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| Reliability analysis of slopes from sparse measurements considering sites similarity |
| XU Ling，WANG Wenlong，ZHAO Tengyuan |
| (School of Human Settlements and Civil Engineering，Xi?an Jiaotong University，Xi?an，Shaanxi 710000，China) |
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Abstract This paper proposes a hierarchical Bayesian method(HBM) with MCMC to address the challenges of large uncertainty in geotechnical statistics，inaccurate probability distribution of geotechnical properties，and unreasonable reliability analysis of slopes due to limited geotechnical experimental data. The HBM effectively integrates measurements from multiple similar geotechnical sites and combines them with the limited measurements at the target site. This integration allows for a reasonable characterization of the probability distribution of geotechnical parameters for the target site under small sample conditions. The effectiveness of the proposed method is validated using real datasets from several loess sites in the northern Shaanxi Province，China. Furthermore，a reliability analysis of a loess slope is conducted to demonstrate the practical application of the HBM. The results indicate that the proposed HBM significantly reduces the failure probability of the loess slope from 11.6% to 4.8%. Additionally，a comprehensive set of numerical examples is used to explore and verify the accuracy of the HBM compared to traditional methods. The results show that the HBM improves the accuracy of geotechnical statistics by 33% to 53% and reduces uncertainty by approximately 19% to 53% compared to conventional Bayesian methods that do not fully utilize the information from multiple similar geotechnical sites.
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