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Bayesian probabilistic characterization of the shear-wave velocity combining the cone penetration test and standard penetration test

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Abstract

The shear-wave velocity \({V}_{S}\) a crucial parameter for determining small-strain soil stiffness characteristics and site classification. However, directly measuring \({V}_{S}\) in the field can be challenging, and requires specific equipment. As a result, researchers have conducted numerous studies on \({V}_{S}\) correlation, and extensive research has demonstrated that the results from cone penetration test (CPT) and standard penetration test (SPT) data are strongly related to the shear-wave velocity. Due to the uncertainty of the transformation model, the accuracy of the \({V}_{S}\) derived from the empirical equations are unsatisfactory. The purpose of the present paper is to propose a Bayesian framework for determining the probabilistic characteristics of \({V}_{S}\) while considering the transformation uncertainty. The Bayesian framework considers both the in-situ test data (SPT, CPT) and prior information, and the results show that the framework considering two in-situ tests accurately predicts the shear-wave velocity. There are several advantages of using the Bayesian method described in this study: (1) The Bayesian framework incorporates both the inherent uncertainty of the shear-wave velocity and the transformation uncertainty. (2) Prior information and field data can be combined to improve the accuracy of predictions. (3) In the framework, the statistical characteristics of \({V}_{S}\) can be ascertained from small samples of field test data.

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Data availability statements

The datasets generated during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors gratefully acknowledge the financial support from National Natural Science Foundation of China (Grant Nos. 42277153, 41977241 and 52008098) and the Natural Science Foundation of Jiangsu Province (Grant No. BK20200405). The authors would like to express their appreciations to the editors and anonymous reviewers for their valuable comments and suggestions.

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Authors and Affiliations

  1. Institute of Geotechnical Engineering, School of Transportation, Southeast University, Nanjing, Jiangsu, China

    Shijie Zhai, Guangyin Du & Huan He

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  1. Shijie Zhai
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  2. Guangyin Du
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Shijie Zhai and Guanyin Du wrote the main manuscript text. Huan He was responsible for the language changes.

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Correspondence to Guangyin Du.

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Zhai, S., Du, G. & He, H. Bayesian probabilistic characterization of the shear-wave velocity combining the cone penetration test and standard penetration test. Stoch Environ Res Risk Assess 38, 69–84 (2024). https://doi.org/10.1007/s00477-023-02566-2

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