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Probabilistic Models for Reliability Analysis Using Safe-Life and Damage Tolerance Methods

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Springer Handbook of Engineering Statistics

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Abstract

The chapter presents a systematical method for probabilistic analysis using safe-life and damage tolerance models. In particular, the reliability analysis incorporating those models are developed to provide a basic framework for the life prediction given risk constraints and the time-dependent probability of failure estimation. First, the probabilistic modeling is presented, and the uncertainties from model prediction and data are considered. The uncertainties are quantified and are encoded in the probability density functions of model parameters using probabilistic parameter estimation. The propagation of the characterized uncertainties to the result of quantity of interest can be obtained using probabilistic prediction. Next, the reliability model based on the probabilistic modeling is introduced, where the safe-life model and the damage tolerance model are discussed in detail. The life prediction given a certain risk constraint and the time-dependent probability of failure estimation can be made using the developed method. Two examples are employed to demonstrate the overall method.

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Authors and Affiliations

  1. Graduate School of China Academy of Engineering Physics, Beijing, China

    Xuefei Guan

  2. School of Reliability and Systems Engineering, Beihang University, Beijing, China

    Jingjing He

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  1. Xuefei Guan
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  2. Jingjing He
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Correspondence to Xuefei Guan .

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Editors and Affiliations

  1. Department of Industrial & Systems Engineering, Rutgers University, Piscataway, NJ, USA

    Hoang Pham

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    Guan, X., He, J. (2023). Probabilistic Models for Reliability Analysis Using Safe-Life and Damage Tolerance Methods. In: Pham, H. (eds) Springer Handbook of Engineering Statistics. Springer Handbooks. Springer, London. https://doi.org/10.1007/978-1-4471-7503-2_48

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