CRESCENT Earthquake Dynamic Rupture, Earthquake Cycle, and Tsunami Code Verification Platform
DOI:
https://doi.org/10.26443/seismica.v5i2.2716Abstract
Physics-based simulations are critical for understanding natural hazards. The increasing complexity of numerical codes requires benchmark exercises to verify that different computational methods yield consistent results when solving the same governing equations. Here, we present an open-access web platform designed for the verification of earthquake dynamic rupture, seismic cycle, and tsunami simulations. The platform architecture utilizes a modular, serverless backend on Amazon Web Services (AWS) to provide scalable file processing and visualization. A lightweight static web application provides a secure interface for uploading and managing results, while the browser-based data visualization enables interactive analysis of time series and surface grid data. By using structured JavaScript Object Notation (JSON) text files to define benchmark structures, the system remains fully extensible, allowing the addition of new scenarios without modifying the underlying software logic. The platform hosts the "The Tsunami Problem Versions" (TTPV) 1 & 2, two benchmarks for 3D fully coupled earthquake dynamic rupture and tsunami generation, and provides a framework for earthquake cycle models. This community resource aims to build trust in numerical simulations and facilitate long-term collaborative code verification as modeling software continues to evolve.
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Copyright (c) 2026 Loïc Bachelot, Fabian Kutschera, Michael Barall, Brittany A. Erickson, Eric M. Dunham, Alice-Agnes Gabriel, Ruth Harris, Shuo Ma, Amanda M. Thomas, Wenqiang Zhang

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Funding data
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National Science Foundation
Grant numbers 2225286 -
U.S. Geological Survey
Grant numbers G25AC00531 -
Pacific Gas and Electric Company
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National Science Foundation
Grant numbers OAC-2311208;EAR-2121568;OAC-2139536 -
HORIZON EUROPE Framework Programme
Grant numbers 101093038, 101058129, 101058518 -
National Aeronautics and Space Administration
Grant numbers 80NSSC20K0495 -
Gauss Centre for Supercomputing
Grant numbers pn49ha

