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Published in:
2025 | OriginalPaper | Chapter
Application of an Efficient Bayesian Back Analysis Framework for Settlement Prediction of Soft Soils: A Case Study
Authors : Shan Huang, Jinsong Huang, Richard Kelly, Merrick Jones, A. H. M. Kamruzzaman
Published in: Proceedings of the 5th International Conference on Transportation Geotechnics (ICTG) 2024, Volume 6
Publisher: Springer Nature Singapore
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Abstract
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.