To accurately predict fracture patterns in quasi-brittle materials, it is necessary to accurately characterize heterogeneity in the properties of a material microstructure. This heterogeneity influences crack propagation at weaker points. Also, inherent randomness in localized material properties creates variability in crack propagation in a population of nominally identical material samples. In order to account for heterogeneity in the strength properties of a material at a small scale (or “microscale”), a mesoscale model is developed at an intermediate scale, smaller than the size of the overall structure. A central challenge of characterizing material behavior at a scale below the representative volume element (RVE), is that the stress/strain relationship is dependent upon boundary conditions imposed. To mitigate error associated with boundary condition effects, statistical volume elements (SVE) are characterized using a Voronoi tessellation based partitioning method. A moving window approach is used in which partitioned Voronoi SVE are analysed using finite element analysis (FEA) to determine a limiting stress criterion for each window. Results are obtained for hydrostatic, pure and simple shear uniform strain conditions. A method is developed to use superposition of results obtained to approximate SVE behavior under other loading conditions. These results are used to determine a set of strength parameters for mesoscale material property fields. These random fields are then used as a basis for input in to a fracture model to predict fracture patterns in quasi-brittle materials.
Mesoscale Models Characterizing Material Property Fields Used As a Basis for Predicting Fracture Patterns in Quasi-Brittle Materials
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Acton, KA, Baxter, SC, Bahmani, B, Clarke, PL, & Abedi, R. "Mesoscale Models Characterizing Material Property Fields Used As a Basis for Predicting Fracture Patterns in Quasi-Brittle Materials." Proceedings of the ASME 2017 International Mechanical Engineering Congress and Exposition. Volume 9: Mechanics of Solids, Structures and Fluids; NDE, Structural Health Monitoring and Prognosis. Tampa, Florida, USA. November 3–9, 2017. V009T12A061. ASME. https://doi.org/10.1115/IMECE2017-71500
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