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Published May 9, 2018 | Published
Journal Article Open

A comparison between rate-and-state friction and microphysical models, based on numerical simulations of fault slip

Abstract

Rate-and-state friction (RSF) is commonly used for the characterisation of laboratory friction experiments, such as velocity-step tests. However, the RSF framework provides little physical basis for the extrapolation of these results to the scales and conditions of natural fault systems, and so open questions remain regarding the applicability of the experimentally obtained RSF parameters for predicting seismic cycle transients. As an alternative to classical RSF, microphysics-based models offer means for interpreting laboratory and field observations, but are generally over-simplified with respect to heterogeneous natural systems. In order to bridge the temporal and spatial gap between the laboratory and nature, we have implemented existing microphysical model formulations into an earthquake cycle simulator. Through this numerical framework, we make a direct comparison between simulations exhibiting RSF-controlled fault rheology, and simulations in which the fault rheology is dictated by the microphysical model. Even though the input parameters for the RSF simulation are directly derived from the microphysical model, the microphysics-based simulations produce significantly smaller seismic event sizes than the RSF-based simulation, and suggest a more stable fault slip behaviour. Our results reveal fundamental limitations in using classical rate-and-state friction for the extrapolation of laboratory results. The microphysics-based approach offers a more complete framework in this respect, and may be used for a more detailed study of the seismic cycle in relation to material properties and fault zone pressure-temperature conditions.

Additional Information

© 2017 The Authors. Published by Elsevier B.V. Open Access funded by European Research Council. Under a Creative Commons license. Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) Received 26 July 2017, Revised 9 November 2017, Accepted 28 November 2017, Available online 5 December 2017. The authors thank the guest editor M.-L. Doah, M. Thomas, and an anonymous reviewer for their thoughtful comments. This project is supported by the European Research Council (ERC), grant no. 335915, and by the NWO Vidi-grant 854.12.001 awarded to A.R. Niemeijer. J.P.A. acknowledges supplemental funding to NSF CAREER grant EAR-1151926 for research opportunities in Europe. The most recent version of the QDYN source code, including the modifications presented in this work, is publicly available at https://github.com/ydluo/qdyn.

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