A data-driven constitutive model for compressible polymeric foams

Date

2025-01-01

Author

Açan, Alp Kağan
Gargı, Y.
Başdemir, Selçuk
Dal, Hüsnü

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Compressible polymeric foams exhibit a highly non-linear mechanical behaviour. Classical constitutive models have a fixed Mathema tical expression. Degree of porosity and the cellular structure of the foam affects the mechanical response significantly. In this regard, phenomenological constitutive models may not be successful in modeling a variety of compressible polymeric foams. Data-driven constitutive modeling is a promising approach to solve this problem, here we propose an extended version of B-spline based data-driven framework (Dal, Denli, Açan, & Kaliske 2023) for compressible materials. The model adapts its control point values to reduce the error between data and prediction until a threshold is reached, and is thermodynamically consistent through the use of optimization constraints. The proposed model has been validated with closed-cell EPDM (ethylene propylene diene monomer) with three distinct foam densities. The uniaxial tension and the confined compression experiments were conducted to identify the mechanical behavior of the materials. A non-homogeneous uniaxial compression experiment was performed to validate the control points obtained through the simultaneous fitting of uniaxial tension and confined compression. Finite element analysis was conducted under conditions precisely replicated from the non-homogeneous uniaxial compression experiment. Furthermore, a comparison is performed between the classical constitutive models (Blatz & Ko 1962, Hill 1979) and the proposed data-driven approach. The results show that the data-driven approach is very promising to model the mechanical behavior of compressible polymeric materials.

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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85217720134&origin=inward
https://hdl.handle.net/11511/113643

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Department of Mechanical Engineering, Conference / Seminar