Data-driven hyperelasticity – Part III: A canonical isotropic formulation for compressible polymeric foams
Journal of the Mechanics and Physics of Solids, cilt.217, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 217
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.jmps.2026.106813
- Dergi Adı: Journal of the Mechanics and Physics of Solids
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Chimica, Compendex, INSPEC, MathSciNet, zbMATH, Academic Search Ultimate (EBSCO), Engineering Source (EBSCO)
- Anahtar Kelimeler: Compressible foam, Constitutive modeling, Data-driven modeling, Hyperelasticity, Mechanical characterization, Polyconvexity
- Orta Doğu Teknik Üniversitesi Adresli: Evet
Özet
Compressible polymeric foams exhibit highly nonlinear mechanical behavior governed primarily by their porosity and cellular architecture. Traditional constitutive models, constrained by predefined analytical forms, often fail to capture this complexity with sufficient accuracy. In this study, we extend a B-spline-based data-driven constitutive framework to compressible materials by adopting an additively separable invariant-based formulation of hyperelasticity. The method adaptively updates control points to minimize discrepancies between experimental observations and model predictions, while ensuring thermodynamic consistency, as well as satisfying normalization and growth conditions through constrained optimization. The framework is validated using a newly generated experimental dataset, reported here for the first time, obtained from closed-cell EPDM foams with three distinct densities, characterized through uniaxial tension, confined compression, and uniaxial compression tests. In addition, experimental data from EPDM rubber are incorporated to further assess the generalizability of the proposed approach across different compressible polymeric materials. Finite element simulations confirm the predictive accuracy of the model. Comparative analyses against classical constitutive models demonstrate the superior performance of the data-driven framework in capturing the complex mechanical response of compressible polymeric foams and rubbers.