A finite element model updating method based on global optimization

TL;DR

This paper introduces a global optimization-based finite element model updating method that effectively finds the best parameters by minimizing discrepancies between experimental and numerical dynamic data, validated through simulations and real case studies.

Contribution

It presents a novel numerical method capable of reliably locating the global minimum in finite element model updating, addressing issues of local minima and validation with real-world data.

Findings

Successfully tested on simulated examples of a masonry tower and a domed temple.

Validated against a genetic algorithm and sensitivity analysis tools.

Applied to a real structure to estimate material properties from operational data.

Abstract

Finite element model updating of a structure made of linear elastic materials is based on the solution of a minimization problem. The goal is to find some unknown parameters of the finite element model (elastic moduli, mass densities, constraints and boundary conditions) that minimize an objective function which evaluates the discrepancy between experimental and numerical dynamic properties. The objective function depends nonlinearly on the parameters and may have multiple local minimum points. This paper presents a numerical method able to find a global minimum point and assess its reliability. The numerical method has been tested on two simulated examples - a masonry tower and a domed temple - and validated via a generic genetic algorithm and a global sensitivity analysis tool. A real case study monitored under operational conditions has also been addressed, and the structure's experimental modal properties have been used in the model updating procedure to estimate the mechanical properties of its constituent materials.