Mechanical behaviour and stress-strain recovery characteristics of expanded polypropylene

Abstract

Expanded Polypropylene (EPP) foam has been widely recognized as an energy absorbing material, and it is routinely used for variety of industrial applications. However, EPP foam has a relatively limited scope in the construction industry, especially for load-bearing applications. To address this aspect, the mechanical behaviour of EPP foam was examined under unconfined conditions in this study, and the effects of different preloading/precompression strain histories (5% to 60%) on the stress-strain response and strain energy characteristics of EPP were evaluated. Additionally, the stress-strain recovery behaviour of EPP foam having different preloading histories was also studied while considering the effects of recovery time after preloading (0 to 28 Days). The results suggest that EPP foam subjected to different preloading histories has identical patterns of stress-strain response as of other conventional closed-cell polymeric foams, such as Expanded Polystyrene (EPS) foam, and EPP can adequately be used for load-bearing applications under the recommended design limits. Furthermore, noticeable recovery in the stress-strain response of EPP was also witnessed during the initial 14 days after preloading. Based on these findings, it is anticipated that the promising stress-strain recovery characteristics of EPP foam enable it to be reused, even after experiencing large in-situ deformations.

Modeling hysteresis in expanded polystyrene foams under compressive loads using feed-forward neural networks

“…Other studies have also presented similar discussions and conclusions about the study of energy parameters in polymer foams. [17][18][19][20] Since energy related parameters are useful properties in polymer foam materials for engineering applications, which are also derived primarily from stress-strain curves or force-displacement curves of a material -or a design-, this contribution presents a systematic approach to model strain energy loss due to hysteresis in polystyrene polymer foams at different densities subjected to compressive loading using neural-network-based models. The present work seeks to model parameters at fixed levels and conditions from testing, but also to derive synthetic data outside them.…”

“…Other studies have also presented similar discussions and conclusions about the study of energy parameters in polymer foams. 17–20…”