Applications: Simulation of EarthquakesEvan Bollig, bollig@scs.fsu.edu

Summary

Motivation

Earthquake modeling and simulation

Data Assimilation

Computational Requirements

Case Studies

Importance of Earthquake Simulations

Kobe, Japan (1995)

Magnitude 6.9 --> $200B in damage

5,500 Dead; 26,000 Injured

Active prediction program was in place, but not sophisticated enough to give warning

Living on an ACTIVE Earth: Perspectives on Earthquake Science. National Academic Press, Washington D.C. 2003

Things to remember[...] currently no approaches to earthquake forecasting that are uniformly reliable. {SRC p.213}

Events may repeat, but span longer time than documented history and/or larger space than sensor networks can monitor

“Grand Challenges” are just starting

Most “large-scale parallel simulations” are attempts to prove it can be done in parallel

Earthquake models useful in other disciplines (i.e. Tsunami- and Geo-engineers)

Spatial/Temporal Scales{S

RC

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}

Scales (Cont.)

Microscopic (~10-6m to 10-1m)

Fault-zone (~10-1m to 102m)

Fault-system (~102m to 104m)

Regional Fault-Network (~104m to 105m)

Tectonic Plate-Boundary (~105m to 107m)

Typical Computational Problems

Data Assimilation

Sensors provide incomplete information to existing simulations

Simulation attempts to forecast possible aftershocks and damage to infrastructures

Example: disloc (NASA JPL)

Earthquake Fault-System Simulations

Particle/slider-block model

Earthquake occurs when cluster of particles displace at same time

Grand Challenges for Earthquakes

Subcommittee on Disaster Reduction (US Government) has 10 year strategy, 6 challenges

Provide hazard and disaster information where and when it is needed

Understand the natural processes that produce hazards

Develop hazard mitigation strategies and technologies

Reduce the vulnerability of infrastructure

Assess disaster resilience

Promote risk-wise behavior

Other Grand Challenge Initiatives

Network for Earthquake Engineering Simulation (NEES)

APEC Cooperation for Earthquake Simulation (ACES)

Australian Computational Earth Systems Simulator (ACcESS)

Network for Earthquake Engineering Simulation (NEES)

NSF Funded “Collaboratory” managing “Grand Challenges” in Geosciences

Share data, software and facilities to encourage collaboration

Provide metadata documenting simulations and events

High Priority Topics:

Performance-based criteria for design, evaluation and retrofit of new/existing structures

Post-disaster safety assessment, repair, loss estimation

Model-based analysis

Example NEES Project

Mitigation of Collapse Risk in Older Concrete Buildings

http://peer.berkeley.edu/grandchallenge/index.html

Hazard assessments in one or more urban regions

Lab and field tests in addition to computational models

January 2007 - December 2012; $3.6M

ACES

Offshoot of APEC (Asia Pacific Economic Cooperation)

APEC Cooperation for Earthquake Simulation

Sponsored by Australia, China, Japan and United States

Goal: develop simulation for the complete earthquake process and provide virtual laboratory to probe behavior

iSERVO Project (ACES)

the international Solid Earth Virtual Research Observatory

http://iservo.edu.au

Started in 2003

Mission: develop web-based services and grid technologies to ensure seamless access to data and models

iSERVO ResultsVirtual California (QUAKESim)

1000 Year simulation

faults divided into 650 segments (10km long, 15km deep)

http://quakesim.jpl.nasa.gov/animations.html

iSERVO ResultsAustralian intraplate model (FEM)

Model interaction bewteen multiple plates

Software Frameworks

OpenSEES (NEES)

Object oriented library for building models, solving problems, etc.

Tcl Model Builder

http://opensees.berkeley.edu/index.php

GeoFEST

2D/3D FEM package written in C

http://www.physics.hmc.edu/GL/geofest/

GeoFEM (used on EarthSimulator)

http://geofem.tokyo.rist.or.jp/

Case Studies: TeraShakeTeraShake 2.1

Mw 7.7 earthquake

230 km section of San Andreas fault

60 second rupture; 250 second simulation

Mesh Dimensions: 3000 x 1500 x 400

contains 1.8 billion cubes (200m resolution)

Computing Requirements

18,000 CPU hrs

240 processors of the 10 teraflop IBM DataStar supercomputer at SDSC

47 TB of data produced (150,000 files)

http://www.hpcwire.com/hpcwire/hpcwireWWW/04/1217/108981.htmlhttp://epicenter.usc.edu/cmeportal/TeraShake.html

See What’s Shaking (IEEE Vis 2006)

Contest to visualize subset of TeraShake 2.1 data

Motivate new techniques and software for seismic visualization

See What’s Shaking (IEEE Vis 2006)

Contest to visualize subset of TeraShake 2.1 data

Motivate new techniques and software for seismic visualization http://2006_ieee_vis.sdsc.edu/2006_ieee_vis_data/submissions/

22122/terashake1.png

See What’s Shaking (IEEE Vis 2006)

Contest to visualize subset of TeraShake 2.1 data

Motivate new techniques and software for seismic visualization http://2006_ieee_vis.sdsc.edu/2006_ieee_vis_data/submissions/

87788/Image%202.png

See What’s Shaking (IEEE Vis 2006)

Contest to visualize subset of TeraShake 2.1 data

Motivate new techniques and software for seismic visualization

Bollig, Womeldorff, Chen (2008)

Case Study: Tsunami Simulation

December 26, 2004

Mw 9.3 event

produced waves up to 25m (80ft) tall

New Jersey water level fluctuated 34cm

300,000 people killed

Case Study: Tsunami Simulation

December 26, 2004

Mw 9.3 event

produced waves up to 25m (80ft) tall

New Jersey water level fluctuated 34cm

300,000 people killed

Court

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Tsunami ModelFinite Element Method

more than 2 million nodes

Mesh generated from GTOPO30 (http://

edc.usgs.gov/products/elevation/gtopo30/gtopo30.html)

global elevation model with grid spacing of 30 arc seconds (1 km)

Huai Zhang, Yaolin Shi, Dave A. Yuen, Ying-chun Liu, Chaofan

Zhang and Xiaoru Yuan, "Modelling and Visualization of Tsunamis"

Submitted to Pure and Applied Geophysics (PAGEOPH). Birkhauser

Verlag AG. (In Press).

Tsunami ModelFinite Element Method

more than 2 million nodes

Mesh generated from GTOPO30 (http://

edc.usgs.gov/products/elevation/gtopo30/gtopo30.html)

global elevation model with grid spacing of 30 arc seconds (1 km)

Huai Zhang, Yaolin Shi, Dave A. Yuen, Ying-chun Liu, Chaofan

Zhang and Xiaoru Yuan, "Modelling and Visualization of Tsunamis"

Submitted to Pure and Applied Geophysics (PAGEOPH). Birkhauser

Verlag AG. (In Press).

Case Studies: Tsunami SimulationProbabilistic model for forecasting hazards

Scenario with inter-plate thrust along Manila subduction zone in South China Sea

Mw 7.5 event southwest of Philippines

Furthest from Chinese mainland

Yingchun Liu, Angela Santos, Shuo M. Wang, Yaolin Shi, Hailing Liu, and David A. Yuen.

Tsunami Hazards From Potential Earthquakes along South China Coast. Physics of the

Earth and Planetary Interiors (PEPI). Elsevier, 2007, Vol.163, 233–245. (SCI)

Creative Expression

Results overlayed in Google Earth (interactive)

Carefully chosen colormaps help isolate areas at high risk of damage

Xiaoru Yuan, Yingchun Liu, Baoquan Chen, David A. Yuen and Tomas

Pergler. “Visualization of High Dynamic Range Data in Geosciences”

Physics of the Earth and Planetary Interiors (PEPI), 163:312-320, 2007.

Elsevier. DOI

Acknowledgements

Thanks to Yuen’s Group (Univ. of MN Twin Cities) for Tsunami images