Speaker
Description
Data management is crucial in the scope of material science digitalization and collaborative research projects. In this context, a simple modular workflow is proposed to link material properties databases with analytical and numerical modelling tools. As a first step, Ansys Granta MI framework is used and designed to capture and to manage a large amount of experimental data [1]. Then, gateways are established to enable a rapid transfer of material properties from Granta MI into a combination of a Matlab toolbox and Ansys simulation tools to perform parameterized multi-scale modelling [2-3]. The last step is to implement an automatic optimization process of this workflow to achieve excellent convergence between experimental and simulation results [4]. The proposed solution has been applied to study the anisotropic plasticity of Titanium alloy, examined by combining electron backscatter diffraction (EBSD), nanoindentation and atomic force microscopy (AFM) experiments with crystal plasticity finite element (CPFE) simulations [5-6].
[1] Arnold and Maphey, “Integration of Information Management System, Workflow and Computational Tools Enabling Multiscale Modeling Within an ICME Paradigm”, 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference
[2] Mercier et al., “A Matlab toolbox to analyze slip transfer through grain boundaries”, 17th International Conference on Textures of Materials, 2014
[3] https://www.ansys.com/products/structures
[4] Hokes et al., “Optimization as a tool for the inverse identification of parameters of nonlinear material models”, 2015, ISBN: 978-1-61804-346-7
[5] Zambaldi et al., “Orientation informed nanoindentation of α-titanium: Indentation pileup in hexagonal metals deforming by prismatic slip”, Journal of Materials Research, 2012
[6] Su et al., “Quantifying deformation processes near grain boundaries in α titanium using nanoindentation and crystal plasticity modeling.”, International Journal of Plasticity, 2016
| Speaker Country | France |
|---|