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Parameter estimation of Gumbel distribution and its application to pitting corrosion depth of concrete girder bridges

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Abstract

Taking pitting corrosion depth uncertainty into account is key to approach durability analysis of concrete girder bridges in a probabilistic way. The Gumbel distribution has been widely used to represent the probability distribution of pitting corrosion depth. In this study, Bayesian Quantile method was used to estimate the parameters of the Gumbel distribution. The proposed method was also compared with the commonly used maximum likelihood method via an extensive numerical simulation and two real pitting corrosion depth data examples based on performance measures such as, K–S test, RMSE, and R2. The numerical study reveals that the Bayesian Quantile method is suitable for estimating the parameters of the Gumbel distribution. Statistical analysis of real pitting corrosion depth data sets are presented to demonstrate the applicability and the conclusion of the simulation results.

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Acknowledgements

This work presented herein has been supported by the National Natural Science Foundation of China under grant number 51278064 and the Science and Technology Plan Project of Henan Provincial Department of Transportation (2013K30). These supports are gratefully acknowledged. The valuable comments of the anonymous reviewers of the paper are also acknowledged.

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Authors and Affiliations

  1. Highway College, Chang’an University, Xi’an, 710064, China

    Pingming Huang & Feng Hu

  2. Henan Transportation Research Institute Co., Ltd, Zhengzhou, 450006, China

    Feng Hu

  3. Department of Bridge Engineering, Tongji University, Shanghai, 200092, China

    Fenghui Dong

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  1. Pingming Huang
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  2. Feng Hu
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  3. Fenghui Dong
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Correspondence to Fenghui Dong.

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Huang, P., Hu, F. & Dong, F. Parameter estimation of Gumbel distribution and its application to pitting corrosion depth of concrete girder bridges. Cluster Comput 22 (Suppl 2), 3405–3411 (2019). https://doi.org/10.1007/s10586-018-2187-y

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  • DOI: https://doi.org/10.1007/s10586-018-2187-y

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