However, cities that line the fault, like Los Angeles and San Francisco, have not experienced a major destructive earthquake — of magnitude 7.5 or more — since their intensive urbanizations in the early twentieth century. With knowledge that large earthquakes occur at about 150-year intervals on the San Andreas, seismologists are certain that the next “big one” is near.
Clearly, understanding what might happen in a particular area is no simple task. In fact, the prediction involves a laundry list of complex inputs that could not be calculated all together without the help of Titan, a 27-petaflop Cray XK7 machine with a hybrid CPU-GPU architecture. Titan is managed by the Oak Ridge Leadership Computing Facility (OLCF), a DOE Office of Science User Facility located at ORNL.
Running on Titan, the team uses SCEC’s CyberShake — a physics-based computational approach that integrates many features of an earthquake event — to calculate a probabilistic seismic hazard map for California. In May, Jordan’s team completed its highest resolution CyberShake map for Southern California using the OLCF’s Titan.
One of the most important variables that affects earthquake damage to buildings is seismic wave frequency, or the rate at which an earthquake wave repeats each second. With greater detail and increases in the simulated frequency — from 0.5 hertz to 1 hertz — the latest CyberShake map is the most useful one to date and serves as an important tool for engineers who use its results to design and build critical infrastructure and buildings.
“They’re the same earthquake with the same magnitude, but the rupture characteristics — where it started and how it propagated, for example — will change the areas at Earth’s surface that are affected by this strong ground motion,” Maechling said.
As the team increased the maximum frequency in historic earthquake simulations, however, they identified a threshold right around 1 hertz, at which their simulations diverged from observations. The team determined it needed to integrate more advanced physics into its code for more realistic results.
Including topography — the roughness of Earth’s surface — the team’s simulations now include additional geometrical and attenuation (gradual dampening of the shaking due to loss of energy) effects — near-fault plasticity, frequency-dependent attenuation, small-scale near-surface heterogeneities, near-surface nonlinearity, and fault roughness.
With the new physics included in SCEC’s earthquake code — the Anelastic Wave Propagation by Olsen, Day, and Cui (AWP-ODC) — Jordan’s team was able to run its first CyberShake hazard curve on Titan for one site at 1 hertz, establishing the computational technique in preparation for a full-fledged CyberShake map.
The team used the US Geologic Survey’s (USGS’s) Uniform California Earthquake Forecast — which identifies all possible earthquake ruptures for a particular site — for generating CyberShake hazard curves for 336 sites across southern California.
Using Cui’s GPU-accelerated code on Titan, the team ran simulations 6.3 times more efficiently than the CPU-only implementation, saving them 2 million core hours for the project. Completion of the project required about 9.6 million core hours on Titan.
Click on image above to view an animation of the wave propagation during a simulated Magnitude 7.8 earthquake rupturing the San Andreas Fault from southwest to northeast. Red/blue colors reflect the intensity of shaking; green indicates areas of permanent ground deformation. The colored vertical “signals” show the evolution of seismograms at three locations.
Note: The above post is reprinted from materials provided by Oak Ridge Leadership Computing Facility.