Journal
INTERNATIONAL JOURNAL FOR MULTISCALE COMPUTATIONAL ENGINEERING
Volume 14, Issue 4, Pages 389-413Publisher
BEGELL HOUSE INC
DOI: 10.1615/IntJMultCompEng.2016016841
Keywords
micro-CT imaging; micro-polar plasticity; critical state; higher-order continuum; Hostun Sand
Funding
- Earth Materials and Processes program at the US Army Research Office [W911NF-14-1-0658, W911NF-15-1-0581]
- Mechanics of Material program at National Science Foundation [CMMI-1462760, EAR-1516300]
- Provost's Grants Program for Junior Faculty at Columbia University
- Directorate For Engineering [1462760] Funding Source: National Science Foundation
- Directorate For Geosciences [1516300] Funding Source: National Science Foundation
- Division Of Earth Sciences [1520732] Funding Source: National Science Foundation
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Unlike a conventional first-order continuum model, the material parameters of which can be identified via an inverse problem conducted at material point that exhibits homogeneous deformation, a higher-order continuum model requires information from the derivative of the deformation gradient. This study concerns an integrated experimental-numerical procedure designed to identify material parameters for higher-order continuum models. Using a combination of micro-CT images and macroscopic stress-strain curves as the database, we construct a new finite element inverse problem which identifies the optimal value of material parameters that matches both the macroscopic constitutive responses and the meso-scale micropolar kinematics. Our results indicate that the optimal characteristic length predicted by the constrained optimization procedure is highly sensitive to the types and weights of constraints used to define the objective function of the inverse problems. This sensitivity may in return affect the resultant failure modes (localized vs. diffuse), and the coupled stress responses. This result signals that using the mean grain diameter alone to calibrate the characteristic length may not be sufficient to yield reliable forward predictions.
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