{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/grfsaw-a-lightweight-stochastic","title":"GRFsaw: A lightweight stochastic microstructure generator","arxiv_id":"2412.05168","date":"2024-12-06","proceeding":null,"authors":["Lars Blatny","Henning Löwe","Johan Gaume"],"abstract":"This article presents GRFsaw, an open-source software for generating two-phase (binary) microstructures with user-defined structural properties. Unlike most standard software for microstructure generation, GRFsaw is based on the concept of thresholding Gaussian random fields (GRF). It is designed to be used by researchers or engineers in need of a lightweight tool to generate microstructures of various geometries, for example as input to simulations or to other models where such geometries are needed. This could be simulations of fluid flow through porous media, in predictive models of electromagnetic scattering by materials, or in mechanical loading simulations in order to assess, e.g., the material's elasticity or strength.","url_abs":"https://arxiv.org/abs/2412.05168v1","url_pdf":"https://arxiv.org/pdf/2412.05168v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"grfsaw-a-lightweight-stochastic","repo_url":"https://github.com/larsblatny/GRFsaw","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}