using DWT because DWT is a transient-sensitive means of processing a signal.Both the wavelet coefficient of the transient voltage and the sum of squared wavelet coefficients (called wavelet energy herein) of the fault current are utilized to enhance the proposed method.The proposed method avoids negative sequence of components [18], which may be caused by unbalanced loads rather than balanced faults, and avoids the use of fault currents only [15], which may lead to a delay in the detection logic.( 2) Fuzzy reasoning provides a high-level linguistic inference engine that can tolerate uncertainty but lacks learning capability.An artificial neural network, by contrast, is like a black box but it can learn and tolerate imprecision.ANFIS is an intelligent system that integrates fuzzy reasoning with a neural network by considering their advantages.ANFIS builds a hybrid intelligent system that is capable of reasoning and learning in an uncertain and imprecise environment.However, three different neural networks, which are not subject to uncertainty and lack reasoning capability, were developed in [18].(3) The use of double detection/location logics (wavelet coefficient of transient voltage and ANFIS plus wavelet energy of transient current) enhances the reliability of the proposed method.The proposed method, therefore, is able to use only the transient voltage and current near PCC to detect and locate a fault.This capability is essential in case the plug-and-play and peer-to-peer implementations are concerned and the decentralized control is applied.However, references [15][16][17][18] used multiple sensors in the power systems.(4) The microgrid test bed is studied using the real-time simulator eMegaSim developed by Opal-RT Technology Inc. [13].The detection/location module established by the DWT and ANFIS is implemented in an FPGA using the Xilinx System Generator.Other studies in [16,17] are not suitable for real-time applications.
|
None
|
[
[],
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
622b1a7c-0a41-4c5f-9539-b5288a9bdd5e
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-08T14:23:28.808000 |
01939da0-2471-437f-beac-9c6e4496c28f
|
[10.3390/en11051066](https://doi.org/10.3390/en11051066)
|
abstract
|
Integrated energy system (IES) has received increasing attention in micro grid due to the high energy efficiency and low emission of carbon dioxide. Based on the technology of combined heat and power (CHP), this paper develops a novel operation mechanism with community micro turbine and shared energy storage system (ESS) for energy management of prosumers. In the proposed framework, micro-grid operator (MGO) equipped with micro turbine and ESS provides energy selling business and ESS leasing business for prosumers. Prosumers can make energy trading with public grid and MGO, and ESS will be shared among prosumers when they pay for the rent to MGO. Based on such framework, we adopt a cooperative game for prosumers to determine optimal energy trading strategies from MGO and public grid for the next day. Concretely, a cooperative game model is formulated to search the optimal strategies aiming at minimizing the daily cost of coalition, and then a bilateral Shapley value (BSV) is proposed to solve the allocation problem of coalition’s cost among prosumers. To verify the effectiveness of proposed energy management framework, a practical example is conducted with a community energy network containing MGO and 10 residential buildings. Simulation results show that the proposed scheme is able to provide financial benefits to all prosumers, while providing peak load leveling for the grid.
|
None
|
[
[],
[]
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Partially correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
null,
"energy storage, energy network and gird missed"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
4697e6c5-19bb-4a05-9010-b208b5a60a52
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:53.900000 |
1b9191a6-1ff6-4b2f-b7ec-dcaa9e907be0
|
[10.3390/en11051066](https://doi.org/10.3390/en11051066)
|
System Model
|
The structure of community energy network is shown in Figure 1.Community energy network is a micro integrated energy system which consists of MGO and multiple prosumers.MGO has micro turbine and ESS, who can sell electrical and thermal energy to prosumers, and meanwhile provide energy storage leasing business for prosumers.The scheduling and dispatching for turbine and energy storage are both executed by EMS of MGO.Each prosumer is equipped with EMS, PV generation, electrical load, thermal load.Note that, cooling load of each prosumer has been included in electrical load, and thermal load can obtain energy supply from micro thermal grid or power grid.Here, EMS of MGO is responsible by independent service department of MGO; while smart meter is in charge of the operation of prosumer's EMS.In the proposed scenario, prosumer can store surplus energy to ESS but needs to pay lease expense to the MGO.When prosumers have a high energy demand, they will take back the stored energy from storage or purchase energy from MGO and public.Furthermore, DR is considered in the scenario by public grid setting an effective pricing mechanism.In order to conduct DR project perfectly, we assume that prosumer EMS can control and schedule energy consumption of partial electrical load, and prosumer EMS will communicate with EMS of MGO via information network. Suppose that there are N prosumers in the whole community energy network with the set N = {1, 2, • • • , N}.Additionally, this paper is focused on the day-ahead energy scheduling, thus assume that a day is divided into T time slots with the set T = {1, 2, • • • , T}.
|
<li> <b>PV generation:</b> Solar photovoltaic (241000)
|
[
[
{
"end": 468,
"label": "energyType",
"start": 455
}
]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
{
"end": 468,
"label": "energyType",
"start": 455
}
] | null | null |
59fc62e6-cede-4465-9270-f450199bfcfc
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:53.989000 |
1ade65ad-d482-42a4-ba48-26d85cd8a918
|
[10.3390/en15072395](https://doi.org/10.3390/en15072395)
|
abstract
|
In the context of the economic situation, international relations, and the consequences of COVID-19, the future competition pattern of crude oil trade is uncertain. In this paper, the crude oil international import competition and export competition networks are based on a complex network model. The link prediction method is used to construct a crude oil competition relationship prediction model. We summarize the evolving characteristics of the competitive landscape of the global crude oil trade from 2000 to 2019 and explore the reasons for the changes. Finally, we forecast the future potential crude oil import and export competition. The results indicate the following. (1) The crude oil import competition center is transferred from Europe and America to the Asia–Pacific region and it may continue to shift to developing regions. (2) At present, the competition among traditional crude oil exporters is the core of crude oil export competition, such as OPEC, Canada, and Russia. The United States has become the world’s largest crude oil exporter, which means that the core of crude oil export competition has begun to shift to emerging countries. The competition intensity of emerging crude oil exporters is gradually increasing. There is likely to be fierce export competition between traditional and emerging exporters. (3) In the future crude oil competition, we should pay attention to the trend of the United States, which may lead to the restructuring of the global oil trade pattern. Finally, this paper considers the exporters and importers and puts forward policy suggestions for policymakers to deal with the future global crude oil trade competition.
|
<li> <b>crude oil:</b> Conventional crude oil (114100)
|
[
[
{
"end": 144,
"label": "energyType",
"start": 135
},
{
"end": 193,
"label": "energyType",
"start": 184
},
{
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"label": "energyType",
"start": 347
},
{
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"label": "energyType",
"start": 485
},
{
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"label": "energyType",
"start": 602
},
{
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"label": "energyType",
"start": 687
},
{
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"label": "energyType",
"start": 891
},
{
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"label": "energyType",
"start": 926
},
{
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"label": "energyType",
"start": 1039
},
{
"end": 1097,
"label": "energyType",
"start": 1088
},
{
"end": 1206,
"label": "energyType",
"start": 1197
},
{
"end": 1361,
"label": "energyType",
"start": 1352
},
{
"end": 1654,
"label": "energyType",
"start": 1645
}
]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
{
"end": 144,
"label": "energyType",
"start": 135
},
{
"end": 193,
"label": "energyType",
"start": 184
},
{
"end": 356,
"label": "energyType",
"start": 347
},
{
"end": 494,
"label": "energyType",
"start": 485
},
{
"end": 611,
"label": "energyType",
"start": 602
},
{
"end": 696,
"label": "energyType",
"start": 687
},
{
"end": 900,
"label": "energyType",
"start": 891
},
{
"end": 935,
"label": "energyType",
"start": 926
},
{
"end": 1048,
"label": "energyType",
"start": 1039
},
{
"end": 1097,
"label": "energyType",
"start": 1088
},
{
"end": 1206,
"label": "energyType",
"start": 1197
},
{
"end": 1361,
"label": "energyType",
"start": 1352
},
{
"end": 1654,
"label": "energyType",
"start": 1645
}
] | null | null |
7957d585-f0c0-4c40-83cb-e3a766d4919e
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-05T07:37:08.429000 |
c9051b5a-9ee1-41f6-9414-83d056df2457
|
[10.3390/en5072545](https://doi.org/10.3390/en5072545)
|
abstract
|
This paper is concerned with the protection of wind energy systems against the direct effects of lightning. As wind power generation undergoes rapid growth, lightning damages involving wind turbines have come to be regarded as a serious problem. Nevertheless, very few studies exist yet in Portugal regarding lightning protection of wind energy systems using numerical codes. A new case study is presented in this paper, based on a wind turbine with an interconnecting transformer, for the analysis of transient phenomena due to a direct lightning strike to the blade. Comprehensive simulation results are provided by using models of the Restructured Version of the Electro-Magnetic Transients Program (EMTP), and conclusions are duly drawn.
|
<li> <b>wind energy systems:</b> Wind energy (230000)<li> <b>wind power generation:</b> Wind energy (230000)<li> <b>wind turbines:</b> Wind energy (230000)
|
[
[
{
"end": 66,
"label": "energyType",
"start": 47
},
{
"end": 352,
"label": "energyType",
"start": 333
},
{
"end": 132,
"label": "energyType",
"start": 111
},
{
"end": 198,
"label": "energyType",
"start": 185
},
{
"end": 444,
"label": "energyType",
"start": 432
}
],
[
{
"end": 66,
"label": "energyType",
"start": 47
},
{
"end": 352,
"label": "energyType",
"start": 333
},
{
"end": 132,
"label": "energyType",
"start": 111
},
{
"end": 198,
"label": "energyType",
"start": 185
}
]
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Partially correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
{
"end": 66,
"label": "energyType",
"start": 47
},
{
"end": 352,
"label": "energyType",
"start": 333
},
{
"end": 132,
"label": "energyType",
"start": 111
},
{
"end": 198,
"label": "energyType",
"start": 185
}
] | null | null |
7f229484-26d1-418d-94f5-ec115e113977
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-08T14:24:39.865000 |
4ca43d34-fdf9-4f4b-80e4-a16a02fd5585
|
[10.3390/en5072545](https://doi.org/10.3390/en5072545)
|
Capacitive Coupling
|
The capacitive effect between the tower and the cable inside or the LV/HV transformer has been considered because the lightning current flowing through the tower will increase radically its potential.In these circumstances disruptions could occur and consequently dangerous overvoltages to the equipment.The values used for capacitances in this model are theoretical.
|
None
|
[
[],
[]
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct that there isn't one\n",
null
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
8bc55b18-0a50-4669-93d0-f3cf1d520c90
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:54.124000 |
0cfb320b-6226-4a5e-81c1-3532cbdc1e6e
|
[10.1186/s43251-020-00001-y](https://doi.org/10.1186/s43251-020-00001-y)
|
abstract
|
AbstractStructural analysis and construction control of staged construction process is a major subject for modern long-span bridges. This paper introduces the concept of stress-free-state variable of structural elements and deduces the mechanical equilibrium equations and geometric shape governing equations for staged construction structures utilizing the minimum potential energy theorem. As the core of stress-free-state theory, the two aforementioned equations demonstrate following principles, 1) when the stress-free-state variable of a structural element is set, the internal force and deformation of the element are unique at the completion state of the structure regardless of its construction process; 2) the stress-free length of a cable is independent of its external loads, change in stress-free length of the cable corresponds to a unique variation of the cable force when load is constant; and 3) the internal force of a structural element can be independent from its geometric shape within the completion state of a staged construction structure through an active manipulation of stress-free-state variables of the element. Stress-free-state theory establishes the stage-to-stage and stage-to-completion relationships for staged construction bridges, provides a direct and efficient method for theoretical calculations and a flexible and convenient approach for the control of staged construction, and makes parallel construction and auto-filtering of thermal and temporary loading effect possible.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
fba7696c-d46c-4ee6-8355-81afc912a413
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:54.248000 |
6fcb0516-be11-41df-a5ec-24b4f74b2ac7
|
[10.1186/s43251-020-00001-y](https://doi.org/10.1186/s43251-020-00001-y)
|
Conclusions
|
Structural analysis and construction control of staged construction process is a major subject for the modern long-span bridges.This paper introduced the concept of stressfree-state variable of structural elements and briefly deduced the mechanical equilibrium equations and geometric shape governing equations for the staged construction bridge structure utilizing the minimum potential energy theorem.Three basic principles of the stress-free-state theory are drawn as follows, 1) When the stress-free-state variable of a structural element is set, the internal force and deformation of the element are unique at the completion state of the structure regardless of its construction process. 2) The stress-free length of a cable is independent of its external loads, and the change in stress-free length of the cable corresponds to a unique variation of the cable force when the external load is constant. 3) The internal force of a structural element can be independent from its geometric shape within the completion state of a staged construction structure through an active manipulation of stress-free-state variables of the element. Stress-free state theory establishes the stage-to-stage and relationships for the staged construction of bridges, provides a direct and efficient method for theoretical calculations and a flexible and convenient approach for the control of staged construction, and makes parallel construction and auto-filtering of thermal and temporary loading effect possible.The successful applications of the stress-free-state theory in the staged construction controls of nearly one hundred long-span bridges prove that the theory is an efficient and universal method in the structural analysis and construction control for staged construction of bridges.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
001c4354-f0d3-4978-bdf1-2d366266ba5b
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:54.339000 |
853517d2-dd08-4df0-a933-c29e6fbb4420
|
[10.2516/ogst/2015015](https://doi.org/10.2516/ogst/2015015)
|
abstract
|
Solar driven water splitting can be achieved by coupling electrolyzers with PhotoVoltaics (PV). Integration of both functions in a compact PhotoElectroChemical (PEC) cell is an attractive option but presents significant scientific challenges. In this work, the design of single- and dual-compartment PEC cells for research purposes is discussed. The fabrication of separator-electrode assemblies is an important aspect, and upscaling of these architectures even to centimeter scale is not trivial. The layout of a new dual-compartment compact PEC cell with in-situ monitoring of pH, temperatures, and oxygen and hydrogen evolution for research purposes is presented. Finally, a prospect of future PEC cells for practical applications is presented.
|
<li> <b>PhotoVoltaics (PV):</b> Solar photovoltaic (241000)
|
[
[
{
"end": 94,
"label": "energyType",
"start": 76
}
]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
{
"end": 94,
"label": "energyType",
"start": 76
}
] | null | null |
dedb90db-55f7-4c58-a26c-cd07145433ee
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-20T09:41:36.113000 |
3d1a3425-ed53-4f0b-8054-6c47ae2feeef
|
[10.2516/ogst/2015015](https://doi.org/10.2516/ogst/2015015)
|
ADVANCED RESEARCH PEC CELLS
|
State-of-the-art exPEC cells offers access to a variety of relevant experimental parameters, namely illumination intensity and composition, electrolyte composition (concentration and pH), reactant flow rates, and gas composition. There is ample room for refinement and sophistication.Future exPEC cells should enable investigation of the influence of assembly configuration, geometry, temperature, humidity, light incident angle, etc.For this aim, a new dual-compartment exPEC cell with additional functionalities was designed (Fig. 10).The cell is divided in two compartments and consists of two modular half-cells which can be fabricated and optimized separately.Each half-cell is fabricated out of PEEK and is equipped with a quartz window (1) which is pressed into the PEEK half-cell and sealed with a square-shaped polymer sealing.The illuminated surface area is 3 9 3 cm extendable by using a larger window.Each half-cell was manufactured from a solid PEEK block through mechanical milling.The in-and outflow of the cell are conceived for an even flow distribution.At the inlet (2), the flow enters a cylindrical channel after which it is equally divided into 5 smaller cylindrical channels (4).Before reaching the SEA surface, these 5 channels gather into one common channel to redistribute the flow.The flow channel over the sample chamber is approximately 1 mm high to avoid product buildup in dead volumes.The path for reactant and product flow in gas or liquid phase is well defined.The SEA ( 5) can be mounted in between these two half-cells, each of which seal off the sample from the environment by a square-shaped sealing ( 6).An electrical contact with the sample is obtained by a connection with four spring contacts located at the four corners of the sample for an equal current or potential distribution across the sample surface area.Numerical simulations of the 3-D design were performed to evaluate the uniformity of the flow.Width and height of the different channels were varied as well as the flow velocity.A constant hydrogen production activity across the sample surface was assumed.The resulting pressure loss, concentration gradient across the sample surface and velocity profile were calculated using numerical software.The results showed no significant impact of the variables on the observables and thus it was concluded that an equal distribution of the flow over the sample surface could be obtained with this design.Additionally, the model showed that the products can be evacuated from the flow channel without creating a significant concentration gradient over the sample surface (Fig. 11). By adjusting the height of the quartz window, it is possible to implement sensors close to the sample surface.Sealable insertion holes for the implementation of various sensors is envisioned.Reference electrodes can be inserted for (photo)electrochemical testing in 3-or 4-electrode setup.pH sensors can be mounted for in situ investigation of pH gradients.Such pH gradients over SEA recently have been simulated and experimentally observed (Hernández-Pagán et al., 2012;Jin et al., 2014).Additionally, O 2 -and H 2 -microsensors fitting in the flow channel can be mounted for time resolved reaction monitoring, close to the active SEA surface.Temperatures can be monitored by insertion of thermocouples or by infrared detection directly on the surface.
|
None
|
[
[],
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
e9a85bff-953b-4133-ac99-aa4c0d0d167c
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:54.466000 |
5eb40c93-d332-455c-a6bb-12fdeaa12e55
|
[10.15632/jtam-pl/128901](https://doi.org/10.15632/jtam-pl/128901)
|
abstract
|
This article aims to present a report of experimental and numerical investigations on crashworthiness characteristics of single and multi-cell/bi-tubular structures. Novel multi--cell/bi-tubular structures are proposed in order to improve the crashworthiness performance, LS-DYNA FE software is applied for the modelling of axial crashing behaviour to validate with experimental results and a good agreement is observed. The KPIs are used to compare various structures and to determine the best performing ones. The investigations reveal that the HMC4 has significantly obvious effects on the structural crashworthiness and improved 515% energy absorption efficiency. Afterward, a parametric study has been carried out for the best energy absorber.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
55667521-64d6-489c-994b-65f37376ba87
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:54.553000 |
aaef0115-0034-4c1a-a3c1-d7bc93d97714
|
[10.15632/jtam-pl/128901](https://doi.org/10.15632/jtam-pl/128901)
|
Specific Energy Absorption (SEA)
|
Specific energy absorption is considered as retained energy per unit mass of the thin-walled sections.It is one of the common criteria for comparing the energy absorption capacity of structures with distinctive mass which is given by where TEA is the Total Energy Absorption, TEA = δ 0 F (δ) dδ and F is the direct crashing force with a work of the crashing distance δ; m is mass of the structure.
|
None
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[]
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"submitted"
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"Partially correct"
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[
"submitted"
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[
"Partially correct"
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[
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[
"energy (generic) missed"
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"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
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[
"submitted"
] |
[] | null | null |
56c68e2f-694e-472b-87b0-5e05305ef2c2
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-05T07:38:54.002000 |
c9322d19-c91f-4dfe-b0e5-266b150056dd
|
[10.3390/molecules25040802](https://doi.org/10.3390/molecules25040802)
|
abstract
|
Concerns about depleting fossil fuels and global warming effects are pushing our society to search for new renewable sources of energy with the potential to substitute coal, natural gas, and petroleum. In this sense, biomass, the only renewable source of carbon available on Earth, is the perfect replacement for petroleum in producing renewable fuels. The aviation sector is responsible for a significant fraction of greenhouse gas emissions, and two billion barrels of petroleum are being consumed annually to produce the jet fuels required to transport people and goods around the world. Governments are pushing directives to replace fossil fuel-derived jet fuels with those derived from biomass. The present mini review is aimed to summarize the main technologies available today for converting biomass into liquid hydrocarbon fuels with a molecular weight and structure suitable for being used as aviation fuels. Particular emphasis will be placed on those routes involving heterogeneous catalysts.
|
<li> <b>biomass:</b> Bioenergy (260000)<li> <b>fossil fuels:</b> Fossil fuels (110000)<li> <b>natural gas:</b> Natural gas (113000)<li> <b>petroleum:</b> Oil (114000)<li> <b>coal:</b> Coal (111000)
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76949986-70af-4aaf-ac95-b4a232bc3b83
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-03T08:44:27.008000 |
5ffe87cf-d636-41cb-8c96-69b6a9d14cba
|
[10.3390/molecules25040802](https://doi.org/10.3390/molecules25040802)
|
Gas to Jet Fuels
|
As shown in Figure 2, the GTJ route is comprised of two different processes, namely, biomass gasification to syngas (H 2 /CO), followed by Fischer-Tropsch conversion of this syngas into jet fuel hydrocarbons [52].Gasification is a well-developed technology that allows conversion of virtually any carbon source (natural gas, coal, biomass) into a mixture of gaseous species (e.g., CO, H 2 , CO 2 , CH 4 ) by applying a treatment at high temperatures under a carefully controlled oxidizing atmosphere (e.g., air, steam, oxygen).Control over the composition of the gas stream is difficult, with a large number of factors (biomass source, particle size, gasification conditions, and gasifier design) having an influence on the gasification performance [53].Pure oxygen atmospheres, high temperatures (1300 • C), and high pressures lead to gas streams enriched in syngas [54].The utilization of biomass feedstocks versus fossil carbon sources has two important implications for the downstream Fischer-Tropsch process.First, compared to coal or natural gas, biomass contains a larger number of impurities (N, Cl, S, tars, ashes, alkali) that are typically found accompanying CO and H 2 in the gas stream.These impurities are particularly problematic because they deactivate Fischer-Tropsch catalysts.Second, the high oxygen content of biomass compared to fossil fuels results in syngas streams with H 2 /CO ratios (ca.0.5) well below those required for the Fischer-Tropsch synthesis of hydrocarbons (ca.2) [55].Thus, before reaching the Fischer-Tropsch unit, the syngas delivered by the gasifier must be deeply cleaned and compositionally adjusted by performing additional cleaning and water gas shift (WGS) steps, respectively.These extra cleaning and WGS units significantly increase the complexity and cost of the GTJ process.Once the syngas is cleaned and compositionally adjusted, it can be fed to the Fischer-Tropsch reactor.The Fischer-Tropsch synthesis is a well-known highly exothermic industrial process that allows the conversion of syngas into a mixture of hydrocarbons with low carbon-chain selectivity (C 1 -C 50 ) over metal-based catalysts at moderate temperatures and pressures [56].The hydrocarbon distribution depends highly on both the operating conditions (temperature and pressure) and the catalyst composition.For instance, cobalt-based catalysts are particularly active in producing linear alkanes [57,58], while iron-based catalysts are more selective toward olefins and can operate at lower H 2 /CO ratios because of their significant WGS activity.Oxygenated compounds such as alcohols, aldehydes, and carboxylic acids are typically produced in the process along with the hydrocarbons.Addition of promoters such as K to Fe catalysts allows for an increase in the selectivity to jet fuel range hydrocarbons, as recently demonstrated by Martinez del Monte et al. [59].The large amount of heat released during the Fischer-Tropsch process must be removed rapidly to avoid high temperatures in the reactor, which favor the formation of CH 4 and lead to catalyst deactivation.In order to produce hydrocarbons in the jet fuel range (C 9 -C 16 ), heavy hydrocarbons (waxes) can be produced first by operating at low temperatures (230 • C), followed by controlled cracking and isomerization steps to jet fuel components [60].Thus, conventional petrochemical units such as hydrocracking, isomerization, and fractionation are normally required after the Fischer-Tropsch reactor to adjust the molecular weight and structure of the hydrocarbons to the jet fuel range.As in the case of the OTJ process, the jet-fuel obtained by this route lacks aromatics, thereby avoiding utilization of 100% renewable fuel and requiring blend mixtures. The high complexity of the GTJ route is an important factor limiting the commercialization of this technology.In fact, this process is only cost effective at large scales, which is counterproductive when using low energy density feeds such as biomass [38].The chemical composition of biomass (i.e., high oxygen content and presence of impurities) increases the complexity of the GTJ route compared to routes starting from carbon or natural gas.Thus, according to Hileman et al. [61], the production costs of jet fuels obtained by biomass gasification are ca.20% higher than those obtained by gasification of coal.The cost of the feedstock and the temperature of the gasifier accounts for a significant fraction of the production costs of the fuel.In this sense, higher temperature gasifiers are preferred since they allow the complexity of the syngas cleaning process to be reduced by providing cleaner gas streams and faster gasification kinetics.For a GTJ plant of 2000 tons per day, Anex et al. [62] reported significantly higher capital expenses when low-temperature gasifiers were used (610 vs. 500 M$ for gasifiers operating at 870 vs. 1300 • C, respectively).The GTJ route has higher capital costs than other thermochemical processes.The biomass pretreatment (mostly drying and mechanical particle size reduction), gasification, and syngas cleaning/conditioning units account for most of these capital expenses.In a recent study, Sahir et al. [63] analyzed the cost of producing liquid fuels from biomass/natural gas mixtures.Minimum selling prices ranging from 2.47 to 3.47 $/gasoline gallon equivalent (gge) were obtained in this study for a 50 million GGE/year facility.The addition of a hydrocracker allowed a substantial increase in the yield of diesel and jet fuel hydrocarbons, although this increase did not offset the higher capital expenses of the new unit. The CO 2 generated by fossil fuel combustion in the gasifier and the emissions resulting from the Fischer-Tropsch reactor account for most of the GHG emissions of the GTJ process.Despite these emissions, the GTJ process achieved significant reduction of the GHG emissions (ca.90%) compared to conventional jet fuel processes [64], provided that biomass can supply nearly half of the energy required to drive gasification and Fischer-Tropsch.GHG emissions as low as 2-10 g CO 2 /MJ have been reported for GTJ processes with corn stover, forest residues, and switchgrass as biomass feedstocks [65].In this sense, the GTJ route is more attractive than the OTJ route, which has higher GHG emissions associated with the utilization of fertilizers to grow the oil plant. The high capital costs of the GTJ route have prevented large companies from investing in large facilities, and only test/pilot plants have been developed.Technical challenges associated with the handling of biomass and cleaning of the syngas have delayed (or even cancelled) industrial efforts to bring this technology to commercial status [66].Despite these difficulties, a number of companies such as Red Rock Biofuels, Sasol, Fulcrum, and Total have built facilities with capacities of 30-48,000 tons/year of biomass (wood, municipal wastes), and some of them are intended to be operative this year [67][68][69][70].Some of these companies have signed agreements with airline companies to supply renewable jet fuel.The GTJ fuel has been ASTM certified for commercial use blended with petroleum-derived jet fuel up to 50% [71] The lack of aromatics in the jet fuel is the main limitation to increasing the concentration of renewable jet fuel in these blends.Slight variations of the GTJ technology have been developed to overcome this limitation.These variations involve additional steps such as aromatization of a fraction of the syncrude or the addition of naphtha fractions enriched in monoaromatics.This new technology has been denoted as Fischer-Tropsch synthetic kerosene with aromatics (FT-SKA).This aromatic-containing jet fuel has been approved to be blended with Jet A1 conventional fuel in amounts up to 50 vol% [72].
|
<li> <b>biomass:</b> Bioenergy (260000)<li> <b>natural gas:</b> Natural gas (113000)<li> <b>coal:</b> Coal (111000)<li> <b>syngas:</b> Natural gas products (113300)<li> <b>jet fuel:</b> Kerosene-type jet fuel (114561)
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] | null | null |
0e481bae-67c3-4235-a91b-b075ab009e86
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:54.682000 |
d5d8b46e-55ec-4585-88b8-50d17c6400c0
|
[10.3390/en16237837](https://doi.org/10.3390/en16237837)
|
abstract
|
The decline in power quality within electrical networks is adversely impacting the energy efficiency and safety of transmission elements. The growing prevalence of power electronics has elevated harmonic levels in the grid to an extent where their significance cannot be overlooked. Additionally, the increasing integration of renewable energy sources introduces heightened fluctuations, rendering the prediction and simulation of working modes more challenging. This paper presents an improved algorithm for calculating power transformer losses attributed to harmonics, with a comprehensive validation against simulation results obtained from the Power Factory application and real-world measurements. The advantages of the algorithm are that all evaluations are performed in real-time based on single-point measurements, and the algorithm was easy to implement in a Programmable Logic Controller (PLC). This allows us to receive the exchange of information to energy monitoring systems (EMSs) or with Power factor Correction Units (PFCUs) and control it. To facilitate a more intuitive understanding and visualization of potential hazardous scenarios related to resonance, an extra Dijkstra algorithm was implemented. This augmentation enables the identification of conditions, wherein certain branches exhibit lower resistance than the grid connection point, indicating a heightened risk of resonance and the presence of highly distorted currents. Recognizing that monitoring alone does not inherently contribute to increased energy efficiency, the algorithm was further expanded to assess transformer losses across a spectrum of Power Factory Correction Units power levels. Additionally, a command from a PLC to a PFCU can now be initiated to change the capacitance level and near-resonance working mode. These advancements collectively contribute to a more robust and versatile methodology for evaluating power transformer losses, offering enhanced accuracy and the ability to visualize potentially critical resonance scenarios.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
e7852b0a-7349-40ba-b3d6-384cbbf06e3e
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-08T14:57:56.520000 |
05024d43-0e64-4b08-864f-7f496acc601a
|
[10.3390/en16237837](https://doi.org/10.3390/en16237837)
|
Results
|
To check the accuracy of implemented the algorithm, the same conditions as those presented in article [54] were modeled in a Power Factory environment.The model consisted of two MV voltage connection points, which were the first branch representing the consumer with the transformer and PFCU and the second branch representing the current distortion source.The model of the Power Factory environment is shown in Figure 5.The Dijkstra algorithm's implementation allows us to monitor frequency sweep changes in bigger systems and detect dangerous resonance scenarios in real time.
|
None
|
[
[],
[]
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
df7debe8-3c72-4a1c-a81b-be92614ea919
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:54.811000 |
695bf7ad-5fe9-46fd-84a9-20633199d9d4
|
[10.3390/pr9101744](https://doi.org/10.3390/pr9101744)
|
abstract
|
This study aims to quantify the climate change impact of pyrochar production from pulp and paper mill sludge and the subsequent utilisation in combined heat and power (CHP) plants for co-generation of heat and electricity using the environmental life cycle assessment (E-LCA) method. In the Pyrochar Scenario, in which the sludge is pyrolyzed into pyrochar, the authors have assumed that pyrochar would replace coal. In the Reference Scenario, sludge is incinerated with a subsequent low rate of energy recovery. A comprehensive sensitivity analysis was performed to determine the conditions in which the sludge pyrochar would offer the greatest climate-effect benefits. The parameters selected for the said analysis are the form of pyrochar (pellet or powder), fuels replaced by it in the CHP plant (solid waste and peat vis-à-vis coal), and the utilisation of the pyrochar fuel in another European country (Germany and Spain vis-à-vis Sweden). The results of this E-LCA clearly show that using pyrochar as a biofuel in CHP plants delivered a considerable reduction in greenhouse gas (GHG) emissions (−1.87 tonne CO2-eq per 2.8 tonne dry sludge). Contribution analysis reveals that the process accounting for the biggest share of the reduction is the pyrochar combustion (a negative contribution of 76%), which results in a displacement of coal-based fuels. The authors conclude that the utilisation of pyrochar in firing units would provide the highest reduction in GHG emissions, while recommending a comprehensive economic analysis in addition to climate effect assessment, before making a decision regarding the introduction of sludge pyrochar to the energy sector.
|
<li> <b>pyrochar:</b> Solid biofuels (261000)<li> <b>coal:</b> Coal (111000)<li> <b>peat:</b> Peat (112100)<li> <b>solid waste:</b> Renewable waste (264000)
|
[
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[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
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[
"submitted"
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[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
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[
"submitted"
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[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
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[
null
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{
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}
] | null | null |
25b2ad6d-f3bc-4742-8187-e7d7cc6c683d
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:54.930000 |
4bb12a31-0dc5-4330-8357-a504df638ecf
|
[10.3390/pr9101744](https://doi.org/10.3390/pr9101744)
|
Material Flow Analysis
|
Material flow analysis (MFA) is indispensable for a systematic assessment of the flows and stocks of materials/substances within the designed scenarios as well as to provide the basis for the subsequent E-LCA study.MFA, in other words, is a necessary precursor to E-LCA.In this assessment, the sludge (on dry mass basis) and the other input materials were taken into account in all the processes, and the flows of carbon (in the sludge) and energy in the entire life cycle of Pyrochar Scenario, were quantified (refer Section 2.4). The amounts and forms of inflows to a process in an MFA may be different from those of the output flows, especially in transformation processes like pyrolysis or incineration.The partitioning of a material in a process, and its transfer into another process is calculated and presented, with the aid of so-called transfer coefficients (TC) (refer Equation ( 1)).The TC can link the ratio between inflow (X input ) and outflow (X output ) or the efficiency of conversion of input primary energy to output final-use energy, as shown in Equation (2).
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
9253af17-f16f-487f-bcc8-84fead25d735
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:55.014000 |
5c06143c-a4db-4596-b0b2-d467e951f2c3
|
[10.3390/en16104075](https://doi.org/10.3390/en16104075)
|
abstract
|
Induced seismicity has been a serious problem for many coal mines in the Upper Silesian Coal Basin in Poland for many decades. The occurring mining tremors of the rock mass generate seismic vibrations that cause concern to the local population and in some rare cases lead to partial damage to buildings on the surface. The estimation of peak ground acceleration values caused by high energy mining seismic tremors is an important part of seismic hazard assessment in mining areas. A specially designed bootstrapping procedure has been applied to estimate the ground motion prediction model and makes it possible to calculate the confidence intervals of these peak ground acceleration values with no assumptions about the statistical distribution of the recorded seismic data. Monte Carlo sampling with the replacement for 132 seismic records measured for mining seismic tremors exceeding 150 mm/s2 have been performed to estimate the mean peak ground acceleration values and the corresponding upper limits of 95% confidence intervals. The specially designed bootstrap procedure and obtained ground motion prediction model reflect much better the observed PGA values and therefore provide more accurate PGA estimators compared to the GMPE model from multiple regression analysis. The bootstrap analysis of recorded peak ground acceleration values of high-energy mining tremors provides significant information on the level of seismic hazard on the surface infrastructure. A new tool has been proposed that allows for more reliable determination of PGA estimators and identification in the areas in coal mines that are prone to high-energy seismic activity.
|
None
|
[
[
{
"end": 59,
"label": "energyType",
"start": 55
},
{
"end": 1601,
"label": "energyType",
"start": 1597
}
]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"coal missed"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
6ae4754a-c115-414f-9628-5e7f18cef4a6
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:55.105000 |
cb3ff53c-c2fa-4aa7-a5ac-d4fd73ed973d
|
[10.3390/en16104075](https://doi.org/10.3390/en16104075)
|
Multiple Regression Results of Ground Motion Prediction Equations, GMPE
|
The calculated regression parameters of Equations ( 1) and ( 2) for the logarithm of the peak ground acceleration, PGA, are presented in Table 2. Figure 6 shows the recorded values of the logarithm of the peak ground acceleration at the surface stations and the theoretical values determined by the GMPE model ( 1).This regression procedure includes all the gathered seismic data records.A large discrepancy between theoretical and observed peak ground acceleration values can be readily noticed for extreme, i.e., low and high, PGA values in Figure 6.For low peak ground acceleration values, a significant overestimation of the GMPE model is visible, whereas for high peak ground acceleration values, the empirical values are significantly higher than the theoretical values determined by the GMPE model.As mentioned earlier, the solution to this problem can be to estimate the GMPE model parameters of peak ground acceleration models (1) and (2) only on the basis of seismic PGA records exceeding a certain predetermined threshold.Therefore, in further analysis, it was assumed that seismic records with PGA values not lower than 150 mm/s 2 would be included in calculations.This 150 mm/s 2 threshold value corresponds to the lower limit of the first degree of the mining seismic intensity scale, GSIS-2017 [3], and makes it possible to include seismic PGA records felt by local communities on the surface.This threshold value resulted in limiting the sample to 132 observations and also shows that only about 5% of all seismic PGA records caused noticeable effects on the surface infrastructure according to the GSIS-2017 mining seismic intensity scale.Figure 7a shows the recorded values of the logarithm of peak ground acceleration at the surface stations and the theoretical values determined by the GMPE model ( 1) for all seismic records.Figure 7b shows the recorded values of the logarithm of peak ground acceleration at the surface stations and the theoretical values determined by the GMPE model ( 1) for the seismic records with PGA values not lower than 150 mm/s 2 .It can be easily noticed that the discrepancy between the theoretical and observed peak ground acceleration values is much smaller for the GMPE model ( 1) which includes only seismic records with PGA values not lower than 150 mm/s 2 (Figure 7b).This partially validates the concept of using PGA values not lower than 150 mm/s 2 in the regression procedure.The calculated regression parameters of Equation ( 1) for the logarithm of peak ground acceleration with PGA values not lower than 150 mm/s 2 are presented in Table 3.A large discrepancy between theoretical and observed peak ground acceleration values can be readily noticed for extreme, i.e., low and high, PGA values in Figure 6.For low peak ground acceleration values, a significant overestimation of the GMPE model is visible, whereas for high peak ground acceleration values, the empirical values are significantly higher than the theoretical values determined by the GMPE model.As mentioned earlier, the solution to this problem can be to estimate the GMPE model parameters of peak ground acceleration models ( 1) and ( 2) only on the basis of seismic PGA records exceeding a certain predetermined threshold.Therefore, in further analysis, it was assumed that seismic records with PGA values not lower than 150 mm/s 2 would be included in calculations.This 150 mm/s 2 threshold value corresponds to the lower limit of the first degree of the mining seismic intensity scale, GSIS-2017 [3], and makes it possible to include seismic PGA records felt by local communities on the surface.This threshold value resulted in limiting the sample to 132 observations and also shows that only about 5% of all seismic PGA records caused noticeable effects on the surface infrastructure according to the GSIS-2017 mining seismic intensity scale. Figure 7a shows the recorded values of the logarithm of peak ground acceleration at the surface stations and the theoretical values determined by the GMPE model ( 1) for all seismic records.Figure 7b shows the recorded values of the logarithm of peak ground acceleration at the surface stations and the theoretical values determined by the GMPE model ( 1) for the seismic records with PGA values not lower than 150 mm/s 2 .It can be easily noticed that the discrepancy between the theoretical and observed peak ground acceleration values is much smaller for the GMPE model ( 1) which includes only seismic records with PGA values not lower than 150 mm/s 2 (Figure 7b).This partially validates the concept of using PGA values not lower than 150 mm/s 2 in the regression procedure.The calculated regression parameters of Equation ( 1) for the logarithm of peak ground acceleration with PGA values not lower than 150 mm/s 2 are presented in Table 3.The regression GMPE model parameters in Table 3 are statistically significant.Nevertheless, it is not enough to use this model for the prediction of peak ground acceleration values (PGA).The prediction accuracy and the correct construction of the confidence intervals require us to conduct the verification of the estimated GMPE model in terms of the normality and homoscedasticity of the random component.For the analyzed GMPE model shown in Table 3, the p-values were calculated for the Kolmogorov-Smirnov and Anderson-Darling statistical tests verifying the normality of the residual component.The obtained p-values are 0.0175 and 0.0197, respectively, indicating that the distribution of the residual component of this model does not form the normal distribution at the significance α = 0.05.Additionally, the Breusch-Pagan statistical test indicates the presence of heteroscedasticity in the analyzed model.Therefore, there are no grounds at the level of α = 0.05 to reject the hypothesis of the homoscedasticity of the random component. Therefore, a bootstrap approach was used to estimate the model parameters and to determine the confidence intervals of the forecasts.This approach does not require the normality and homoscedasticity of the random component. Bootstrap model of ground motion prediction equations (GMPE) obtained from seismic data records with PGA values exceeding 150 mm/s 2 . In order to determine the bootstrap model of ground motion prediction equations (GMPE), we have also constrained our seismic records to PGA values exceeding 150 mm/s 2 .We have utilized the bootstrap procedure described in Section 2.2.2 and assumed that the number of replications r is equal to 1000.The number of bootstrap replications needed depends on the precision required for the estimation and the complexity of the model being analyzed.In general, the more bootstrap samples are used, the more accurate the estimation of the parameter of interest or the sampling distribution of a statistic will be.However, as the number of bootstrap samples increases, so does the computational cost of the analysis.There is no fixed number of bootstrap replications that can be universally recommended, as the appropriate number depends on the specific analysis and research question.A common rule of thumb is to use at least 1000 bootstrap samples to obtain stable and reliable estimates [27]. Based on these 1000 resamplings with replacement replications, we have estimated the mean values of the parameters of the GMPE model ( 1) and the corresponding lower and upper limits of 95% confidence intervals.These values are presented in Table 4.A comparison of the GMPE bootstrap model with the GMPE linear regression m from Table 3 is shown in Figure 9.It is clearly seen that theoretical values determined f the bootstrap GMPE model better correspond to the observed PGA values, i.e., the di ences between theoretical and recorded PGA values are smaller for most of the obse tions for the second level of mining seismic intensity scale GSIS-2017 and in all obse tions of the third and fourth levels of the mining seismic intensity scale GSIS-2017.T 5 summarizes these findings for the PGA values exceeding 600 mm/s 2 .The differe between the theoretical values of the GMPE bootstrap model and the GMPE linear reg sion model from Table 3 reach 136 mm/s 2 .Therefore, the bootstrap analysis of reco peak ground acceleration values of high-energy mining tremors can provide impor information regarding the level of seismic hazard on the surface infrastructure by esti ing the level of the mining seismic intensity scale, Figure 9.By estimating bootstrap P values caused by high-energy mining tremors, it is possible to assess the seismic ha on the surface infrastructure related to the level of the mining seismic intensity scale example, if the probability of the level of the mining seismic intensity scale is high, the surface infrastructure may be at a higher risk of damage or failure due to the gro motions caused by the tremors.Thus, the proposed tool may be directly applicable preventing damage to buildings and protecting local populations by identifying are coal mines that are prone to high-energy seismic activity and strong ground motions A comparison of the GMPE bootstrap model with the GMPE linear regression model from Table 3 is shown in Figure 9.It is clearly seen that theoretical values determined from the bootstrap GMPE model better correspond to the observed PGA values, i.e., the differences between theoretical and recorded PGA values are smaller for most of the observations for the second level of mining seismic intensity scale GSIS-2017 and in all observations of the third and fourth levels of the mining seismic intensity scale GSIS-2017.Table 5 summarizes these findings for the PGA values exceeding 600 mm/s 2 .The differences between the theoretical values of the GMPE bootstrap model and the GMPE linear regression model from Table 3 reach 136 mm/s 2 .Therefore, the bootstrap analysis of recorded peak ground acceleration values of high-energy mining tremors can provide important information regarding the level of seismic hazard on the surface infrastructure by estimating the level of the mining seismic intensity scale, Figure 9.By estimating bootstrap PGA values caused by high-energy mining tremors, it is possible to assess the seismic hazard on the surface infrastructure related to the level of the mining seismic intensity scale.For example, if the probability of the level of the mining seismic intensity scale is high, then the surface infrastructure may be at a higher risk of damage or failure due to the ground motions caused by the tremors.Thus, the proposed tool may be directly applicable for preventing damage to buildings and protecting local populations by identifying areas in coal mines that are prone to high-energy seismic activity and strong ground motions.Based on the 1000 resamplings with replacement replications for 132 seismic records exceeding 150 mm/s 2 , we have estimated the mean PGA values.The results of our analysis are presented in Figure 10a, which displays the estimated mean PGA values, and Figure 10b, which shows the upper limits of the 95% confidence intervals.In addition to estimating the mean PGA values, our analysis also involved performing a comparison test.This test involved plotting the mean and upper 95% confidence intervals for a linear regression model from Table 3, as shown in Figure 10.This allowed for a comparison between the estimated mean PGA values and the predictions from the regression model, which was previously fitted to the data.One can clearly observe that both the mean PGA values and the upper limits of the 95% confidence intervals of our bootstrapping method yield higher estimated values compared to the ordinary least square linear model (OLS) in the right part of Figure 10a,b and correspondingly smaller values for the left part of Figure 10a,b.This means we have obtained larger predicted values for samples 100-132, i.e., samples Based on the 1000 resamplings with replacement replications for 132 seismic records exceeding 150 mm/s 2 , we have estimated the mean PGA values.The results of our analysis are presented in Figure 10a, which displays the estimated mean PGA values, and Figure 10b, which shows the upper limits of the 95% confidence intervals.In addition to estimating the mean PGA values, our analysis also involved performing a comparison test.This test involved plotting the mean and upper 95% confidence intervals for a linear regression model from Table 3, as shown in Figure 10.This allowed for a comparison between the estimated mean PGA values and the predictions from the regression model, which was previously fitted to the data.One can clearly observe that both the mean PGA values and the upper limits of the 95% confidence intervals of our bootstrapping method yield higher estimated values compared to the ordinary least square linear model (OLS) in the right part of Figure 10a,b and correspondingly smaller values for the left part of Figure 10a,b.This means we have obtained larger predicted values for samples 100-132, i.e., samples with the highest recorded PGA values, and smaller predicted values for samples 1-50, i.e., samples with the lowest recorded PGA.Overall, our analysis provides more valuable insights into the characteristics of the seismic records under consideration and helps to inform decisions related to seismic hazard assessment and risk management. prediction model can provide a reliable and accurate estimate of the distribution of PGA values. The proposed bootstrap tool for determining peak ground acceleration estimators and identifying areas in coal mines that are prone to high-energy seismic activity has several significant implications.First, it can improve safety in coal mines by identifying areas in coal mines that are prone to high seismic ground motion vibrations, and second, by providing more accurate estimations of peak ground acceleration values, the tool can help companies assess the risk of seismic events more effectively and implement appropriate risk management strategies.Table 6 shows the upper limits of 95% confidence for both considered models for recordings exceeding the value of vibration acceleration equal to 0.6 m/s 2 .It is clearly seen that the bootstrap GMPE model reflects the observed PGA values much better and therefore provides more accurate estimators compared to the GMPE model from Table 3.This finding has particular importance for the largest PGA values related directly to high seismic hazards and the highest impact on the surface infrastructure.The accuracy of the analyzed bootstrap model depends on the quality and representativeness of the observed seismic data.When these factors are properly accounted for, our bootstrap ground motion prediction model can provide a reliable and accurate estimate of the distribution of PGA values. The proposed bootstrap tool for determining peak ground acceleration estimators and identifying areas in coal mines that are prone to high-energy seismic activity has several significant implications.First, it can improve safety in coal mines by identifying areas in coal mines that are prone to high seismic ground motion vibrations, and second, by providing more accurate estimations of peak ground acceleration values, the tool can help companies assess the risk of seismic events more effectively and implement appropriate risk management strategies.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
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[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
803e19b4-06d1-4f59-9ed3-befbbc8c8154
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-03T08:08:28.414000 |
bae1ea1e-dd5f-4d2f-a5c5-40d3892a0abb
|
[10.17485/ijst/2016/v9i35/101843](https://doi.org/10.17485/ijst/2016/v9i35/101843)
|
abstract
|
This paper analyses the essential need for EVs in Indian transport, need for advanced charging infrastructure and technoeconomic comparative analysis of EVs and ICE engine vehicle. India is depending on oil imports largely for the energy needs. The share of oil imported by India was 57% at 1957, and it’ll be 97% for 2020. The escalating price of oil poses a severe problem in Indian energy segment in future. An emission from the transport sector is the key source of air pollution next to power sector in India. 13/ 20 cities in the world with highest air pollution are positioned in India. Transport and power sector have a significant effect in worsening air quality. As for these reasons the exploration of a different kind of transportation is required. Electric Vehicles (EV) are proving to be an absolutely new way to store and consume mass amounts of energy from the power grid. Battery Electric Vehicles (EV) and Plug-in Hybrid-Electric Vehicle (PHEV) offers beneficial rewards compared to the conventional ICE vehicle. Power generation from renewable sources, transmission, distribution, and allocation of energy and energy mix are developed with improved efficiency and consistency. A prearranged analysis is done for the business-related scopes of electric vehicles Indian energy sector. Data aggregator provides supplementary grid services as well as controls the electric vehicles charging.
|
<li> <b>Battery Electric Vehicles (EV):</b> Mobile electric batteries (322000)<li> <b>Plug-in Hybrid-Electric Vehicle (PHEV):</b> Mobile electric batteries (322000)
|
[
[
{
"end": 919,
"label": "energyStorage",
"start": 889
},
{
"end": 962,
"label": "energyStorage",
"start": 924
}
],
[
{
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"label": "energyStorage",
"start": 889
},
{
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"label": "energyStorage",
"start": 924
},
{
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"label": "energyType",
"start": 203
},
{
"end": 261,
"label": "energyType",
"start": 258
},
{
"end": 351,
"label": "energyType",
"start": 348
},
{
"end": 778,
"label": "energyStorage",
"start": 761
},
{
"end": 783,
"label": "energyStorage",
"start": 780
},
{
"end": 156,
"label": "energyStorage",
"start": 153
},
{
"end": 46,
"label": "energyStorage",
"start": 43
}
]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Partially correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
{
"end": 919,
"label": "energyStorage",
"start": 889
},
{
"end": 962,
"label": "energyStorage",
"start": 924
}
] | null | null |
ecaf3028-5ac3-4436-81e4-1eb569167705
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:55.253000 |
bf0dec81-2fa7-4772-ab67-9dd878757234
|
[10.17485/ijst/2016/v9i35/101843](https://doi.org/10.17485/ijst/2016/v9i35/101843)
|
XVIII. Geopolitical neutrality
|
ISee, in all its publications, maintains its geopolitical neutrality; any trans boundary rights of sovereign States and their representations and institutional affiliations are solely the representative of the authors only.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
9a1f35b8-600d-4145-b77b-35fa33ac5db0
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-20T09:43:51.896000 |
5dfa815a-56b0-4b51-9f82-693f3dc1b388
|
[10.3390/s23177584](https://doi.org/10.3390/s23177584)
|
abstract
|
Precise identification and spatial analysis of land salinity in China’s Yellow River Delta are essential for the rational utilization and sustainable development of land resources. However, the accurate retrieval model construction for monitoring land salinity remains challenging. This study constructed a land salinity retrieval framework using a harmonized UAV and Landsat-9 multi-spectral dataset. The Kenli district of the Yellow River Delta was selected as the case study area, and a land salinity monitoring index (LSMI) was proposed based on field survey data and UAV multi-spectral image and applied to the reflectance-corrected Landsat-9 OLI image. The land salinity distribution patterns were then mapped and spatially analyzed using Moran’s I and Getis-Ord GI* analysis. The results demonstrated the following: (1) The LSMI-based method can accurately retrieve land salinity content with a validation determination coefficient (R2), root mean square error (RMSE), and residual predictive deviation (RPD) of 0.75, 1.89, and 2.11, respectively. (2) Land salinization affected 93.12% of the cultivated land in the study area, and the severely saline soil grade (with a salinity content of 6–8 g/kg) covered 38.41% of the total cultivated land area and was widely distributed throughout the study area. (3) Saline land exhibited a positive spatial autocorrelation with a value of 0.311 at the p = 0.000 level; high–high cluster types occurred mainly in the Kendong and Huanghekou towns (80%), while low–low cluster types were mainly located in the Dongji, Haojia, Kenli, and Shengtuo towns (88.46%). The spatial characteristics of various salinity grades exhibit significant variations, and conducting separate spatial analyses is recommended for future studies.
|
None
|
[
[],
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Incorrect"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Incorrect"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
7b541a16-2277-4c62-be84-0f85aa244566
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:55.361000 |
69795610-7cfe-4c82-afd9-4fe259e677c8
|
[10.3389/fpls.2013.00538](https://doi.org/10.3389/fpls.2013.00538)
|
abstract
|
Fine roots (FR) play a major role in the water and nutrient uptake of plants and contribute significantly to the carbon and nutrient cycles of ecosystems through their annual production and turnover. FR growth dynamics were studied to understand the endogenous and exogenous factors driving these processes in a 14-year-old plantation of rubber trees located in eastern Thailand. FR dynamics were observed using field rhizotrons from October 2007 to October 2009. This period covered two complete dry seasons (November to March) and two complete rainy seasons (April to October), allowing us to study the effect of rainfall seasonality on FR dynamics. Rainfall and its distribution during the two successive years showed strong differences with 1500 and 950 mm in 2008 and 2009, respectively. FR production (FRP) completely stopped during the dry seasons and resumed quickly after the first rains. During the rainy seasons, FRP and the daily root elongation rate (RER) were highly variable and exhibited strong annual variations with a total FRP of 139.8 and 40.4 mm(-) (2) and an average RER of 0.16 and 0.12 cm day(-) (1) in 2008 and 2009, respectively. The significant positive correlations found between FRP, RER, the appearance of new roots, and rainfall at monthly intervals revealed the impact of rainfall seasonality on FR dynamics. However, the rainfall patterns failed to explain the weekly variations of FR dynamics observed particularly during the rainy seasons. At this time step, FRP, RER, and the appearance of new FR were negatively correlated to the average soil matric potential measured at a depth of between 30 and 60 cm. In addition, our study revealed a significant negative correlation between FR dynamics and the monthly production of dry rubber. Consequently, latex harvesting might disturb carbon dynamics in the whole tree, far beyond the trunk where the tapping was performed. These results exhibit the impact of climatic conditions and tapping system in the carbon budget of rubber plantations.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
e8cadb1d-2221-4b9f-a260-035e684c365b
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-08T14:27:48.168000 |
9f44af86-1e74-4ef0-97ff-39ecceea8c64
|
[10.3389/fpls.2013.00538](https://doi.org/10.3389/fpls.2013.00538)
|
SITE DESCRIPTION
|
The experimental site was located at the Chachoengsao Rubber Research Center, Chachoengsao province (13 • 41 N, 101 • 04 E, and 69 m elevation), eastern Thailand.The observation plot was a monoclonal stand of rubber trees (Hevea brasiliensis Müll.Arg.) planted with the clone RRIM 600 in 1994 after cassava cultivation, with a tree spacing of 7 m × 2.5 m.The clone RRIM 600 is the most extensively planted in Thailand (78% of the planted area).Tapping for latex production began when the trees were 9 years old in 2003.Since then, the trees have been tapped each year during the 9 months from late April/early May to the end of January.During this period, tapping was performed every two or three days with a half-spiral downward cut [(1/2) S d/2, (1/2) S d/3].The average diameter of the trees at 1.70 m from the ground was 20.04 cm (3.95 cm standard deviation) at the beginning of the study in November 2007. The soils in the plot belong to the Kabin Buri series with 50% sand, 15% silt, and 35% clay.The soil depth is limited at 1-1.5 m by a compact layer of ferralitic concretions that strongly limits root growth.The mean annual air temperature and cumulative rainfall were 28.1 • C and 1328 mm, respectively, with a strict dry season between November and April (sourced from the Thai Meteorological Department).
|
None
|
[
[],
[]
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
cb6c190a-10ed-4464-8937-a162f2be33b8
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-08T14:04:29.784000 |
dda1ce26-1950-445c-8d4e-65999ad54186
|
[10.2478/pomr-2019-0050](https://doi.org/10.2478/pomr-2019-0050)
|
abstract
|
Abstract The Turkish Merchant Shipping Industry has recently witnessed an increasing awareness of the importance to minimize environmental pollution and fuel oil consumption. Together with certain non-governmental organizations and media concerns about environmental protection, the International Maritime Organization (IMO) has been strict on controlling undesirable effects on the environment and, consequently, forcing shipping companies to minimize their emissions. Besides, today’s highly advanced technology companies over the world have developed various innovative systems that can be utilized to minimize carbon emission, thus giving assurance to relevant investors that their investments are most likely to turn out well with a considerable financial gain in the short or long term. Despite all such favorable developments, in a general look, shipping companies seem reluctant in making use of technologies providing efficiency in energy consumption. This reluctance has eventually brought about the term “Energy Efficiency Gap”. This research conducts a questionnaire, created by Acciaro et al. [1], among the shipping companies in Turkey. 20 respondent companies, who represent 26 percent of the Turkish owned merchant marine fleet of over 1000 gross tonnage in terms of deadweight cargo capacity, participated in the research. The Pearson correlation analysis was used, and interpretations were made according to the obtained statistical values. The aim of the research was to identify reasons and points restraining the use of new technologies regarding energy efficiency, as well as to develop proposals for the innovators in this field about how to overcome this handicap concerning technical and managerial aspects of gaining energy efficiency.
|
None
|
[
[
{
"end": 161,
"label": "energyType",
"start": 153
}
],
[]
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Incorrect",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Incorrect",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
621f995d-1e71-4ea2-9c41-a5798934ea1b
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-20T09:30:42.589000 |
4381553d-ae77-472a-ba82-ef0be901a258
|
[10.2478/pomr-2019-0050](https://doi.org/10.2478/pomr-2019-0050)
|
CONCLUSION
|
The paper evaluates barriers to the implementation of new technologies which aim at reducing exhaust emissions and improving energy efficiency in the Turkish maritime transportation industry.This evaluation bases on the questionnaire created by Acciaro et al. [1], and its results are discussed. Reliability is deduced as the most important barrier against the implementation of the emission reducing and energy efficiency improving technologies to the Turkish merchant marine fleet.The most significant relationship among the barriers is found between the operating cost and the installation cost, with the R value of 0.937. As expected, the costs are generally the main topic, but also the uncertainties about operational measures and payback periods make it difficult to convince the shipping companies to utilize innovative products of the emission reduction technology.The shipping companies regard the operational measures as more suitable to the company, as these measures require lower initial and operational costs.The know-hows about these technologies are considered as insufficient and unreliable, which raises concern about the increased risk to ship's safety.Therefore, reliable information must be provided, and the risk status concerning the safety of operations must be eliminated to increase the application density of the technologies by the shipping companies. The study of Acciaro et al. [1] aimed to find the barriers in the Norwegian shipping industry.As a result of the study, operational measures appeared to have lower barriers than hardware measures.The same pattern is observed among the Turkish shipping companies.Renewable energy and LNG technologies have the highest barrier scores for both countries.Maturity levels of the technologies and cost considerations have possessed a high barrier level.An active role of Norwegian policymakers through financial incentives has also been suggested.In comparison, the Turkish maritime transportation is basically in the need to revise the existing regulations to be effective, along with incentives, in overcoming these barriers.The reliability and safety issues are among the most important issues for both countries. In this respect, it is suggested that the university-industry cooperation should be well-established in the emission reduction and energy efficiency improvement technology fields to accelerate the innovative products with reliable source of information.In that way, the payback periods and the initial costs may be decreased as a solution to the main concern of end-users, and the energy efficiency gap would be narrowed in the Turkish maritime transportation industry.
|
None
|
[
[],
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
87acbc50-2aec-4a71-b964-8e50f852219d
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:55.507000 |
7c9b4078-e78b-413e-971e-9d4b37062b20
|
[10.3389/fenrg.2022.841497](https://doi.org/10.3389/fenrg.2022.841497)
|
abstract
|
Global warming is mainly influenced by factors such as energy consumption, human development, and economic activities, but there is no consensus among researchers and there is relatively little research literature on less developed countries. Therefore, this study attempts to explore the impact of renewable energy consumption, human development and economic growth on climate change from a macroeconomic perspective for 105 countries worldwide over the period 1990–2019 by constructing a panel vector autoregressive (PVAR) model and using generalized method of moments (GMM) and panel impulse response analysis. The analysis includes four panels of high-income, upper-middle-income, lower-middle-income, and low-income countries. The results of the study find that economic growth, FDI, trade openness, industrialization, renewable energy consumption and HDI have different impacts on climate change (CO2 emissions) in different regions during the sample period. Specifically, in the four panels, economic growth, industrialization, FDI, and trade openness all play a varied role in aggravating environmental pollution (CO2 emissions). In high-income and upper-middle-income countries, industrialization has a positive effect on CO2 emissions, while FDI has a negative impact, which supports the pollution halo hypothesis. However, both have a positive impact on CO2 emissions in lower-middle-income and low-income countries. The results also found that except for upper-middle-income countries, trade openness and renewable energy consumption help reduce CO2 emissions, while renewable energy consumption has little effect on suppressing CO2 emissions in low-income countries. In addition, HDI has promoted CO2 emissions in upper-middle-income and lower-middle-income countries, but has curbed CO2 emissions in high-income countries. Therefore, under the premise of not affecting economic growth and HDI, those empirical results will not only help decision-makers formulate appropriate renewable energy policies, but also are of great significance to the realization of a healthy and sustainable global environment.
|
<li> <b>renewable energy consumption:</b> Renewable energy (200000)
|
[
[
{
"end": 327,
"label": "energyType",
"start": 299
},
{
"end": 852,
"label": "energyType",
"start": 824
},
{
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"label": "energyType",
"start": 1517
},
{
"end": 1607,
"label": "energyType",
"start": 1579
}
]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
{
"end": 327,
"label": "energyType",
"start": 299
},
{
"end": 852,
"label": "energyType",
"start": 824
},
{
"end": 1545,
"label": "energyType",
"start": 1517
},
{
"end": 1607,
"label": "energyType",
"start": 1579
}
] | null | null |
7dde31db-2d86-478f-a959-5b65c5ad921c
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:55.594000 |
ee9f6b7b-0553-447d-88d3-5ec2c3804d6e
|
[10.3389/fenrg.2022.841497](https://doi.org/10.3389/fenrg.2022.841497)
|
PVAR Model Specification
|
Panel autoregression model (panel VAR) was first proposed by Holtz-Eakin et al. (1988) (Holtz-Eakin et al., 1988), and then Love et al. (2006) (Love and Zicchino, 2006) further improved it.Compared with the ordinary VAR model, this model is an organic synthesis of the panel data model and the vector autoregressive model, and has the dual advantages of time series and panel data.It is not only suitable for analyzing the relationship between complex variables, but also suitable for analyzing the influence of one variable on other variables (Shen, 2020).In addition, the model treats all variables as endogenous variables, which circumvents the relationship assumptions of the fixed structure model, and to a certain extent reduces some restrictive conditions of the vector autoregressive model, which is used to examine the interaction between the variables and their leads and lags (Aydin, 2019).Given that there are individual differences in the impact of different types of variable indicators on climate change, and individual variable data will also change over time.Therefore, this study adds individual fixed effects and time fixed effects to the model, and the general manifestation of PVAR model is as follows: where i refers to each sample; t refers to the year; y i,t is a vector of dependent variable; γ i is the individual effect of the sample; β j is the parameter matrix; p is the lag order; x i is individual effect; φ i is the time effect; ε i,t is random interference terms that obey the normal distribution. The matrix form of the PVAR model reported in Eq. 1 can also be rewritten in six equations, Eqs 2-8, as follows: where CE represents the growth rate of carbon emissions per capita, HDI refers to Human Development Index growth rate, RE denotes renewable energy consumption, GDP represents economic growth.Macroeconomic variables comprise the foreign direct investment, trade openness and industrialization, denoted as FDI, TRO and IND, respectively.In addition, after the vector autoregressive model (VAR) is widely used in the time series model, and through the continuous improvement and development of scholars, the GMM estimation method of the parallel panel model is obtained in the PVAR method.The GMM removes deterministic effects by performing some transformation other than differencing, which is called "forward mean differencing or orthogonal deviation" (Helmert process).To eliminate the fixed effects, all variables in the equation are transformed in deviations from forward means in this procedure (Amer, 2020).Therefore, before the GMM estimation, the forward mean difference method will be used to eliminate the time effects and individual fixed effects in the panel data to ensure that the lagged variables and the transformed variables are orthogonal to form effective instrumental variables, and use AIC, BIC, and HQIC information criterion to calculate, screen the lag order of the model, and select the optimal lag order.The general equation is as follows: Akaike information criterion: Bayesian information criterion: Hannan-Quinn information criterion: where N p N(T -P) is the number of valid samples in the model, and k is the number of parameters in the model.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
c929070f-c10b-492f-b142-5bfec0cdc983
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:55.681000 |
efc22c32-7291-4126-a82f-5c863c9e9e30
|
[10.3390/ijerph19116644](https://doi.org/10.3390/ijerph19116644)
|
abstract
|
Abstract This paper introduced PGTWR model as the base model of the study and adopted thirteen prefecture-level cities as individuals of cross section and conducted spatial and temporal heterogeneity study of the converted influencing factors of carbon emissions in Beijing-Tianjin-Hebei region with the time period from the year 2013 to 2018 as panel data. From the perspective of time and space as a whole, the regression coefficient of each influencing factor of carbon emission in Hebei Province has obvious heterogeneity. Relatively speaking, the heterogeneity of influencing factors of carbon emission in Beijing-Tianjin-Hebei region is mainly reflected in time dimension. In the period of study, the impact of industrial structure, the level of urbanization, energy intensity and the level of economic development on carbon emission was on a decline curve while the impact of population size and the level of opening up on carbon emission was on the rise, which indicates that the former four factors that reflect the level of economy and technology are not the focus of consideration when making the policy of carbon emission reduction and that more attention should be paid to the latter two factors for the time to come. From the perspective of space, the differences in the impact of industrial structure and energy intensity on carbon emission vary significantly. As a result, these differences should be attached importance to when making the policy of carbon emission reduction.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
301fd034-48a4-4517-afe0-03e75fb01916
|
completed
| 2025-04-28T10:06:43.015000 | 2025-05-08T14:32:05.634000 |
db22fc38-0809-4107-a86e-745449273cd3
|
[10.3390/ijerph19116644](https://doi.org/10.3390/ijerph19116644)
|
Temporal Heterogeneity Analysis of the Impact of Urbanization Level on Carbon Emission
|
The direct and indirect demand of city life for energy is considered to be a major contributor to the adverse environmental impact of urbanization [48].During the period of study, the influence of urbanization on carbon emissions in the Beijing-Tianjin-Hebei region decreased annually, mainly because the rise of urbanization rate and the population agglomeration in cities have promoted scientific and technological progress, facilitated the transition and upgrades of the industrial structure, and improved industrial efficiency through sharing, matching, and learning effect.At the same time, it has contributed to more intensive use of infrastructure, facilitated the agglomeration of economic activities and production behavior, and improved the efficiency of resources and energy use, thus effectively reducing the carbon emissions.In terms of policy, in recent years, China has vigorously implemented a new urbanization development strategy of economy and intensiveness, ecological and suitable living, and harmonious development, and advocated the idea of low-carbon living for urban residents as well.Therefore, the impact of the level of urbanization on carbon emission has gradually weakened.
|
None
|
[
[],
[]
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
9ad2bfa0-f4c0-4542-9be5-2dc855a34b17
|
completed
| 2025-04-28T10:06:43.015000 | 2025-06-19T09:39:55.794000 |
65ab8db6-4400-4086-af41-d9307207a22b
|
[10.3390/rs61110306](https://doi.org/10.3390/rs61110306)
|
abstract
|
The increasing competition for water resources requires a better understanding of flows, fluxes, stocks, and the services and benefits related to water consumption. This paper explains how public domain Earth Observation data based on Moderate Resolution Imaging Spectroradiometer (MODIS), Second Generation Meteosat (MSG), Tropical Rainfall Measurement Mission (TRMM) and various altimeter measurements can be used to estimate net water production (rainfall (P) > evapotranspiration (ET)) and net water consumption (ET > P) of Nile Basin agro-ecosystems. Rainfall data from TRMM and the Famine Early Warning System Network (FEWS-NET) RainFall Estimates (RFE) products were used in conjunction with actual evapotranspiration from the Operational Simplified Surface Energy Balance (SSEBop) and ETLook models. Water flows laterally between net water production and net water consumption areas as a result of runoff and withdrawals. This lateral flow between the 15 sub-basins of the Nile was estimated, and partitioned into stream flow and non-stream flow using the discharge data. A series of essential water metrics necessary for successful integrated water management are explained and computed. Net water withdrawal estimates (natural and humanly instigated) were assumed to be the difference between net rainfall (Pnet) and actual evapotranspiration (ET) and some first estimates of withdrawals—without flow meters—are provided. Groundwater-dependent ecosystems withdraw large volumes of groundwater, which exceed water withdrawals for the irrigation sector. There is a strong need for the development of more open-access Earth Observation databases, especially for information related to actual ET. The fluxes, flows and storage changes presented form the basis for a global framework to describe monthly and annual water accounts in ungauged river basins.
|
None
|
[
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted"
] |
[] | null | null |
9d6f365f-bc2e-4ecf-b2eb-ab5f4f90f2f7
|
completed
| 2025-04-28T10:06:43.016000 | 2025-06-03T08:21:27.175000 |
f4d2c549-033e-4ee3-99d1-febaa37ada8f
|
[10.3390/rs61110306](https://doi.org/10.3390/rs61110306)
|
Rainfall
|
The difference in annual rainfall from TRMM and RFE is presented in Figure 2. The bar chart demonstrates that TRMM gives for most years a slightly higher rainfall over the Nile basin than RFE.The average value for the period 2006-2010 is 647 mm for TRMM and 600 mm for RFE.This is a difference of 47 mm or 8%.While this difference seems reasonable, the consequence of 8% difference at an average rainfall volume of 2013 km 3 is a potential error of 161 km 3 /yr, which is two times the historic Nile flow at Dongola.This example demonstrates the need for a high accuracy in rainfall products.Because the official WMO rain gauge network is limited in number, and both TRMM and RFE have advantages and disadvantages, it is difficult to favor one of the rainfall products without in-depth research.For pragmatic reasons, the pixel values of the two rainfall products were linearly averaged.Ensemble rainfall products based on Earth observation data will likely lead the way forward to obtain reliable rainfall data layers.The new Climate Hazard Group IR Precipitation Station (CHIRPS) rainfall product is an example of an ensemble product based on various interpolation schemes to create spatially continuous grids from raw point data based on climatology, satellite measurements and ground precipitation observations from a variety of sources (Funk et al., [49]). The average rainfall of the two products for the period 2005-2010 is 624 mm/yr (2013 km 3 /yr for a basin area of 3,229,038 km 2 ).The FAO-Nile report (Hilhorst et al., [4]) gives an average rainfall volume of 2008 km 3 /yr for a basin area of 3,170,418 km 2 , which computes to 633 mm/yr, and which is close to the value used here (deviation is +1.4%).The FAO irrigation potential study mentions a rainfall of 615 mm/yr (deviation is -1.4%) for an area of 3,112,369 km 2 or 1914 km 3 /yr (FAO, 1997).Kirby et al. estimated the Nile basin rainfall volume to be 2,043 km 3 /yr (627 mm/yr; deviation is 0.5%) using data from the Climate Research Unit at the University of East Anglia (CRU TS 2.10) covering the period 1901-2002.Karimi et al. [50] summarized the water balance of the Nile, and estimated the total rainfall for the wet year 2007 as 2045 km 3 /yr, which is plausible for an above-average rainfall volume.Hence, the estimates appear to correspond closely.The consistency between the TRMM and RFE rainfall products for all 15 sub-basins is shown in Figure 3.The scatterplot demonstrates that the overall agreement is acceptable, but that large differences in local rainfall occur (RMSE is 153 mm/yr).The largest differences in absolute rainfall amounts occur over the equatorial Nile zone.The rainfall rates over Lake Victoria and the Victoria Nile sub-basins are frequently more than 250 mm/yr different: the difference of 250 mm/yr is unlikely.Rainfall estimates of the Blue Nile sub-basin also seem to have unreasonable differences.It is therefore concluded that more research is needed to validate local rainfall products from Earth observation data.The success of calibration will increase if the data are exposed to a downscaling procedure first.The rainfall regimes differ significantly across the different sub-basins, and rainfall evaluation should actually focus on the sub-basins only (see Table 1).The humid tropical Kagera, Lake Victoria, Semiliki and Lake Albert and Victoria Nile basins all show substantial amounts of rainfall throughout the year, with their peaks occurring during March and April (P > 100 mm/month).The central part of the Nile basin receives rainfall during June, July and August and is relatively dry during the period November to March.The area downstream of the Blue Nile sub-basin receives substantially lower rainfall amounts.Their access to water resources depends entirely on the rainfall surplus (P-ET) from the upstream basins.
|
None
|
[
[],
[]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
c404f96c-7a8d-4494-a135-0b201a414a8e
|
completed
| 2025-04-28T10:06:43.016000 | 2025-05-08T15:03:17.325000 |
7c681dd7-ff44-4c1c-a190-dc983990add4
|
[10.1007/s10666-018-9627-1](https://doi.org/10.1007/s10666-018-9627-1)
|
abstract
|
One of the main goals in pursuing sustainable development is to provide universal access to modern energy services, notably through the use of off-grid renewable energy technologies. To date, integrated assessment models (IAMs) poorly address energy access targets. In the context of research dedicated to energy scenarios and climate change mitigation in Africa, we attempt to advance the representation of energy access in one such IAM by using GIS data. In a case study for Ethiopia with the TIAM-ECN model, we demonstrate that by enriching an IAM with information derived from GIS databases, insights are obtained that better capture the dynamics of energy access developments, in comparison to conventional IAM analysis of energy technology deployment pathways. When duly accounting for the geographical spread in demography and technology costs in a developing country, we find that many people may gain access to electricity in remote areas thanks to the availability of affordable off-grid power production options that render expensive grid extensions unnecessary. This effect is not explicitly accounted for in most traditional IAMs. By the middle of the century, off-grid technologies could provide affordable electricity to 70% of the Ethiopian population, based almost entirely on renewable sources such as wind, solar and hydropower.
|
<li> <b>renewable energy:</b> Renewable energy (200000)<li> <b>wind:</b> Wind energy (230000)<li> <b>solar:</b> Solar energy (240000)<li> <b>hydropower:</b> Renewable hydropower (210000)
|
[
[
{
"end": 168,
"label": "energyType",
"start": 152
},
{
"end": 1324,
"label": "energyType",
"start": 1320
},
{
"end": 1331,
"label": "energyType",
"start": 1326
},
{
"end": 1346,
"label": "energyType",
"start": 1336
}
],
[
{
"end": 168,
"label": "energyType",
"start": 152
},
{
"end": 1324,
"label": "energyType",
"start": 1320
},
{
"end": 1331,
"label": "energyType",
"start": 1326
},
{
"end": 1346,
"label": "energyType",
"start": 1336
}
]
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
{
"end": 168,
"label": "energyType",
"start": 152
},
{
"end": 1324,
"label": "energyType",
"start": 1320
},
{
"end": 1331,
"label": "energyType",
"start": 1326
},
{
"end": 1346,
"label": "energyType",
"start": 1336
}
] | null | null |
8c7078a0-e2f7-44c7-9778-3c9e3571beb4
|
completed
| 2025-04-28T10:06:43.016000 | 2025-05-20T09:40:35.742000 |
cbdcad20-5dd7-42e8-bb6d-d03bc272c4f5
|
[10.1007/s10666-018-9627-1](https://doi.org/10.1007/s10666-018-9627-1)
|
TIAM-ECN
|
TIAM-ECN is a well-established version of the global TIAM model developed under the Energy Technology Systems Analysis Program of the International Energy Agency (IEA-ETSAP).A technology-rich, bottom-up integrated assessment model with global geographical scope, TIAM, is built on the TIMES model generator, as described in detail in Loulou and Labriet [15] and Loulou [14].TIAM is a linear optimization model that minimises energy system costs in each time-period with perfect foresight.The objective function includes capital, operation and maintenance, as well as fuel and trading costs. Building on a database of hundreds of energy-related processes and commodities, TIAM-ECN the entire global system from resource extraction to end-use over a period that spans the entire twenty-first century.For a general description of the reference energy system of TIAM-ECN, see Syri et al. [36].TIAM-ECN has been used successfully in several different sectors and domains, such as transportation (see, e.g.Rösler et al. 37), power supply (Keppo and van der Zwaan [38]), burden sharing among countries for global climate change control [13] and global and regional technology diffusion (see, e.g.van der Zwaan et al. [39]).In the current set-up of TIAM-ECN, the world is disaggregated in 36 distinct regions ( [28,30]; Dalla Longa et al. [35]).Ethiopia is modelled as a separate 'region', enabling the country-level analysis described here. For the present paper, we enriched the input database of TIAM-ECN with a more detailed description of a set of offgrid electricity production technologies, namely, wind, solar PV, hydropower and diesel generators.Although off-grid wind was not assessed in the GIS analysis, we included it in the TIAM-ECN input database.The rationale behind this choice is that in this study, we use the results of the GIS analysis to estimate overall demand for residential electricity, split into two components: off-grid and grid.All off-grid, respectively grid-connected, processes in TIAM-ECN are eligible (within appropriate constraints) to fulfil these demand components, and we let the model deploy the most costefficient options.
|
None
|
[
[],
[
{
"end": 1602,
"label": "energyType",
"start": 1598
},
{
"end": 1612,
"label": "energyType",
"start": 1604
},
{
"end": 1624,
"label": "energyType",
"start": 1614
},
{
"end": 1646,
"label": "energyType",
"start": 1629
},
{
"end": 1669,
"label": "energyType",
"start": 1656
}
]
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Incorrect"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Incorrect"
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[
null,
null
] |
[
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a",
"126aa856-31dd-41e9-8688-003b63bdf236"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
e9593c56-ec08-43c2-927e-19f55719c033
|
completed
| 2025-04-28T10:06:43.016000 | 2025-05-08T14:59:20.312000 |
ca7d02a6-e7ed-4a87-af80-b6cec4b564a0
|
[10.21285/1814-3520-2020-6-1209-1222](https://doi.org/10.21285/1814-3520-2020-6-1209-1222)
|
abstract
|
The purpose of the study is to identify industrial facilities that are critically important for the fuel and energy complex in the conditions of joint functioning of industries, taking into account the system effect and existing mechanisms of structural redundancy. To identify critically important facilities of the fuel and energy complex based on its operation models derived as a result of stage-by-stage sectoral and general energy studies, a methodology is proposed. It is based on the identification methods of critically important industry facilities on the principles of assessing vulnerability of critically important infrastructure elements. The presented methodology is characterized by the complex and flexible assessment of the critical importance of sectoral facilities, which is carried out on the basis of scenario options of fuel and ener gyomplex operation. The methodology is supplemented with a formalized representation of a typical general energy optimization model, which unifies the relationship between the territorial-production structure of the sectoral systems modeled in it, its information base with the corresponding technical and economic indicators, and the research problems solved with its help. The assessment of the critical importance of gas industry facilities is given for 80 constituent entities of the Russian Federation. The approbation results of the proposed methodology are given on the example of the identification of the critically important gas industry facilities using a model of fuel and energy complex operation with a detailed scheme of the Unified Gas Supply System of Russia. The approbation has revealed the differences in the priority of critically important facilities of the gas industry and the fuel and energy complex. It has also shown a significant influence of the system effect of the mutually coordinated functioning of industries on the fuel and energy supply of consumers. The results obtained confirm the efficiency of the methodology, prove the possibility of its use for assessing the critical importance of power industry branch facilities. The research scheme implemented in the methodology allows to obtain an adequate state of matters with the fuel and energy supply to consumers under cut-out critically important sectoral facilities.
|
None
|
[
[],
[]
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Partially correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
"Correct",
"Correct"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[
null,
"fuel gas missing"
] |
[
"126aa856-31dd-41e9-8688-003b63bdf236",
"0c55e31a-e8f5-4179-bc89-1418dcdb3d6a"
] |
[
"submitted",
"submitted"
] |
[] | null | null |
Dataset Card for scilake-energytype
This dataset has been created with Argilla. As shown in the sections below, this dataset can be loaded into your Argilla server as explained in Load with Argilla, or used directly with the datasets
library in Load with datasets
.
Using this dataset with Argilla
To load with Argilla, you'll just need to install Argilla as pip install argilla --upgrade
and then use the following code:
import argilla as rg
ds = rg.Dataset.from_hub("SIRIS-Lab/scilake-energytype", settings="auto")
This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation.
Using this dataset with datasets
To load the records of this dataset with datasets
, you'll just need to install datasets
as pip install datasets --upgrade
and then use the following code:
from datasets import load_dataset
ds = load_dataset("SIRIS-Lab/scilake-energytype")
This will only load the records of the dataset, but not the Argilla settings.
Dataset Structure
This dataset repo contains:
- Dataset records in a format compatible with HuggingFace
datasets
. These records will be loaded automatically when usingrg.Dataset.from_hub
and can be loaded independently using thedatasets
library viaload_dataset
. - The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.
- A dataset configuration folder conforming to the Argilla dataset format in
.argilla
.
The dataset is created in Argilla with: fields, questions, suggestions, metadata, vectors, and guidelines.
Fields
The fields are the features or text of a dataset's records. For example, the 'text' column of a text classification dataset of the 'prompt' column of an instruction following dataset.
Field Name | Title | Type | Required |
---|---|---|---|
doi | DOI | text | True |
section | Section | text | True |
text | Text | text | True |
links | Linked entities | text | True |
Questions
The questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking.
Question Name | Title | Type | Required | Description | Values/Labels |
---|---|---|---|---|---|
span_label | Select and classify the tokens according to the specified categories. | span | True | N/A | ['energyType', 'energyStorage'] |
assess_ner | Extracted entity validation | label_selection | True | Are the extracted entities correct? | ['Correct', 'Partially correct', 'Incorrect'] |
assess_nel | Linked IRENA entity validation | label_selection | True | Are the linked entities in the IRENA taxonomy correct? | ['Correct', 'Partially correct', 'Incorrect'] |
comments | Comments | text | False | Additional comments | N/A |
Data Splits
The dataset contains a single split, which is train
.
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation guidelines
Energy type validation guidelines
Task Description
Your task is to validate the extraction of energy (storage) type entities and their linking to their closest matching entries in the IRENA taxonomy.
What to Validate
For each record, please verify the following:
- Entity Spans: Are all text spans correctly identified? Are the span boundaries accurate?
- Entity Types: Are entity types correctly assigned?
- Entity Linking: Are the matching entities in the IRENA taxonomy correctly assigned?
Instructions
- Carefully read the texts.
- Review the NER spans and correct them if:
- The boundaries (start/end) are incorrect
- The entity label is wrong
- Verify that the extracted entities are correctly linked to their closest match in the IRENA taxonomy
- Add any comments or feedback you deem relevant
Validation Guidelines
- Entity Annotations: Mark spans as "Correct" only if boundaries and labels are accurate.
- Entity Extraction: Mark as "Correct" if all energy (storage) types mentioned are extracted; "Partially correct" if any are missing or incorrect.
- IRENA Linking: Mark as "Correct" if all links are to the appropriate entries. Use "Partially correct" if any are incorrect.
Annotation process
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Who are the annotators?
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Personal and Sensitive Information
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Considerations for Using the Data
Social Impact of Dataset
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Discussion of Biases
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Other Known Limitations
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Additional Information
Dataset Curators
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Licensing Information
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Citation Information
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Contributions
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