Abstract
We present a highly scalable 3D fully-coupled Earth & ocean model of earthquake rupture and tsunami generation and perform the first fully coupled simulation of an actual earthquake-Tsunami event and a 3D benchmark problem of tsunami generation by a megathrust dynamic earthquake rupture. Multi-petascale simulations, with excellent performance demonstrated on three different platforms, allow high-resolution forward modeling. Our largest mesh has ?261 billion degrees of freedom, resolving at least 15 Hz of the acoustic wave field.We self-consistently model seismic, acoustic and surface gravity wave propagation in elastic (Earth) and acoustic (ocean) materials sourced by physics-based non-linear earthquake dynamic rupture, thereby gaining insight into the tsunami generation process without relying on approximations that have previously been applied to permit solution of this challenging problem. Complicated geometries, including high-resolution bathymetry, coastlines and segmented earthquake faults are discretized by adaptive unstructured tetrahedral meshes. This inevitably leads to large differences in element sizes and wave speeds which can be mitigated by ADER local time-stepping and a Discontinuous Galerkin discretization yielding high-order accuracy in time and space.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis |
| Publisher | ACM |
| ISBN (Print) | 9781450384421 |
| DOIs | |
| State | Published - Nov 14 2021 |
| Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2022-06-23Acknowledged KAUST grant number(s): ORS-2017-CRG6 3389.02
Acknowledgements: This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 823844 (ChEESE – Centre of Excellence in Solid Earth). Compute resources were provided by the Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) on SuperMUC-NG at the Leibniz Supercomputing Centre (www.lrz.de, project pn68fi), by the CSC – IT Center for Science, Finland (project 2003841, on Mahti) and by the Supercomputing Laboratory at King Abdullah University of Science & Technology (KAUST, project k1488, on Shaheen-II) in Thuwal, Saudi Arabia. We thank all colleagues at LRZ, CSC and KAUST for their excellent support. C.U., T.U. and A.-A.G. acknowledge additional support by the European Union’s Horizon 2020 Research and Innovation Programme under ERC StG TEAR, no. 852992, the German Research Foundation (DFG) (grants no. GA 2465/2-1, GA 2465/3-1) and by KAUST-CRG (grant no. ORS-2017-CRG6 3389.02). L.S.A. was supported by National Science Foundation grant DGE-1656518.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.