Industrial Applications of Microstructural Characterization — Current and Potential Future Issues and Applications

Furrer, David; Noraas, Ryan; Brough, David B.

doi:10.1201/9781315121062-22

Cited by 1 publication

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“…Within the MSE literature, myriad reports and papers describe methods for microstructure quantification and representation. Over time, industries have employed these to optimise and control mechanical properties, sometimes tying descriptors to distributions of behaviour [1][2][3][4][5]. Since the early 1900s microstructure quantification has evolved from photomicrographic standards that humans viewed and compared to unknown samples, to methods of image analysis by manual point counting or dimensional or area measurements, and eventually to computer-aided automated feature delineation and quantification.…”

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confidence: 99%

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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