Data Structures and Workflows for ICME

Donegan, Sean P.; Groeber, Michael A.

doi:10.1007/978-3-030-40562-5_2

Cited by 2 publications

(2 citation statements)

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“…To link SERVE to intrinsic spatial variation in a part, Donegan and Groeber [169] have suggested a method for objectively and quantitatively partitioning the spatial domain of an engineered component, into regions or 'zones' of common processing state variables, or microstructure, using machine learning tools. Using a clustering algorithm [170] within the DREAM.3D software, their work computationally partitioned regions of a small forging, using data generated from metal forging simulations, and microstructure characterisation.…”

Section: Requirements and Linkages To Materials Processes And Structu...mentioning

confidence: 99%

“…Figure 26a shows a map of the effective strain for each mesh element, as determined by process simulations (DEFORM, 2022), for a small Ti-6Al-4 V pancake forging. Following the methods in [169], the K-medoids clustering tool available in DREAM.3D was used to assign the effective strains to 4 zones or clusters (Figure 26b), thereby dividing the forging into 4 regions that may warrant having their own SEVM based on changing microstructure. The number of zones of interest is a user-selected variable.…”

Section: Requirements and Linkages To Materials Processes And Structu...mentioning

confidence: 99%

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Statistically equivalent representative volume elements (SERVE) for material behaviour analysis and multiscale modelling

Ghosh,

Dimiduk,

Furrer

2023

International Materials Reviews

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Mechanical properties of materials and associated engineered components are controlled by the material structure at various lengths and time scales. As materials are being further utilised to the maximum extent of their capabilities, tails on property distributions become significant. These tails are often driven by the extremities of microstructural feature distributions, suggesting the need for a statistically relevant description of the microstructure and a reciprocity relationship with the range of property measurement capabilities and the models that represent this information.Representative volume elements (RVE) and statistically equivalent representative volume elements (SERVE) have emerged as frameworks for such microstructural characterisation and quantification.This review covers the evolution of quantitative microstructure description for use in material behaviour predictions from homogenised representations, large volume statistical representation, to the determination of the minimum spatial size to statistically represent a microstructure based on features of interest and properties of interest.

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Section: Requirements and Linkages To Materials Processes And Structu...mentioning

confidence: 99%

Section: Requirements and Linkages To Materials Processes And Structu...mentioning

confidence: 99%