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Reliability Models Based on Experiments

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Experimental Stress Analysis for Materials and Structures

Part of the book series: Springer Series in Solid and Structural Mechanics ((SSSSM,volume 4))

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Abstract

An engineered system may be affected by several uncertainties, which can be classified as aleatory or epistemic ones. To be able to manage the effects of these uncertainties is nowadays more and more important, especially in those cases where an accident may have catastrophic effects and it is necessary to predict its probability of occurrence. This is the case, for instance, of life extension problems, where the final decision must be supported by a probabilistic approach, to make sure that the probability of a fatality is sufficiently low. Experimentation is of course also important, as it is the way to estimate or reduce the uncertainty affecting the studied system. This chapter tackles the aforementioned issues, from the estimation of statistical distributions, based on experimental data, to the adoption of a Most Probable Point Method to estimate the probability of failure of engineered systems, depending on several variables, in an efficient and accurate way. Theory is accompanied by several practical case studies and exercises taken from existing research, which confirm the strict relationship between the outcomes of experimental campaigns and the development of analytical models for probability of failure prediction.

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Authors and Affiliations

  1. Department of Industrial Engineering, University of Bologna, Bologna, Italy

    Giorgio Olmi

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  1. Giorgio Olmi
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Correspondence to Giorgio Olmi .

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Olmi, G. (2015). Reliability Models Based on Experiments. In: Experimental Stress Analysis for Materials and Structures. Springer Series in Solid and Structural Mechanics, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-319-06086-6_11

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  • DOI: https://doi.org/10.1007/978-3-319-06086-6_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06085-9

  • Online ISBN: 978-3-319-06086-6

  • eBook Packages: EngineeringEngineering (R0)

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