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Fatigue damage analysis: Issues and challenges

delete2016-01-01
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A.K. Vasudévan *
K
K. Sadananda
DOI:10.1016/j.ijfatigue.2015.08.026delete
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摘要

摘要

En 中文
During service loading of a vehicle (like an airplane), small cracks nucleate and eventually grow into large cracks, leading to structural damage that will threaten the safety of the vehicle. Managing safety is expensive. As a result, the goal is to provide a performance criteria that can be used as a tool by the designer to incorporate reliability in the component design. These performance criteria come from material selection and design. Since 50 years, there have been multiple efforts to develop fatigue damage life prediction modeling methods. Unfortunately, most of these models are empirical and require adjustable parameters. With respect to crack growth models, most are based on a single crack driving force Delta K. Our goal was to derive a predictive model capability that takes into account various type of structural materials, under service loads and environment. The initial approach was to redefine the physics of crack growth evolution in terms of two crack driving forces Delta K and K-max, along with their respective thresholds, instead of one Delta K. This method of describing fatigue damage minimizes the deficiencies in the earlier descriptive models. This article gives a brief account of the development of this crack growth model. We have added some newer data on environmental damage with physical explanations. In addition, a brief account of the crack nucleation is described. The following discussion lists the key issues about the existing damage philosophies (safe life vs damage tolerant) and describes a reliably correct life prediction model to address the challenges. (C) 2015 Elsevier Ltd. All rights reserved.
Keyword:
History of early life models
Environment classification
Aluminum and steel alloys
Service data prediction
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期刊

International Journal of Fatigue 封面图
International Journal of Fatigue
IF:
6.8
论文数:
8.8K
被引数:
3.4W

机构

T
technical data analysis, inc.
学者数:
17
论文数: 24
被引数: 0
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