A digital twin feasibility study (Part I): Non-deterministic predictions of fatigue life in aluminum alloy 7075-T651 using a microstructure-based multi-scale model

Abstract

The Digital Twin (DT) concept has the potential to revolutionize the way systems and their components are designed, managed, maintained, and operated across a vast number of fields from engineering to healthcare. The focus of this work is the implementation of DT for the health management of fatigue critical structures. This paper is the first part of a two-part series. The second part focuses on the use of in-situ diagnostics to reduce uncertainty in fatigue life predictions once a life-limiting fatigue crack has reached the point where it is observable. In contrast, the focus of this work is to form a non-deterministic prediction of fatigue life prior to the accumulation of observable damage, a condition that often dominates the majority of a component or system’s lifetime. This predictive capability is enabled by a DT framework that simulates crack growth from initiation to failure using microstructure-based, multi-scale modeling. Two models are used in this work, one that incorporates microstructure explicitly and one that uses more traditional linear elastic fracture mechanics. The models are joined by a transition crack length between the micro- and macroscales, which facilitates both the coupling of fatigue life predictions and the transference of uncertainty across scales. The ability to predict fatigue life under uncertainty and across scales is demonstrated in the context of a geometrically complex, metallic test specimen subjected to uniaxial fatigue loading. Conclusions are drawn regarding the feasibility of the approach as a DT-based health management method.