A surrogate model to accelerate non-intrusive global–local simulations of cracked steel structures

Abstract

Physics-based digital twins often require many computations to diagnose current and predict future damage states in structures. This research proposes a novel iterative global–local method, where the local numerical model is replaced with a surrogate to simulate cracking quickly on large steel structures. The iterative global–local method bridges the scales from the operational level of a large steel structure to that of a cracked component. The linear global domain is efficiently simulated using static condensation, and the cracked local domain is quickly simulated using the adaptive surrogate modeling method proposed herein. This work compares solution time and accuracy of the proposed surrogate iterative global–local method with a reference model, a submodeling model, and an iterative global–local method with no surrogate model for the local domain. It is found that the surrogate iterative global–local method gives the fastest solution time with comparatively accurate results.

Diagnostics and prognostics of multi-mode failure scenarios in miter gates using multiple data sources and a dynamic Bayesian network

“…The feature of interest is the crack, which is only explicitly represented in the solid area of the local model. More detailed IGL implementation information may be found in Fillmore et al (2022). For any given l i , ∆s i , and a i , the SIF value may be obtained.…”