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Abstract The nonlinear mechanical responses of rocks and soils to seismic waves play an important role in earthquake physics, influencing ground motion from source to site. Continuous geophysical monitoring, such as ambient noise interferometry, has revealed co‐seismic wave speed reductions extending tens of kilometers from earthquake sources. However, the mechanisms governing these changes remain challenging to model, especially at regional scales. Using a nonlinear damage model constrained by laboratory experiments, we develop and apply an open‐source 3D discontinuous Galerkin method to simulate regional co‐seismic wave speed changes during the 2015 Mw7.8 Gorkha earthquake. We find pronounced spatial variations of co‐seismic wave speed reduction, ranging from <0.01% to >50%, particularly close to the source and within the Kathmandu Basin, while disagreement with observations remains. The most significant reduction occurs within the sedimentary basin and varies with basin depths, whereas wave speed reductions correlate with the fault slip distribution near the source. By comparing ground motions from simulations with elastic, viscoelastic, elastoplastic, and nonlinear damage rheologies, we demonstrate that the nonlinear damage model effectively captures low‐frequency ground motion amplification due to strain‐dependent wave speed reductions in soft sediments. We verify the accuracy of our approach through comparisons with analytical solutions and assess its scalability on high‐performance computing systems. The model shows near‐linear strong and weak scaling up to 2,048 nodes, enabling efficient large‐scale simulations. Our findings provide a physics‐based framework to quantify nonlinear earthquake effects and emphasize the importance of damage‐induced wave speed variations for seismic hazard assessment and ground motion predictions.
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Modeling and Quantifying Parameter Uncertainty of Co‐Seismic Non‐Classical Nonlinearity in Rocks
Abstract Dynamic perturbations reveal unconventional nonlinear behavior in rocks, as evidenced by field and laboratory studies. During the passage of seismic waves, rocks exhibit a decrease in elastic moduli, slowly recovering after. Yet, comprehensive physical models describing these moduli alterations remain sparse and insufficiently validated against observations. Here, we demonstrate the applicability of two physical damage models—the internal variable model (IVM) and the continuum damage model (CDM)—to provide quantitative descriptions of nonlinear co‐seismic elastic wave propagation observations. While the IVM uses one internal variable to describe the evolution of elastic material moduli, the CDM damage variable is a mathematical representation of microscopic defects. We recast the IVM and CDM models as nonlinear hyperbolic partial differential equations and implement 1D and 2D numerical simulations using an arbitrary high‐order discontinuous Galerkin method. We verify the modeling results with co‐propagating acousto‐elastic experimental measurements. Subsequently, we infer the parameters for these nonlinear models from laboratory experiments using probabilistic Bayesian inversion and 2D simulations. By adopting the Adaptive Metropolis Markov chain Monte Carlo method, we quantify the uncertainties of inferred parameters for both physical models, investigating their interplay in 70,000 simulations. We find that the damage variables can trade off with the stress‐strain nonlinearity in discernible ways. We discuss physical interpretations of both damage models and that our CDM quantitatively captures an observed damage increase with perturbation frequency. Our results contribute to a more holistic understanding of co‐seismic damage and post‐seismic recovery after earthquakes bridging the worlds of theoretical analysis and laboratory findings.
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- Award ID(s):
- 2121568
- PAR ID:
- 10484652
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Solid Earth
- Volume:
- 129
- Issue:
- 1
- ISSN:
- 2169-9313
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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