Bayesian-Informed Fatigue Life Prediction for Shallow Shell Structures

• Autorzy: Zhuang Mengke , Larrosa Nicolas O. , Booker Julian D. , Truman Christopher E.

Identyfikatory

DOI

10.2478/fas-2024-0001

• Języki publikacji: EN

Abstrakty

EN

This study introduces a Bayesian-informed framework for fatigue life prediction in shallow shell structures. The methodology focuses on inferring the Equivalent Initial Flaw Size Distribution (EIFSD), a critical parameter for structural durability. Bayesian inference, combined with a Co-Kriging surrogate model, enables statistically robust predictions while accounting for uncertainties in material properties, geometry, and loading. The Dual Boundary Element Method (DBEM) is employed for crack propagation due to its efficiency and re-meshing-free modelling. To improve inference efficiency, an iterative parameter space narrowing strategy is proposed. Instead of exhaustively sampling the entire space, the method begins with coarse discretisation to locate high-probability EIFSD regions, then refines them adaptively. A numerical example involving a fuselage window under cabin pressure demonstrates the method. Surrogate models trained on DBEM-generated data significantly reduce computational cost. The proposed strategy achieves high-precision inference, with only 0.059% error in the inferred mean and 5.2% in standard deviation, while reducing CPU time by 52% compared to dense sampling.

Słowa kluczowe

EN

Shallow Shell Structure; Equivalent Initial Flaw Size; EIFS; Dual Boundary Element Method; DBEM; Bayesian inference; multi-fidelity model

• Wydawca: Wydawnictwa Naukowe Sieci Badawczej Łukasiewicz - Instytutu Lotnictwa
• Czasopismo: Fatigue of Aircraft Structures
• Rocznik: 2024
• Tom: Iss.16
• Strony: 1--15
• Opis fizyczny: Bibliogr. 28 poz., rys., tab., wykr., wzory

Twórcy

autor

Zhuang Mengke

• School of Electrical, Electronic and Mechanical Engineering, Queens Building, University of Bristol, BS8 1TR, Bristol, UK

• https://orcid.org/0000-0002-3098-5109

autor

Larrosa Nicolas O.

• School of Electrical, Electronic and Mechanical Engineering, Queens Building, University of Bristol, BS8 1TR, Bristol, UK

• https://orcid.org/0000-0001-7515-4504

autor

Booker Julian D.

• School of Electrical, Electronic and Mechanical Engineering, Queens Building, University of Bristol, BS8 1TR, Bristol, UK

• https://orcid.org/0000-0002-5564-1724

autor

Truman Christopher E.

• School of Electrical, Electronic and Mechanical Engineering, Queens Building, University of Bristol, BS8 1TR, Bristol, UK

• https://orcid.org/0000-0003-0174-1276

Bibliografia

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Uwagi

1. This article was presented at the 32nd Symposium of ICAF https://www.icaf2025.com/

2. This paper presents work undertaken as part of the “Advanced Landing Gear” project supported by Safran Landing Systems. The research was funded through the Aerospace Technology Institute (ATI), under application number: 10079975, as part of the ATI programme: Batch 40 research projects.