journal article·2026-08Open access

Characterization and Modeling of the Time- and Temperature-Dependent Behavior of a Closed-Cell Polymer Structural Foam under Compression

Sarah Schlegel, Eike Anton Schneider, Martin Rosenschon, Sascha Riegler, Florian Wittemann, Luise Kärger

Applied Composite Materials· Volume 33· Issue 4

Abstract

Abstract The thermo-viscoelastic behavior of a closed-cell polyethylene terephthalate (PET) structural foam is investigated in order to accurately capture foam core deformations during manufacturing of composite sandwich structures, e.g. in Liquid Composite Molding (LCM), and their influence on the structural performance of the final components. The foam exhibits a transversely isotropic material behavior due to its manufacturing in the strand foam extrusion process. Compression tests are carried out in Dynamic Mechanical Analysis (DMA), where the heterogenous foam structure poses some difficulties in finding a valid measuring range and adequate parameter sets compared to a homogenous material. Therefore, close care is taken to select the right load range and sample size. In this way, the time- and temperature-dependency of the homogenized macroscopic material behavior of the structural foam is received. From the measured data, master curves are constructed using the time-temperature superposition principle and a temperature- and time-dependent prony series is fitted to the data. A non-isothermal modeling approach is proposed to capture the stiffness changes due to heating during the manufacturing process. The model is integrated into an open-source finite element framework and the underlying behavior is verified against a commercially available finite element model. The results show that the proposed model is able to accurately capture the thermoviscoelastic behavior of the foam under non-isothermal conditions.
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Research context

OpenAlex topics: Polymer Foaming and Composites · Cellular and Composite Structures · Polymer crystallization and properties

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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