Physics-Based Probabilistic Seismic Hazard Assessment (PSHA)

A Use Case by

Short description

Physics-Based Probabilistic Seismic Hazard Assessment (PSHA) is widely established for deciding safety criteria for making official national hazard maps, developing building code requirements, safety of critical infrastructure (e.g. nuclear power plants) and determining earthquake insurance rates by governments and industry. However, PSHA currently rests on empirical, time-independent assumptions known to be too simplistic and conflict with earthquake physics. Respective deficits become apparent as many damaging earthquakes occur in regions rated as low-risk by PSHA hazard maps and near-fault effects from rupture on extended faults is not taken into account. Combined simulations of dynamic fault rupture and seismic wave propagation are crucial tools to shed light onto the poorly constrained processes of earthquake faulting. Realistic model setups should acknowledge topography, 3D geological structures, rheology, and fault geometries with appropriate stress and frictional parameters, all of which contribute to complex ground motion patterns. A fundamental challenge hereby is to model the high frequency content of the three-dimensional wave field, since the frequency range of 0–10 Hz is of pivotal importance for engineering purposes. Multiple executions of such multi-physics simulations need to be performed to provide a probabilistic-based hazard estimation.

Results & Achievements

Fault models built up in both north and south Iceland

Fully non-linear dynamic simulations accounting for 3-D velocity structures, topography, off-fault plasticity, and model parameter uncertainties and achieved target resolution.

Cybershake implemented successfully and a demo run for south Iceland
Generate the rupture probability using SHERIFS

GMPEs based hazard curves and maps with OpenQuake

About the code SeisSol: Extended YATeTo DSL to generate GPU GEMM kernels

Developed a python library as a GEMM backend for YATeTo

Adapted both SeisSol and YATeTO for batched computations

Implemented Elastic Solver: time, local, neighbour integrals

Both GTS and LTS scheme are working Enabled a distributed Multi-GPU setup Implemented Plasticity kernel (needs to get updated)

Tested performance on a multi-GPU distributed cluster: M100

Merged first stage from experimental to the production code

As a result, we obtained a 23% time reduction with respect to the GPU-only execution. In practice, this represents a performance boost equivalent to attaching an additional GPU per node and thus a much more efficient exploitation of the resources.

Objectives

The objectives of this use case is to develop general concepts for enabling physics-based seismic hazard assessment with state-of-the-art multi-physics earthquake simulation software (SeisSol, SpecFEM3D, ExaHyPE, AWP-ODC) and conduct 3D physics-based seismic simulations to improve PSHA for validation scenarios provided by IMO (Iceland) and beyond. This use case is expected to be applicable to supplement established methods by stakeholders, for different target regions and varying degrees of complexity.

Technologies

Workflow

The workflow of this pilot is shown in Figure 1.

To use the SeisSol code to run fully non-linear dynamic rupture simulations, accounting for various fault geometries, 3D velocity structures, off-fault plasticity, and model parameters uncertainties, to build a fully physics-based dynamic rupture database of mechanically plausible scenarios.

Then the linked post-processing python codes are used to extract ground shakings (PGD, PGV, PGA and SA in different periods) from the surface output of SeisSol simulations to build a ground shaking database.

SHERIFS uses a logic tree method, with the input of the fault to fault ruptures from dynamic rupture database, converting the slip rate to the annual seismic rate given the geometry of the fault system.

With the rupture probability estimation from SHERIFS, and ground shakings from the SeisSol simulations, we can generate the hazard curves for selected site locations and hazard maps for the study region.

In addition, the OpenQuake can use the physics-based ground motion models/prediction equations, established with the ground shaking database from fully dynamic rupture simulations. And the Cybershake, which is based on the kinematic simulations, to perform the PSHA and complement the fully physics-based PSHA.

Software involved

SeisSol (LMU)

ExaHyPE (TUM)

AWP-ODC (SCEC)

SHERIFS (Fault2SHA and GEM)

sam(oa)² (TUM)

OpenQuake (GEM): https://github.com/gem/oq-engine

Pre-processing:

Mesh generation tools: Gmsh (open source), Simmetrix/SimModeler (free for academic institution), PUMGen

Post-processing & Visualization: Paraview, python tools