From LLNL: “Hayward fault earthquake simulations increase fidelity of ground motions”


Lawrence Livermore National Laboratory

Feb. 8, 2018
Anne M Stark
stark8@llnl.gov (link sends e-mail)
925-422-9799


What will happen during an earthquake?

In the next 30 years, there is a one-in-three chance that the Hayward fault will rupture with a 6.7 magnitude or higher earthquake, according to the United States Geologic Survey (USGS). Such an earthquake will cause widespread damage to structures, transportation and utilities, as well as economic and social disruption in the East Bay.

Lawrence Livermore (LLNL) and Lawrence Berkeley (LBNL) national laboratory scientists have used some of the world’s most powerful supercomputers to model ground shaking for a magnitude (M) 7.0 earthquake on the Hayward fault and show more realistic motions than ever before. The research appears in Geophysical Research Letters.

Past simulations resolved ground motions from low frequencies up to 0.5-1 Hertz (vibrations per second). The new simulations are resolved up to 4-5 Hertz (Hz), representing a four to eight times increase in the resolved frequencies. Motions with these frequencies can be used to evaluate how buildings respond to shaking.

The simulations rely on the LLNL-developed SW4 seismic simulation program and the current best representation of the three-dimensional (3D) earth (geology and surface topography from the USGS) to compute seismic wave ground shaking throughout the San Francisco Bay Area. The results are, on average, consistent with models based on actual recorded earthquake motions from around the world.

“This study shows that powerful supercomputing can be used to calculate earthquake shaking on a large, regional scale with more realism than we’ve ever been able to produce before,” said Artie Rodgers, LLNL seismologist and lead author of the paper.

The Hayward fault is a major strike-slip fault on the eastern side of the Bay Area. This fault is capable of M 7 earthquakes and presents significant ground motion hazard to the heavily populated East Bay, including the cities of Oakland, Berkeley, Hayward and Fremont. The last major rupture occured in 1868 with an M 6.8-7.0 event. Instrumental observations of this earthquake were not available at the time. However, historical reports from the few thousand people who lived in the East Bay at the time indicate major damage to structures.

The recent study reports ground motions simulated for a so-called scenario earthquake, one of many possibilities.

“We’re not expecting to forecast the specifics of shaking from a future M 7 Hayward fault earthquake, but this study demonstrates that fully deterministic 3D simulations with frequencies up to 4 Hz are now possible. We get good agreement with ground motion models derived from actual recordings and we can investigate the impact of source, path and site effects on ground motions,” Rodgers said.

As these simulations become easier with improvements in SW4 and computing power, the team will sample a range of possible ruptures and investigate how motions vary. The team also is working on improvements to SW4 that will enable simulations to 8-10 Hz for even more realistic motions.

For residents of the East Bay, the simulations specifically show stronger ground motions on the eastern side of the fault (Orinda, Moraga) compared to the western side (Berkeley, Oakland). This results from different geologic materials — deep weaker sedimentary rocks that form the East Bay Hills. Evaluation and improvement of the 3D earth model is the subject of current research, for example using the Jan. 4, 2018 M 4.4 Berkeley earthquake that was widely felt around the northern Hayward fault.

Ground motion simulations of large earthquakes are gaining acceptance as computational methods improve, computing resources become more powerful and representations of 3D earth structure and earthquake sources become more realistic.

Rodgers adds: “It’s essential to demonstrate that high-performance computing simulations can generate realistic results and our team will work with engineers to evaluate the computed motions, so they can be used to understand the resulting distribution of risk to infrastructure and ultimately to design safer energy systems, buildlings and other infrastructure.”

Other Livermore authors include seismologist Arben Pitarka, mathematicians Anders Petersson and Bjorn Sjogreen, along with project leader and structural engineer David McCallen of the University of California Office of the President and LBNL.

This work is part of the DOE’s Exascale Computing Project (ECP (link is external)). The ECP is focused on accelerating the delivery of a capable exascale computing ecosystem that delivers 50 times more computational science and data analytic application power than possible with DOE HPC systems such as Titan (ORNL) and Sequoia (LLNL), with the goal to launch a U.S. exascale ecosystem by 2021.

ORNL Cray XK7 Titan Supercomputer

LLNL Sequoia IBM Blue Gene Q petascale supercomputer

The ECP is a collaborative effort of two Department of Energy organizations — the DOE Office of Science and the National Nuclear Security Administration (link is external).

Simulations were performed using a Computing Grand Challenge allocation on the Quartz supercomputer at LLNL and with an Exascale Computing Project allocation on Cori Phase-2 at the National Energy Research Scientific Computing Center (NERSC) at LBNL.

See the full article here .

ShakeAlert: An Earthquake Early Warning System for the West Coast of the United States

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The U. S. Geological Survey (USGS) along with a coalition of State and university partners is developing and testing an earthquake early warning (EEW) system called ShakeAlert for the west coast of the United States. Long term funding must be secured before the system can begin sending general public notifications, however, some limited pilot projects are active and more are being developed. The USGS has set the goal of beginning limited public notifications in 2018.

Watch a video describing how ShakeAlert works in English or Spanish.

The primary project partners include:

United States Geological Survey
California Governor’s Office of Emergency Services (CalOES)
California Geological Survey
California Institute of Technology
University of California Berkeley
University of Washington
University of Oregon
Gordon and Betty Moore Foundation

The Earthquake Threat

Earthquakes pose a national challenge because more than 143 million Americans live in areas of significant seismic risk across 39 states. Most of our Nation’s earthquake risk is concentrated on the West Coast of the United States. The Federal Emergency Management Agency (FEMA) has estimated the average annualized loss from earthquakes, nationwide, to be $5.3 billion, with 77 percent of that figure ($4.1 billion) coming from California, Washington, and Oregon, and 66 percent ($3.5 billion) from California alone. In the next 30 years, California has a 99.7 percent chance of a magnitude 6.7 or larger earthquake and the Pacific Northwest has a 10 percent chance of a magnitude 8 to 9 megathrust earthquake on the Cascadia subduction zone.

Part of the Solution

Today, the technology exists to detect earthquakes, so quickly, that an alert can reach some areas before strong shaking arrives. The purpose of the ShakeAlert system is to identify and characterize an earthquake a few seconds after it begins, calculate the likely intensity of ground shaking that will result, and deliver warnings to people and infrastructure in harm’s way. This can be done by detecting the first energy to radiate from an earthquake, the P-wave energy, which rarely causes damage. Using P-wave information, we first estimate the location and the magnitude of the earthquake. Then, the anticipated ground shaking across the region to be affected is estimated and a warning is provided to local populations. The method can provide warning before the S-wave arrives, bringing the strong shaking that usually causes most of the damage.

Studies of earthquake early warning methods in California have shown that the warning time would range from a few seconds to a few tens of seconds. ShakeAlert can give enough time to slow trains and taxiing planes, to prevent cars from entering bridges and tunnels, to move away from dangerous machines or chemicals in work environments and to take cover under a desk, or to automatically shut down and isolate industrial systems. Taking such actions before shaking starts can reduce damage and casualties during an earthquake. It can also prevent cascading failures in the aftermath of an event. For example, isolating utilities before shaking starts can reduce the number of fire initiations.

System Goal

The USGS will issue public warnings of potentially damaging earthquakes and provide warning parameter data to government agencies and private users on a region-by-region basis, as soon as the ShakeAlert system, its products, and its parametric data meet minimum quality and reliability standards in those geographic regions. The USGS has set the goal of beginning limited public notifications in 2018. Product availability will expand geographically via ANSS regional seismic networks, such that ShakeAlert products and warnings become available for all regions with dense seismic instrumentation.

Current Status

The West Coast ShakeAlert system is being developed by expanding and upgrading the infrastructure of regional seismic networks that are part of the Advanced National Seismic System (ANSS); the California Integrated Seismic Network (CISN) is made up of the Southern California Seismic Network, SCSN) and the Northern California Seismic System, NCSS and the Pacific Northwest Seismic Network (PNSN). This enables the USGS and ANSS to leverage their substantial investment in sensor networks, data telemetry systems, data processing centers, and software for earthquake monitoring activities residing in these network centers. The ShakeAlert system has been sending live alerts to “beta” users in California since January of 2012 and in the Pacific Northwest since February of 2015.

In February of 2016 the USGS, along with its partners, rolled-out the next-generation ShakeAlert early warning test system in California joined by Oregon and Washington in April 2017. This West Coast-wide “production prototype” has been designed for redundant, reliable operations. The system includes geographically distributed servers, and allows for automatic fail-over if connection is lost.

This next-generation system will not yet support public warnings but does allow selected early adopters to develop and deploy pilot implementations that take protective actions triggered by the ShakeAlert notifications in areas with sufficient sensor coverage.

Authorities

The USGS will develop and operate the ShakeAlert system, and issue public notifications under collaborative authorities with FEMA, as part of the National Earthquake Hazard Reduction Program, as enacted by the Earthquake Hazards Reduction Act of 1977, 42 U.S.C. §§ 7704 SEC. 2.

For More Information

Robert de Groot, ShakeAlert National Coordinator for Communication, Education, and Outreach
rdegroot@usgs.gov
626-583-7225

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan

YOU CAN HELP CATCH EARTHQUAKES AS THEY HAPPEN RIGHT NOW

QCN bloc

Quake-Catcher Network

The Quake-Catcher Network is a collaborative initiative for developing the world’s largest, low-cost strong-motion seismic network by utilizing sensors in and attached to internet-connected computers. With your help, the Quake-Catcher Network can provide better understanding of earthquakes, give early warning to schools, emergency response systems, and others. The Quake-Catcher Network also provides educational software designed to help teach about earthquakes and earthquake hazards.

After almost eight years at Stanford, and a year at CalTech, the QCN project is moving to the University of Southern California Dept. of Earth Sciences. QCN will be sponsored by the Incorporated Research Institutions for Seismology (IRIS) and the Southern California Earthquake Center (SCEC).

The Quake-Catcher Network is a distributed computing network that links volunteer hosted computers into a real-time motion sensing network. QCN is one of many scientific computing projects that runs on the world-renowned distributed computing platform Berkeley Open Infrastructure for Network Computing (BOINC).

BOINCLarge

BOINC WallPaper

The volunteer computers monitor vibrational sensors called MEMS accelerometers, and digitally transmit “triggers” to QCN’s servers whenever strong new motions are observed. QCN’s servers sift through these signals, and determine which ones represent earthquakes, and which ones represent cultural noise (like doors slamming, or trucks driving by).

There are two categories of sensors used by QCN: 1) internal mobile device sensors, and 2) external USB sensors.

Mobile Devices: MEMS sensors are often included in laptops, games, cell phones, and other electronic devices for hardware protection, navigation, and game control. When these devices are still and connected to QCN, QCN software monitors the internal accelerometer for strong new shaking. Unfortunately, these devices are rarely secured to the floor, so they may bounce around when a large earthquake occurs. While this is less than ideal for characterizing the regional ground shaking, many such sensors can still provide useful information about earthquake locations and magnitudes.

USB Sensors: MEMS sensors can be mounted to the floor and connected to a desktop computer via a USB cable. These sensors have several advantages over mobile device sensors. 1) By mounting them to the floor, they measure more reliable shaking than mobile devices. 2) These sensors typically have lower noise and better resolution of 3D motion. 3) Desktops are often left on and do not move. 4) The USB sensor is physically removed from the game, phone, or laptop, so human interaction with the device doesn’t reduce the sensors’ performance. 5) USB sensors can be aligned to North, so we know what direction the horizontal “X” and “Y” axes correspond to.

If you are a science teacher at a K-12 school, please apply for a free USB sensor and accompanying QCN software. QCN has been able to purchase sensors to donate to schools in need. If you are interested in donating to the program or requesting a sensor, click here.

BOINC is a leader in the field(s) of Distributed Computing, Grid Computing and Citizen Cyberscience.BOINC is more properly the Berkeley Open Infrastructure for Network Computing, developed at UC Berkeley.

Earthquake safety is a responsibility shared by billions worldwide. The Quake-Catcher Network (QCN) provides software so that individuals can join together to improve earthquake monitoring, earthquake awareness, and the science of earthquakes. The Quake-Catcher Network (QCN) links existing networked laptops and desktops in hopes to form the worlds largest strong-motion seismic network.

Below, the QCN Quake Catcher Network map
QCN Quake Catcher Network map

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