Buckling reliability and sensitivity analysis of a composite stiffened panel with high-dimensional uncertainties

This paper presents an uncertainty analysis of composite stiffened panels with high-dimensional input parameters, encompassing reliability assessment and sensitivity analysis. Initially, a finite element model is developed. Subsequently, the uncertain parameters influencing the mechanical properties of the stiffened panels are identified, and finite element simulations are conducted. Following the simulation, various surrogate models are established and compared for accuracy, with results indicating that the high-dimensional surrogate model KDIC exhibits superior fitting accuracy. Finally, the probability of failure is computed, and a local sensitivity analysis (LSA) is performed to evaluate the influence of the input parameters.

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Publication Details

Journal
IET conference proceedings.
Published
2025-01-01
DOI
https://doi.org/10.1049/icp.2024.3447
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
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article

Buckling reliability and sensitivity analysis of a composite stiffened panel with high-dimensional uncertainties

Xufeng Yang, Junyi Zhao, Wenke Jiang
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IET conference proceedings.
Probabilistic and Robust Engineering Design
article

Buckling reliability and sensitivity analysis of a composite stiffened panel with high-dimensional uncertainties

Xufeng Yang, Junyi Zhao, Wenke Jiang
article en

Abstract

This paper presents an uncertainty analysis of composite stiffened panels with high-dimensional input parameters, encompassing reliability assessment and sensitivity analysis. Initially, a finite element model is developed. Subsequently, the uncertain parameters influencing the mechanical properties of the stiffened panels are identified, and finite element simulations are conducted. Following the simulation, various surrogate models are established and compared for accuracy, with results indicating that the high-dimensional surrogate model KDIC exhibits superior fitting accuracy. Finally, the probability of failure is computed, and a local sensitivity analysis (LSA) is performed to evaluate the influence of the input parameters.

IET conference proceedings.Vol. 2024(12)
Southwest Jiaotong University (CN)
Climate action
Openalex Percentile: Top 99%
Probabilistic and Robust Engineering Design
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