A strategy to formulate data-driven constitutive models from random multiaxial experiments
We present a test technique and an accompanying computational framework to obtain data-driven, surrogate constitutive models that capture the response of isotropic, elastic-plastic materials loaded in-plane stress by combined normal and shear stresses. The surrogate models are based on feed-forward...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Springer Nature
2022
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