Detection of the onset of yielding and creep failure from digital image correlation

TL;DR

This paper introduces an equation-free PCA-based method to detect yielding and creep failure from digital image correlation strain fields, enabling nondestructive, continuous assessment of structural materials.

Contribution

The study presents a novel PCA-based approach for identifying yielding and creep onset directly from strain fields without requiring equations, validated on multiple polycrystalline materials.

Findings

Successfully detects yielding in Ni-based Haynes 230 alloy.

Identifies tertiary creep onset in fiber composites.

Applicable to various materials and deformation modes.

Abstract

There are a multitude of applications in which structural materials would be desired to be nondestructively evaluated, while in a component, for plasticity and failure characteristics. In this way, safety and resilience features can be significantly improved. Nevertheless, while failure can be visible through cracks, plasticity is commonly invisible and highly microstructure-dependent. Here, we show that an equation-free method based on principal component analysis is capable of detecting yielding and tertiary creep onset, directly from strain fields that are obtained by digital image correlation, applicable on components, continuously and nondestructively. We demonstrate the applicability of the method to yielding of Ni-based Haynes 230 metal alloy polycrystalline samples, which are also characterized through electron microscopy and benchmarked using continuum polycrystalline plasticity modeling. Also, we successfully apply this method to yielding during uniaxial tension of Hastelloy X polycrystalline samples, and also to the onset of tertiary creep in quasibrittle fiber composites under uniaxial tension. We conclude that there are key features in the spatiotemporal fluctuations of local strain fields that can be used to infer mechanical properties.