70 citations · 78 across the 3 of their papers we have counts for
3 papers
Modular machine learning-based elastoplasticity: generalization in the context of limited data
Jan N. Fuhg, Craig M. Hamel, Kyle Johnson +2
The development of accurate constitutive models for materials that undergo path-dependent processes continues to be a complex challenge in computational solid mechanics. Challenges…
Calibrating constitutive models with full-field data via physics informed neural networks
Craig M. Hamel, Kevin N. Long, Sharlotte L. B. Kramer
The calibration of solid constitutive models with full-field experimental data is a long-standing challenge, especially in materials which undergo large deformation. In this paper,…
Evolutionary Algorithm Guided Voxel-Encoding Printing of Functional Hard-Magnetic Soft Active Materials
Shuai Wu, Craig M. Hamel, H. Jerry Qi +1
Hard-magnetic soft active materials (hmSAMs) have attracted a great amount of research interests due to their fast-transforming, untethered control, as well as excellent programmab…