.png){kind=icon}
返回
A probabilistic-based airframe integrity management model
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ress.2008.10.010.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper proposes a lognormal distribution model to relate crack-length distribution to fatigue damage accumulated in aging airframes. The fatigue damage is expressed as fatigue life expended (FLE) and is calculated using the strain-life method and Miner's rule. A two-stage Bayesian updating procedure is constructed to determine the unknown parameters in the proposed semi-empirical model of crack length versus FILE. At the first stage of the Bayesian updating, the crack closure model is used to simulate the crack growth based upon generic but uncertain physical properties. The simulated crack-growth results are then used as data to update the uninformative prior distributions of the unknown parameters of the proposed semi-empirical model. At the second stage of the Bayesian updating, the crack-length data collected from field inspections are used as evidence to further update the posteriors from the first stage of the Bayesian updating. Two approaches are proposed to build the crack-length distribution for the fleet based on individual posterior crack distribution of each aircraft. The proposed distribution model of the crack length can be used to analyze the reliability of aging airframes by predicting, for instance, the probability that a crack will reach an unacceptable length after additional flight hours. (C) 2008 Elsevier Ltd. All rights reserved.
Keyword:
Airframe reliability
Aging aircraft
Physics of failure
Fatigue
Life prediction
Health management
Prognostics
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
R
IF:
11
论文数:
9.0K
被引数:
4.2W
机构
引用论文
.png){kind=icon}
Children's orthographic representations and linguistic transparency: Nonsense word reading in English, French, and Spanish儿童的正字法表示和语言透明度: 英语，法语和西班牙语的无意义单词阅读
PREAI
分享收藏
分享收藏 没有更多内容
没有更多内容