Angular grain fragmentation with DEM modeling: application to fault gouge shearing

Angular grain fragmentation with DEM modeling: application to fault gouge shearing | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Angular grain fragmentation with DEM modeling: application to fault gouge shearing Nathalie Casas, Guilhem Mollon, Marco Maria Scuderi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6620399/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Oct, 2025 Read the published version in Granular Matter → Version 1 posted You are reading this latest preprint version Abstract Understanding grain fragmentation in fault gouge is essential for capturing the mechanical behavior and evolution of fault zones under shear. In this study, we present a novel Discrete Element Method (DEM) framework that simulates comminution using angular, breakable grains, overcoming limitations of traditional models based on spherical particles. Our approach incorporates realistic fracture mechanics and grain geometries to better represent microstructural evolution during shearing. A series of numerical experiments—including Brazilian, oedometric, and shear tests—were conducted to calibrate the model and examine the roles of grain strength, friction, and Young’s modulus. The simulations reproduce key numerical observations such as strain localization, force chain evolution, and grain rounding through chipping mechanisms. Results show that the model accurately captures the onset and progression of fragmentation, as well as its impact on fault strength and mechanical stability. A comparison with a dedicated laboratory experiment is provided. This work provides a robust numerical tool for studying fault gouge behavior and lays the foundation for future studies exploring the influence of initial grain size and material properties on fault mechanics. Fragmentation DEM Sheared granular gouge angular grains Full Text Additional Declarations No competing interests reported. Supplementary Files supplementaryinfo.pdf S1confiedunconfinedBMC.avi Cite Share Download PDF Status: Published Journal Publication published 21 Oct, 2025 Read the published version in Granular Matter → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6620399","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":462720601,"identity":"23c6c171-a0b8-4d2f-b21f-d66bff8baff8","order_by":0,"name":"Nathalie 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