A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
This paper presents a Bayesian approach to determine characteristic values of the undrained shear strength Su profile for geotechnical analysis and design, particularly those using probability-based design codes. The approach integrates systematically the prior knowledge (e.g., engineering judgment/local experience) and a limited number of project-specific liquidity index (LI) data under a Bayesian framework and transforms the integrated information into a large number, as many as needed, of equivalent samples of the Su profile using Markov Chain Monte Carlo simulation (MCMCS). Then, conventional statistical analysis is carried out to estimate statistics of the Su profile, and the characteristic values of the Su profile is determined accordingly. Equations are derived for the proposed Bayesian approach, and the approach is illustrated through a set of real-life data. It is shown that the approach effectively tackles the difficulty in generating meaningful statistics and probability distributions of soil properties from a usually limited number of soil property data obtained during geotechnical site investigation.
This paper presents a Bayesian approach to determine characteristic values of the undrained shear strength Su profile for geotechnical analysis and design, particularly those using probability-based design codes. The approach integrates systematically the prior knowledge (e.g., engineering judgment/local experience) and a limited number of project-specific liquidity index (LI) data under a Bayesian framework and transforms the integrated information into a large number, as many as needed, of equivalent samples of the Su profile using Markov Chain Monte Carlo simulation (MCMCS). Then, conventional statistical analysis is carried out to estimate statistics of the Su profile, and the characteristic values of the Su profile is determined accordingly. Equations are derived for the proposed Bayesian approach, and the approach is illustrated through a set of real-life data. It is shown that the approach effectively tackles the difficulty in generating meaningful statistics and probability distributions of soil properties from a usually limited number of soil property data obtained during geotechnical site investigation.
Determination of Undrained Shear Strength Characteristic Values
Second International Conference on Vulnerability and Risk Analysis and Management (ICVRAM) and the Sixth International Symposium on Uncertainty, Modeling, and Analysis (ISUMA) ; 2014 ; Liverpool, UK
Vulnerability, Uncertainty, and Risk ; 2370-2379
2014-06-27
Conference paper
Electronic Resource
English
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