基于疲劳损伤诊断和预报的考虑疲劳裂纹扩展的飞机结构风险评估方法

IF 5.7 2区 材料科学 Q1 ENGINEERING, MECHANICAL International Journal of Fatigue Pub Date : 2024-10-13 DOI:10.1016/j.ijfatigue.2024.108650
Liang Han , Xiaofan He , Yu Ning , Yanjun Zhang , Yan Zhou
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引用次数: 0

摘要

考虑到疲劳裂纹的扩展,开发了一种基于疲劳损伤诊断和预报的飞机结构风险评估方法。该过程分为三个阶段:初始裂纹诊断、裂纹诊断和预测,采用蒙特卡罗模拟法。研究使用带中心孔的 2024 铝合金试样,结果表明,在初始裂纹诊断阶段,单次飞行失效概率(SFPOF)小于 10-7 的检测标准和阈值法可增强结构疲劳裂纹诊断。在裂纹诊断和预测阶段,使用动态贝叶斯网络(DBN)中的高斯过程回归(GPR)进行迭代更新,可提高裂纹扩展预测和风险评估的准确性。诊断时间间隔对 SFPOF 有重大影响,优化的时间间隔可在精度和计算时间之间取得平衡。简化而精确的 K 值计算方法提高了效率和准确性。该方法降低了成本,提高了风险评估的准确性,为基于 SPHM 的飞机结构风险评估提供了新的见解。
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An aircraft structural risk assessment method considering fatigue crack propagation based on fatigue damage diagnosis and prognosis
An aircraft structural risk assessment method based on fatigue damage diagnosis and prognosis has been developed, considering fatigue crack propagation. The process is divided into three stages: initial crack diagnosis, crack diagnosis, and prediction, utilizing Monte Carlo simulation. Using 2024 aluminum alloy specimens with central holes, the study indicates that in the initial crack diagnosis stage, an inspection standard with a Single Flight Probability of Failure (SFPOF) less than 10-7 and a threshold method enhances structural fatigue crack diagnosis. In the crack diagnosis and prediction stages, iterative updates using Gaussian Process Regression (GPR) within a Dynamic Bayesian Network (DBN) improve crack propagation prediction and risk assessment accuracy. The diagnostic interval significantly impacts SFPOF, with an optimized interval balancing accuracy and computation time. Simplified and precise K value calculation methods enhance efficiency and accuracy. The method reduces costs and improves risk assessment accuracy, providing new insights for SPHM-based aircraft structural risk assessment.
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来源期刊
International Journal of Fatigue
International Journal of Fatigue 工程技术-材料科学:综合
CiteScore
10.70
自引率
21.70%
发文量
619
审稿时长
58 days
期刊介绍: Typical subjects discussed in International Journal of Fatigue address: Novel fatigue testing and characterization methods (new kinds of fatigue tests, critical evaluation of existing methods, in situ measurement of fatigue degradation, non-contact field measurements) Multiaxial fatigue and complex loading effects of materials and structures, exploring state-of-the-art concepts in degradation under cyclic loading Fatigue in the very high cycle regime, including failure mode transitions from surface to subsurface, effects of surface treatment, processing, and loading conditions Modeling (including degradation processes and related driving forces, multiscale/multi-resolution methods, computational hierarchical and concurrent methods for coupled component and material responses, novel methods for notch root analysis, fracture mechanics, damage mechanics, crack growth kinetics, life prediction and durability, and prediction of stochastic fatigue behavior reflecting microstructure and service conditions) Models for early stages of fatigue crack formation and growth that explicitly consider microstructure and relevant materials science aspects Understanding the influence or manufacturing and processing route on fatigue degradation, and embedding this understanding in more predictive schemes for mitigation and design against fatigue Prognosis and damage state awareness (including sensors, monitoring, methodology, interactive control, accelerated methods, data interpretation) Applications of technologies associated with fatigue and their implications for structural integrity and reliability. This includes issues related to design, operation and maintenance, i.e., life cycle engineering Smart materials and structures that can sense and mitigate fatigue degradation Fatigue of devices and structures at small scales, including effects of process route and surfaces/interfaces.
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