CC BY 4.0Antweiler, DarioDarioAntweilerBurgard, Jan PabloJan PabloBurgardHarmening, MarcMarcHarmeningMarheineke, NicoleNicoleMarheinekeSchmeißer, AndreAndreSchmeißerWegener, RaimundRaimundWegenerWelke, PascalPascalWelke2025-04-232025-04-232025-04-232025-04-10https://doi.org/10.24406/publica-4554https://publica.fraunhofer.de/handle/publica/48684710.1007/978-3-031-83097-6_410.24406/publica-4554Nonwoven materials, characterized by a random fiber structure, are essential for various applications including insulation and filtering. An industrial long-term goal is to establish a framework for the simulation-based design of nonwovens. Due to the random structures, simulations of material properties on fiber network level are computational expensive. We propose a predictive model hierarchy for inferring an important material property - the nonwoven tensile strength behavior. The model hierarchy is built using regression-based approaches, including linear and polynomial models, which provide interpretable results. This allows for significant speedup (six orders of magnitude) over the conventional simulations, while achieving good prediction results (R2 = 0.95). The proposed models open the application to nonwoven material design, as they provide accurate and cost-effective surrogates for predicting material properties. In this way, our work serves as a proof of concept.enNonwovensInterpretabilitySimulation000 Informatik, Informationswissenschaft, allgemeine Werke::000 Informatik, Wissen, Systeme::004 Datenverarbeitung; Informatik600 Technik, Medizin, angewandte Wissenschaften::670 Industrielle Fertigung::677 Textilienbook article