Abstract
This article investigates an energy-based multiscale damage criterion for a biaxial loading case. The criterion incorporates crystal plasticity at the microscale that produces a damage tensor, representing the local damage state derived from a least squares method. The damage tensor, driven by modification of strain energy density on each potential slip system, is averaged from local to grain level to obtain a damage vector for each grain. The Kreisselmeier-Steinhauser function, which produces an envelope function for multiobjective optimization is adopted to predict the failure of a meso-representative volume element, and to calculate the damage index for meso-representative volume element. A weighted averaging method is also used to simultaneously provide the most potential cracking directions for meso-representative volume element. In order to verify that the developed method is capable of producing an acceptable prediction of fatigue damage initiation and growth under multiaxial loading conditions, a cruciform specimen is used for biaxial loading. A biaxial torsion MTS machine is used to conduct fatigue tests on the cruciform specimen. Numerical fatigue analysis is also performed based on the multiscale fatigue damage criterion. Comparing the simulation results with the experimental data shows that the multiscale fatigue damage model can provide acceptable prediction of failure of meso-representative volume element and crack direction.
Original language | English (US) |
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Pages (from-to) | 2084-2096 |
Number of pages | 13 |
Journal | Journal of Intelligent Material Systems and Structures |
Volume | 24 |
Issue number | 17 |
DOIs | |
State | Published - Nov 1 2013 |
Keywords
- Al alloys
- multiscale modeling
- structural health monitoring
ASJC Scopus subject areas
- Materials Science(all)
- Mechanical Engineering