| About this Abstract |
| Meeting |
7th World Congress on Integrated Computational Materials Engineering (ICME 2023)
|
| Symposium
|
ICME 2023
|
| Presentation Title |
Data-oriented Description of Microstructure-dependent Plastic Material Behavior |
| Author(s) |
Jan Schmidt, Alexander Hartmaier |
| On-Site Speaker (Planned) |
Jan Schmidt |
| Abstract Scope |
Constitutive modelling of anisotropic plastic material behavior traditionally follows a deductive scheme, relying on
empirical observations that are cast into analytic equations, the so-called phenomenological yield functions. Recently,
data-driven constitutive modeling has emerged as an alternative to phenomenological models as it offers a more general
way to describe the material behavior with no or fewer assumptions. In data-driven constitutive modeling, methods of
statistical learning are applied to infer the yield function directly from a data set generated by experiments or numerical
simulations. We present a new generic descriptor for crystallographic texture that allows an explicit consideration of
the microstructure in data-driven constitutive modeling. We prove its ability to capture the structure-property
relationship between a variety of textures and their anisotropic plastic behavior described with the yield function
Yld2004-18p by applying methods of supervised machine learning. In the context of data-driven constitutive modeling,
the descriptor enables consideration of microstructure evolution. |
| Proceedings Inclusion? |
Planned: Other |