Using supercomputers to quantify Bay Area earthquake hazard and risk

With unprecedented resolution, Lawrence Livermore and Lawrence Berkeley national laboratory scientists and engineers are simulating precisely how a large-magnitude earthquake along the Hayward Fault would affect different locations and buildings across the San Francisco Bay Area. The researchers reported on their recent simulations in June at the U.S. National Conference on Earthquake Engineering, a meeting held every four years by the Earthquake Engineering Research Institute.

A critical factor affecting earthquake damage to buildings and structures is seismic wave frequency, or the rate at which an earthquake wave repeats each second. Because of this, researchers including LLNL’s computational scientist Anders Petersson and seismologist Artie Rodgers (Atmospheric, Earth, and Energy Division) have been working with Berkeley Lab’s Hans Johansen to advance the existing SW4 code. This code was originally developed by Petersson for simulating three-dimensional seismic wave propagation.

The researchers recently simulated ground motions at a broad range of frequencies using the enhanced SW4 code and 524,288 cores of the Cori supercomputer at LBNL’s National Energy Research Scientific Center. The national lab researchers then used a second computer program to quantify seismic risk for representative building structures on a regional scale.

The fact that buildings respond differently to certain seismic wave frequencies based on their size and location was evidenced by the simulations. These showed an increase in damage potential for a 40-story building—more than for a three-story building—as the earthquake increased in magnitude from 6.5 to 7 at high frequency (5 hertz) due to the significant increase in ground motion at longer periods of vibration. Their simulations also indicated that two buildings with the same number of stories equidistant from the fault line and only approximately three miles apart can have a substantially different damage potential due to the differences in which seismic waves emanating from the fault merge together.

This research is part of DOE’s Exascale Computing Project.