State-of-the-Art Review on Determining One-Dimensional Consolidation Parameters Based on Compression and Distribution of Pore Water Pressure: Coefficient of Consolidation (cv), End of Primary (EOP) Consolidation

IF 9.7 2区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Archives of Computational Methods in Engineering Pub Date : 2024-07-04 DOI:10.1007/s11831-024-10154-y
Bartłomiej Szczepan Olek
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Abstract

Predicting the time rate of consolidation is one of the major aspects of structure design, founded on compressible fine-grained soil. The time to achieve the required advancement of the consolidation process is proportional to the coefficient of consolidation (cv). In practical applications, the settlement rate is directly related to the excess pore water pressure dissipation rate. A plethora of interpretation methods have been proposed for determining consolidation parameters from laboratory one-dimensional consolidation test in the past decades. This state-of-the-art review presents a comprehensive literature study of available approaches for establishing both coefficient of consolidation and end of primary (EOP) consolidation using compression and pore water pressure laboratory data. The classification of the methods has been made to set in order interpretation approaches for future selection and comparisons. The first part of the paper describes approaches based on graphical curve-fitting. This part includes five approaches: square root of time fitting approach, Semi-logarithmic fitting approach, Differential methods, Hyperbolic approach, and approach based on excess pore water pressure dissipation. In addition, a method comparison study has been performed to evaluate the degree of agreement between selected methods statistically. For this purpose, simple regression and Bland & Altman differences analysis have been used. The second part refers to the computational-based approach, covering a wide range of methods centred on full-matching treated by least-squares, correlational equations linking cv with index properties and soft computing approaches. A thorough insight into recently published literature on machine learning and physics-informed deep learning incorporated to derive the representative value of cv has also been compiled.

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基于压缩和孔隙水压力分布确定一维固结参数的最新综述:固结系数 (cv)、原生固结末期 (EOP)
在可压缩细粒土的基础上进行结构设计时,预测固结时间率是其中一个主要方面。固结过程达到所需的推进时间与固结系数(cv)成正比。在实际应用中,沉降速度与过剩孔隙水压力耗散速度直接相关。在过去的几十年里,人们提出了大量的解释方法来确定实验室一维固结试验的固结参数。这篇最新综述对利用压缩和孔隙水压力实验室数据确定固结系数和原生固结末期(EOP)的现有方法进行了全面的文献研究。对这些方法进行了分类,以便为今后的选择和比较提供有序的解释方法。本文第一部分介绍了基于图形曲线拟合的方法。这部分包括五种方法:时间平方根拟合法、半对数拟合法、差分法、双曲线法和基于过剩孔隙水压力耗散的方法。此外,还进行了方法比较研究,以统计评估所选方法之间的一致程度。为此,使用了简单回归和 Bland & Altman 差异分析。第二部分是以计算为基础的方法,涵盖了以最小二乘法处理的完全匹配法、将 cv 与指数属性联系起来的相关方程法和软计算法为中心的各种方法。此外,还汇编了最近发表的关于机器学习和物理信息深度学习的文献,并将其纳入其中,以得出 cv 的代表值。
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来源期刊
CiteScore
19.80
自引率
4.10%
发文量
153
审稿时长
>12 weeks
期刊介绍: Archives of Computational Methods in Engineering Aim and Scope: Archives of Computational Methods in Engineering serves as an active forum for disseminating research and advanced practices in computational engineering, particularly focusing on mechanics and related fields. The journal emphasizes extended state-of-the-art reviews in selected areas, a unique feature of its publication. Review Format: Reviews published in the journal offer: A survey of current literature Critical exposition of topics in their full complexity By organizing the information in this manner, readers can quickly grasp the focus, coverage, and unique features of the Archives of Computational Methods in Engineering.
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