Efficient Class C prediction of PVD-improved soft clay settlements

IF 8.4 1区 工程技术 Q1 ENGINEERING, GEOLOGICAL Engineering Geology Pub Date : 2025-02-21 Epub Date: 2025-01-03 DOI:10.1016/j.enggeo.2024.107903
Shan Huang , Jinsong Huang , Richard Kelly , Merrick Jonse , Patrick Wong , Stanley Yuen , A.H.M. Kamruzzaman , Shui-Hua Jiang
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Abstract

Soft clays exhibit significant challenges in geotechnical engineering due to their low permeability, high compressibility, and susceptibility to settlement under applied loads. These geological factors pose unique difficulties in predicting long-term settlement accurately and efficiently, particularly through Class C prediction methods that involve iterative processes with complex numerical models. To address these challenges, this study presents an efficient approach for Class C prediction of long-term settlement in soft clays. This approach integrates Bayesian updating with structural reliability methods (BUS) and the general simplified Hypothesis B method which is a semi-analytical method based on one-dimensional elastic visco-plastic (1D EVP) model. Unlike previous research that used Response Surface Model (RSM) with polynomial function for consolidation evaluation, the proposed approach enhances both accuracy and performance consistency under varying conditions. Additionally, by leveraging analytical solutions instead of iterative small-time steps required by Finite Element Method (FEM) or Finite Difference Method (FDM), the computational efficiency is also enhanced. The effectiveness of the proposed approach is demonstrated through its application to an embankment improved with prefabricated vertical drain (PVD) in Ballina, New South Wales, Australia. Comparative analyses demonstrate that the predicted settlements from this study, using only the monitoring settlement data collected prior to the 76th day of the project, align closely with the results from established RSM and FEM-based Bayesian back analysis approaches. The obtained results also indicate that the predicted settlements, based on 76 days of monitoring data, closely match field measurements at various depths, whether relying solely on settlement data or integrating additional pore water pressure data. For the Ballina embankment, over 40,000 consolidation analyses required for a single BUS simulation can be completed within 10 h using the general simplified Hypothesis B method, compared to months it might take with FEM or FDM approaches. This makes the proposed approach a practical tool for geotechnical engineers, enabling reliable settlement predictions early in the project timeline while maintaining low computational costs.
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有效的C类预测PVD-improved软粘土定居点
软粘土由于其低渗透性、高压缩性和在外加荷载下易沉降,在岩土工程中表现出重大挑战。这些地质因素给准确有效地预测长期沉降带来了独特的困难,特别是通过涉及复杂数值模型的迭代过程的C类预测方法。为了解决这些问题,本研究提出了一种有效的软粘土长期沉降C类预测方法。该方法将贝叶斯更新与结构可靠性方法(BUS)和基于一维弹性粘塑性(1D EVP)模型的半解析方法一般简化假设B方法相结合。与以往使用多项式函数响应面模型(RSM)进行固结评价不同,该方法在不同条件下提高了精度和性能一致性。此外,通过利用解析解而不是有限元法(FEM)或有限差分法(FDM)所需的迭代小时间步骤,计算效率也得到了提高。通过将该方法应用于澳大利亚新南威尔士州Ballina预制垂直排水管(PVD)改良的路堤,证明了该方法的有效性。对比分析表明,仅使用项目第76天之前收集的监测沉降数据,本研究预测的沉降与已建立的RSM和基于fem的贝叶斯反分析方法的结果非常吻合。结果还表明,无论是单纯依靠沉降数据还是综合孔隙水压力数据,基于76天监测数据的沉降预测结果与不同深度的现场实测结果吻合较好。对于Ballina路堤,使用一般的简化假设B方法可以在10小时内完成单个BUS模拟所需的40,000多个固结分析,而FEM或FDM方法可能需要数月时间。这使得所提出的方法成为岩土工程工程师的实用工具,在保持较低计算成本的同时,在项目时间表的早期实现可靠的沉降预测。
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来源期刊
Engineering Geology
Engineering Geology 地学-地球科学综合
CiteScore
13.70
自引率
12.20%
发文量
327
审稿时长
5.6 months
期刊介绍: Engineering Geology, an international interdisciplinary journal, serves as a bridge between earth sciences and engineering, focusing on geological and geotechnical engineering. It welcomes studies with relevance to engineering, environmental concerns, and safety, catering to engineering geologists with backgrounds in geology or civil/mining engineering. Topics include applied geomorphology, structural geology, geophysics, geochemistry, environmental geology, hydrogeology, land use planning, natural hazards, remote sensing, soil and rock mechanics, and applied geotechnical engineering. The journal provides a platform for research at the intersection of geology and engineering disciplines.
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