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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    Titel :

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


    Weitere Titelangaben:

    Lecture Notes in Civil Engineering


    Beteiligte:
    Rujikiatkamjorn, Cholachat (Herausgeber:in) / Xue, Jianfeng (Herausgeber:in) / Indraratna, Buddhima (Herausgeber:in) / Huang, Shan (Autor:in) / Huang, Jinsong (Autor:in) / Kelly, Richard (Autor:in) / Jones, Merrick (Autor:in) / Kamruzzaman, A. H. M. (Autor:in)

    Kongress:

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



    Erscheinungsdatum :

    18.10.2024


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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