Data: Neural network-based multiscale modeling of finite strain magneto-elasticity with relaxed convexity criteria

Data: Neural network-based multiscale modeling of finite strain magneto-elasticity with relaxed convexity criteria https://opara.zih.tu-dresden.de/xmlui/handle/123456789/5996 This collection provides homogenized datasets for magneto-active polymers (MAPs) with stochastic particle distribution and reversible magneto-elastic behavior. The data have been generated by using an in-house finite element code based on Matlab. 2026-04-06T07:08:51Z Homogenized data magneto-active polymers https://opara.zih.tu-dresden.de/xmlui/handle/123456789/5999 Homogenized data magneto-active polymers Kalina, Karl Alexander; Gebhart, Philipp; Brummund, Jörg; Linden, Lennart; Sun, WaiChing; Kästner, Markus Herein, homogenized datasets for magneto-active polymers (MAPs) with stochastic particle distribution and reversible magneto-elastic behavior are provided. The data have been generated by using an in-house finite element code based on Matlab. For the calculation of the effective tensor values, 2D statistical volume elements (SVEs) have been used. The data can be applied to calibrate macroscopic surrogate models. 2023-01-01T00:00:00Z