Influence of Settlement on Base Resistance of Long Piles in Soft Soil—Field and Machine Learning Assessments

Thanh T. Nguyen, Viet D. Le, T. Q. Huynh, Nhu H. T. Nguyen
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Abstract

Understanding the role that settlement can have on the base resistance of piles is a crucial matter in the design and safety control of deep foundations under various buildings and infrastructure, especially for long to super-long piles (60–90 m length) in soft soil. This paper presents a novel assessment of this issue by applying explainable machine learning (ML) techniques to a robust database (1131 datapoints) of fully instrumented pile tests across 37 real-life projects in the Mekong Delta. The analysis of data based on conventional methods shows distinct responses of long piles to rising settlement, as compared to short piles. The base resistance can rapidly develop at a small settlement threshold (0.015–0.03% of pile’s length) and contribute up to 50–55% of the total bearing capacity in short piles, but it slowly rises over a wide range of settlement to only 20–25% in long piles due to considerable loss of settlement impact over the depth. Furthermore, by leveraging the advantages of ML methods, the results significantly enhance our understanding of the settlement–base resistance relationship through explainable computations. The ML-based prediction method is compared with popular practice codes for pile foundations, further attesting to the high accuracy and reliability of the newly established model.
沉降对软土中长桩基抗力的影响--现场和机器学习评估
了解沉降对桩基抗力的影响是各种建筑物和基础设施深基础设计和安全控制的关键问题,尤其是软土中的长桩和超长桩(长度为 60-90 米)。本文对这一问题进行了新颖的评估,将可解释的机器学习(ML)技术应用于湄公河三角洲 37 个实际项目的全仪器桩测试的强大数据库(1131 个数据点)。基于传统方法的数据分析显示,与短桩相比,长桩对沉降上升的反应截然不同。在较小的沉降临界值(桩长的 0.015%-0.03%)下,基底阻力可迅速发展,短桩的基底阻力可占总承载力的 50-55%,但在较大的沉降范围内,长桩的基底阻力会缓慢上升,由于沉降影响在深度上的大量损失,长桩的基底阻力仅占总承载力的 20-25%。此外,通过利用 ML 方法的优势,这些结果通过可解释的计算,大大提高了我们对沉降-基底阻力关系的理解。基于 ML 的预测方法与常用的桩基实践规范进行了比较,进一步证明了新建立模型的高准确性和可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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