This study aims to utilize a self-developed, high-efficient Bayesian back analysis framework to perform Class C prediction of the embankment constructed on soft soils. In this framework, the general simplified Hypothesis B method based on a one-dimensional elastic visco-plastic (1D EVP) model and bypassing the need to solve complicated partial differential equations, is applied to perform consolidation analysis. Also, a high-efficient sampling method, Bayesian updating with structural reliability method (BUS), is employed to solve the Bayesian back analysis problem. The Class C prediction of a trial embankment constructed at Ballina, New South Wales, Australia, is conducted using the monitoring surface settlement data. The obtained results demonstrate that the accurate long-term settlement prediction at surface can be obtained at early stages, which enables cost-effective outcomes.


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    Title :

    Application of an Efficient Bayesian Back Analysis Framework for Settlement Prediction of Soft Soils: A Case Study


    Additional title:

    Lecture Notes in Civil Engineering



    Conference:

    International Conference on Transportation Geotechnics ; 2024 ; Sydney, NSW, Australia November 20, 2024 - November 22, 2024



    Publication date :

    2024-10-18


    Size :

    9 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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