Probability analysis of vertical drainage improvement for soft soil settlement prediction via a Bayesian back analysis framework and the simplified Hypothesis B method
The time-dependent settlement of soft soils is one of the key problems in geotechnical engineering. Using Bayesian back analysis, this study examined the probability of settlement of the Ballina embankment in Australia. As random variables, the primary compression index (Cc), swelling index (Cs), an...
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| Language: | English |
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Tsinghua University Press
2025-01-01
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| Series: | Journal of Intelligent Construction |
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| Online Access: | https://www.sciopen.com/article/10.26599/JIC.2025.9180077 |
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| author | Shijie Zhai Guangyin Du Tao Peng Yuxiao Wang Zhiheng Shang |
| author_facet | Shijie Zhai Guangyin Du Tao Peng Yuxiao Wang Zhiheng Shang |
| author_sort | Shijie Zhai |
| collection | DOAJ |
| description | The time-dependent settlement of soft soils is one of the key problems in geotechnical engineering. Using Bayesian back analysis, this study examined the probability of settlement of the Ballina embankment in Australia. As random variables, the primary compression index (Cc), swelling index (Cs), and secondary compression index (Cα) were examined for their influence on the settlement probability distribution. To generate compression index samples, Markov chain Monte Carlo simulation (MCMCS) was used, and the predicted settlement samples were derived from the compression index samples. Consequently, the predicted settlement samples can be used for probability analysis. A comparison between the field settlement data and the predicted settlement data reveals that the 90% confidence interval of the predicted settlement data is in reasonable agreement with the field settlement monitoring data. With the incorporation of more monitored settlement data into the Bayesian framework, the distribution of the predicted settlement shifts from the Weibull distribution to the normal distribution. In addition, the degree of uncertainty in the prediction of settlement decreases with the amount of data incorporated into the model. Additionally, the small amount of data used in the Bayesian framework can lead to underestimations of failure probability. |
| format | Article |
| id | doaj-art-b6ff8208952543a9981d40cbc5cffb06 |
| institution | DOAJ |
| issn | 2958-3861 2958-2652 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Journal of Intelligent Construction |
| spelling | doaj-art-b6ff8208952543a9981d40cbc5cffb062025-08-20T02:56:44ZengTsinghua University PressJournal of Intelligent Construction2958-38612958-26522025-01-0131918007710.26599/JIC.2025.9180077Probability analysis of vertical drainage improvement for soft soil settlement prediction via a Bayesian back analysis framework and the simplified Hypothesis B methodShijie Zhai0Guangyin Du1Tao Peng2Yuxiao Wang3Zhiheng Shang4Institute of Geotechnical Engineering of SEU., School of Transportation, Southeast University, Nanjing 211189, ChinaInstitute of Geotechnical Engineering of SEU., School of Transportation, Southeast University, Nanjing 211189, ChinaJSTI Group, Nanjing 210019, ChinaInstitute of Geotechnical Engineering of SEU., School of Transportation, Southeast University, Nanjing 211189, ChinaInstitute of Geotechnical Engineering of SEU., School of Transportation, Southeast University, Nanjing 211189, ChinaThe time-dependent settlement of soft soils is one of the key problems in geotechnical engineering. Using Bayesian back analysis, this study examined the probability of settlement of the Ballina embankment in Australia. As random variables, the primary compression index (Cc), swelling index (Cs), and secondary compression index (Cα) were examined for their influence on the settlement probability distribution. To generate compression index samples, Markov chain Monte Carlo simulation (MCMCS) was used, and the predicted settlement samples were derived from the compression index samples. Consequently, the predicted settlement samples can be used for probability analysis. A comparison between the field settlement data and the predicted settlement data reveals that the 90% confidence interval of the predicted settlement data is in reasonable agreement with the field settlement monitoring data. With the incorporation of more monitored settlement data into the Bayesian framework, the distribution of the predicted settlement shifts from the Weibull distribution to the normal distribution. In addition, the degree of uncertainty in the prediction of settlement decreases with the amount of data incorporated into the model. Additionally, the small amount of data used in the Bayesian framework can lead to underestimations of failure probability.https://www.sciopen.com/article/10.26599/JIC.2025.9180077time-dependent settlementprobabilistic analysissettlement predictionbayesian back analysis |
| spellingShingle | Shijie Zhai Guangyin Du Tao Peng Yuxiao Wang Zhiheng Shang Probability analysis of vertical drainage improvement for soft soil settlement prediction via a Bayesian back analysis framework and the simplified Hypothesis B method Journal of Intelligent Construction time-dependent settlement probabilistic analysis settlement prediction bayesian back analysis |
| title | Probability analysis of vertical drainage improvement for soft soil settlement prediction via a Bayesian back analysis framework and the simplified Hypothesis B method |
| title_full | Probability analysis of vertical drainage improvement for soft soil settlement prediction via a Bayesian back analysis framework and the simplified Hypothesis B method |
| title_fullStr | Probability analysis of vertical drainage improvement for soft soil settlement prediction via a Bayesian back analysis framework and the simplified Hypothesis B method |
| title_full_unstemmed | Probability analysis of vertical drainage improvement for soft soil settlement prediction via a Bayesian back analysis framework and the simplified Hypothesis B method |
| title_short | Probability analysis of vertical drainage improvement for soft soil settlement prediction via a Bayesian back analysis framework and the simplified Hypothesis B method |
| title_sort | probability analysis of vertical drainage improvement for soft soil settlement prediction via a bayesian back analysis framework and the simplified hypothesis b method |
| topic | time-dependent settlement probabilistic analysis settlement prediction bayesian back analysis |
| url | https://www.sciopen.com/article/10.26599/JIC.2025.9180077 |
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