RT Journal Article
T1 Some practical considerations for compression failure characterization of open-cell polyurethane foams using digital image correlation
A1 Belda, Ricardo
A1 Megías, Raquel
A1 Feito Sánchez, Norberto
A1 Vercher Martínez, Ana
A1 Giner, Eugenio
AB Background: Open-cell polyurethane foam mechanical behavior is highly influenced by microstructure. The determination of the failure mechanisms and the characterization of the deformation modes involved at the micro scale is relevant for accurate failure modeling. Methods: We use digital image correlation (DIC) to investigate strain fields of open-cell polyurethane foams of three different densities submitted to compression testing. We analyze the effect of some DIC parameters on the failure pattern definition and the equivalent strain magnification at the apparent ultimate point. Moreover, we explore speckle versus non-speckle approaches and discuss the importance of determining the pattern quality to perform the displacement correlation. Results: DIC accurately characterizes the failure patterns. A variation in the subset size has a relevant effect on the strain magnification values. Step size effect magnitude depends on the subset size. The pattern matching criterion presented little influence (3.5%) on the strain magnification. Conclusion: The current work provides a comprehensive analysis of the influence of some DIC parameters on compression failure characterization of foamed structures. It highlights that changes of subset and step sizes have a significant effect on the failure pattern definition and the strain magnification values, while the pattern matching criterion and the use of speckle have a minor influence on the results. Moreover, this work stands out that the determination of the pattern quality has a major importance for texture analysis. The in-depth, detailed study carried out with samples of three different apparent densities is a useful guide for DIC users as regards texture correlation and foamed structures.
PB MDPI
SN 1424-3210
YR 2020
FD 2020-08-01
LK https://hdl.handle.net/10016/37751
UL https://hdl.handle.net/10016/37751
LA eng
NO This research was funded by the Spanish Ministerio de Ciencia, Innovación y Universidades grant numbers DPI2013-46641-R and DPI2017-89197-C2-2-R and the Generalitat Valenciana, Programme PROMETEO 2016/007 and Plan FDGENT 2018 GVA.
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RD 27 jul. 2024