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Bayesian probabilistic characterization of consolidation behavior of clays using CPTU data
https://orcid.org/http://orcid.org/0000-0002-5223-2124
The coefficient of consolidation (ch) of clay interpreted based on piezocone penetration test (CPTU) usually deviates from the actual values. This can be due to the inherent variability of ch, model uncertainty in the CPTU-based interpretation model, and test errors. Considering the importance of ch in designing the structures over clays, Bayesian inference approach combined with total probability theorem was proposed in this study to integrate the prior knowledge of ch with the project-specific test data to obtain the site-specific distributions of ch. Subsequently, a large number of equivalent samples were generated from the updated distributions of ch by Markov Chain Monte Carlo simulation. Then, Bayesian model comparison approach was developed to quantitatively compare the model proposed by Torstensson (model M1) with the model proposed by Teh and Houlsby (model M2). Finally, a sensitivity analysis was performed to study the effect of model uncertainty and data quantity on the updated distributions of ch. The results showed that model M2 was significantly better than model M1 after considering the rigidity index (Ir). The updated distributions of ch approximately exhibited the log-normal distribution, especially for model M2, which was less affected by the model uncertainty and data quantity than model M1. The proposed Bayesian approach in this study gives the updated distributions of ch from a limited number of test data and recommends model M2 for calculating ch.
Bayesian probabilistic characterization of consolidation behavior of clays using CPTU data
https://orcid.org/http://orcid.org/0000-0002-5223-2124
The coefficient of consolidation (ch) of clay interpreted based on piezocone penetration test (CPTU) usually deviates from the actual values. This can be due to the inherent variability of ch, model uncertainty in the CPTU-based interpretation model, and test errors. Considering the importance of ch in designing the structures over clays, Bayesian inference approach combined with total probability theorem was proposed in this study to integrate the prior knowledge of ch with the project-specific test data to obtain the site-specific distributions of ch. Subsequently, a large number of equivalent samples were generated from the updated distributions of ch by Markov Chain Monte Carlo simulation. Then, Bayesian model comparison approach was developed to quantitatively compare the model proposed by Torstensson (model M1) with the model proposed by Teh and Houlsby (model M2). Finally, a sensitivity analysis was performed to study the effect of model uncertainty and data quantity on the updated distributions of ch. The results showed that model M2 was significantly better than model M1 after considering the rigidity index (Ir). The updated distributions of ch approximately exhibited the log-normal distribution, especially for model M2, which was less affected by the model uncertainty and data quantity than model M1. The proposed Bayesian approach in this study gives the updated distributions of ch from a limited number of test data and recommends model M2 for calculating ch.
Bayesian probabilistic characterization of consolidation behavior of clays using CPTU data
https://orcid.org/http://orcid.org/0000-0002-5223-2124
The coefficient of consolidation (ch) of clay interpreted based on piezocone penetration test (CPTU) usually deviates from the actual values. This can be due to the inherent variability of ch, model uncertainty in the CPTU-based interpretation model, and test errors. Considering the importance of ch in designing the structures over clays, Bayesian inference approach combined with total probability theorem was proposed in this study to integrate the prior knowledge of ch with the project-specific test data to obtain the site-specific distributions of ch. Subsequently, a large number of equivalent samples were generated from the updated distributions of ch by Markov Chain Monte Carlo simulation. Then, Bayesian model comparison approach was developed to quantitatively compare the model proposed by Torstensson (model M1) with the model proposed by Teh and Houlsby (model M2). Finally, a sensitivity analysis was performed to study the effect of model uncertainty and data quantity on the updated distributions of ch. The results showed that model M2 was significantly better than model M1 after considering the rigidity index (Ir). The updated distributions of ch approximately exhibited the log-normal distribution, especially for model M2, which was less affected by the model uncertainty and data quantity than model M1. The proposed Bayesian approach in this study gives the updated distributions of ch from a limited number of test data and recommends model M2 for calculating ch.
Bayesian probabilistic characterization of consolidation behavior of clays using CPTU data
Acta Geotech.
Zhao, Zening (author) / Congress, Surya Sarat Chandra (author) / Cai, Guojun (author) / Duan, Wei (author)
Acta Geotechnica ; 17 ; 931-948
2022-03-01
18 pages
Article (Journal)
Electronic Resource
English
Coefficient of consolidation , CPTU , Bayesian theorem , Markov Chain Monte Carlo , Uncertainty Engineering , Geoengineering, Foundations, Hydraulics , Solid Mechanics , Geotechnical Engineering & Applied Earth Sciences , Soil Science & Conservation , Soft and Granular Matter, Complex Fluids and Microfluidics
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