Systematic and objective identification of the microstructure around damage directly from images

Abstract

An original experimental approach is presented to automatically determine the average phase distribution around damage sites in multi-phase materials. An objective measure is found to be the average intensity around damage sites, calculated using many images. This method has the following benefits: no phase identification or manual interventions are required, and statistical fluctuations and measurement noise are effectively averaged. The method is demonstrated for dual-phase steel, revealing subtle unexpected differences in the morphology surrounding damage in strongly and weakly banded microstructures.

References in corpus (1)

• Microstructural topology effects on the onset of ductile failure in multi-phase materials - a systematic computational approach

Cited by in corpus (4)

• Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials
• Martensite plasticity and damage competition in dual-phase steel: A micromechanical experimental-numerical study
• Competing damage mechanisms in a two-phase microstructure: how microstructure and loading conditions determine the onset of fracture
• Fracture initiation in multi-phase materials: a statistical characterization of microstructural damage sites