After defining the problem space, establishing simulation algorithms, and selecting the methodology to characterize the system sustainability, QSD can be executed with system simulation as the first step. Multiple types of tools can be leveraged in system simulation to generate the system inventory. On the simpler end of the spectrum, designs from existing literature can be used and system inventories can be scaled from the literature design (e.g., scaled based on key flowrates). In this case, spreadsheets or programming languages (e.g., R, Python ) can be used for inventory scaling, and this process can be automated through spreadsheet built-in functions (e.g., Microsoft Excel Macros 216,217 ) or add-in applications (e.g., Crystal Ball ®218 , SimVoi ®219 ). Though straightforward, this strategy relies on existing designs with limited capacity to accurately reflect the intrinsic correlations between QSD inputs and system sustainability. Additionally, as mass and energy flows within the system would be scaled using generic algorithms (often linear correlations) rather than being solved analytically or numerically to convergence, the results could be inaccurate as values of the QSD inputs diverge from the existing design. Therefore, this strategy is generally only appropriate for very preliminary evaluations or for the evaluation of relatively mature technologies for which well-tested scaling algorithms are available.