A Paradigm Shift to Assembly-like Finite Element Model Updating

2024-12-17

arXiv.org

AI Summary

Finite-element models of aircraft flexible wings often exhibit discrepancies with experimental measurements due to modeling inaccuracies and parameter uncertainties. Method: This paper proposes an *assembled model updating paradigm*, wherein submodels corresponding to physical components are updated incrementally during hierarchical structural assembly—replacing conventional global, one-shot updating. We introduce a novel framework integrating experimental data-driven calibration, modular substructure modeling, and surrogate-model acceleration. Contribution/Results: The approach preserves high modeling fidelity while significantly improving computational efficiency: experiments demonstrate a 20% reduction in iteration count versus global methods, fewer parameters to estimate, faster convergence, and comparable accuracy. Crucially, the method maintains physical interpretability through component-level updates and offers scalability for high-fidelity modeling of complex aerospace structures.

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• Machine Learning: Ensemble Methods
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Abstract

In general, there is a mismatch between a finite element model of a structure and its real behaviour. In aeronautics, this mismatch must be small because finite element models are a fundamental part of the development of an aircraft and of increasing importance with the trend to more flexible wings in modern designs. Finite element model updating can be computationally expensive for complex structures and surrogate models can be employed to reduce the computational burden. A novel approach for finite element model updating, namely assembly-like, is proposed and validated using real experimental data. The assembly-like model updating framework implies that the model is updated as parts are assembled. Benchmarking against the classical global, or one-shot, approach demonstrates that the proposed method is more computationally efficient since it takes 20% fewer iterations to obtain convergence, also using fewer parameters for the model evaluations. Despite the increase in computational performance, the new approach retains the fidelity of the global approach.

Problem

• Mismatch between finite element models and real behavior
• Computational expense in updating complex structural models
• Need for efficient model updating in aeronautics

Innovation

• Assembly-like finite element model updating
• Reduces computational burden with surrogate models
• 20% fewer iterations for convergence