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Research Article
Oct 3, 2022

Establishment of the Off-Center Embedded Crack Stress Intensity Factor Database for Probabilistic Risk Assessment Based on Universal Weight Function

Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Volume 9, Issue 2

Abstract

Probabilistic failure risk analysis is frequently used in the airworthiness area, while efficient stress intensity factor (SIF) solutions are vital in its process. Universal weight function (UWF) is a method that has remarkable computational efficiency and high accuracy in SIF calculation. However, the concrete coefficients in the UWF for different geometries remain unknown, which hinders the subsequent application of the method. This article focuses on general off-center embedded cracks. The response surface method is used to construct the UWF database. The accuracy of the database is confirmed by comparing it with existing literature and the finite element method, although large errors are identified to be inevitable for certain stress. Gaussian process regression is further adopted for better fitting, and the R-square is over 0.96. In addition, the effect of the offset distance on SIFs is discussed for embedded cracks in a given plate. Results show that SIF changes are dependent on the plate boundary in the uniform stress field, while stress predominates the SIF changes in nonuniform stress fields. This article is available in the ASME Digital Collection at https://doi.org/10.1115/1.4055535.

Information & Authors

Information

Published In

Go to ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Volume 9Issue 2June 2023

History

Received: May 11, 2022
Revision received: Aug 31, 2022
Published online: Oct 3, 2022
Published in print: Jun 1, 2023

Authors

Affiliations

Aircraft/Engine Integrated System Safety Beijing Key Laboratory, School of Energy and Power Engineering, Beihang University, Beijing 100191, China e-mail: [email protected]
Shuiting Ding [email protected]
Professor Aircraft/Engine Integrated System Safety Beijing Key Laboratory, School of Energy and Power Engineering, Beihang University, Beijing 100191, China e-mail: [email protected]
Huimin Zhou [email protected]
Aircraft/Engine Integrated System Safety Beijing Key Laboratory, School of Energy and Power Engineering, Beihang University, Beijing 100191, China e-mail: [email protected]
Professor Aircraft/Engine Integrated System Safety Beijing Key Laboratory, School of Energy and Power Engineering, Beihang University, Beijing 100191, China e-mail: [email protected]

Funding Information

National Natural Science Foundation of China10.13039/501100001809: U1833109

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Cited by

  • Crack Detection via Hierarchical Multiscale Feature Learning and Densely Connected Conditional Random Field, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10.1061/AJRUA6.RUENG-1102, 10, 1, (2024).

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