A Flexible and Efficient Output File Format for Grain-Scale Multiphysics Simulations
Source abstract
Abstract
Modern high-performing structural materials gain their excellent properties from the complex interactions of various constituent phases, grains, and subgrain structures that are present in their microstructure. To further understand and improve their properties, simulations need to take into account multiple aspects in addition to the composite nature. Crystal plasticity simulations incorporating additional physical effects such as heat generation and distribution, damage evolution, phase transformation, or changes in chemical composition enable the compilation of comprehensive structure–property relationships of such advanced materials under combined thermo-chemo-mechanical loading conditions. Capturing the corresponding thermo-chemo-mechanical response at the microstructure scale usually demands specifically adopted constitutive descriptions per phase. Furthermore, to bridge from the essential microstructure scale to the component scale, which is often of ultimate interest, a sophisticated (computational) homogenization scheme needs to be employed. A modular simulation toolbox that allows the problem-dependent use of various constitutive models and/or homogenization schemes in one concurrent simulation requires a flexible and adjustable file format to store the resulting heterogeneous data. Besides dealing with heterogeneous data, a file format suited for microstructure simulations needs to be able to deal with large (and growing) amounts of data as (i) the spatial resolution of routine simulations is ever increasing and (ii) more and more quantities are taken into account to characterize a material. To cope with such demands, a flexible and adjustable data layout based on HDF5 is proposed. The key feature of this data structure is the decoupling of spatial position and data, such that spatially variable information can be efficiently accommodated. For position-dependent operations, e.g., spatially resolved visualization, the spatial link is restored through explicit mappings between simulation results and their spatial position.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Composite Material Mechanics · Advanced Mathematical Modeling in Engineering · Machine Learning in Materials Science
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References (17)
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