On the multi-parameters identification of concrete dams: A novel stochastic inverse approach

IF 3.4 2区 工程技术 Q2 ENGINEERING, GEOLOGICAL
Chaoning Lin, Xiaohu Du, Siyu Chen, Tongchun Li, Xinbo Zhou, P. H. A. J. M. van Gelder
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Abstract

This paper introduces a novel stochastic inverse method that utilizes perturbation theory and advanced intelligence techniques to solve the multi-parameter identification problem of concrete dams using displacement field monitoring data. The proposed method considers the uncertainties associated with the dam displacement monitoring data, which are comprised of two distinct sources: the first is related to stochastic mechanical properties of the dam, and the second is due to observation errors. The displacements at different measuring points generated by dam mechanical properties exhibit spatial correlation, while the observation errors at different points can be considered statistically random. In this context, the inversion formulas are derived for unknown stochastic parameters of the dam by combining perturbation equations and Taylor expansion methods. An improved meta-heuristic optimization method is employed to identify the mean of stochastic parameters, while mathematical and statistical methods are used to determine the variance of stochastic parameters. The feasibility of the proposed method is verified through numerical examples of a typical dam section under different conditions. Additionally, the paper discusses and demonstrates the applicability of this method in a practical dam project. Results indicate that this method can effectively capture the uncertainty of dam's mechanical properties and separates them from observation errors.

混凝土大坝的多参数识别:一种新颖的随机反演方法
本文介绍了一种新颖的随机逆方法,该方法利用扰动理论和先进的智能技术,利用位移现场监测数据解决混凝土大坝的多参数识别问题。所提出的方法考虑了与大坝位移监测数据相关的不确定性,这些不确定性由两个不同的来源组成:第一个来源与大坝的随机力学特性有关,第二个来源是观测误差。由大坝机械特性产生的不同测量点的位移表现出空间相关性,而不同点的观测误差可视为统计随机误差。在这种情况下,通过结合扰动方程和泰勒展开方法,得出了大坝未知随机参数的反演公式。采用改进的元启发式优化方法来确定随机参数的平均值,同时使用数学和统计方法来确定随机参数的方差。通过不同条件下典型坝段的数值实例验证了所提方法的可行性。此外,论文还讨论并演示了该方法在实际大坝工程中的适用性。结果表明,该方法可有效捕捉大坝力学性能的不确定性,并将其与观测误差区分开来。
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来源期刊
CiteScore
6.40
自引率
12.50%
发文量
160
审稿时长
9 months
期刊介绍: The journal welcomes manuscripts that substantially contribute to the understanding of the complex mechanical behaviour of geomaterials (soils, rocks, concrete, ice, snow, and powders), through innovative experimental techniques, and/or through the development of novel numerical or hybrid experimental/numerical modelling concepts in geomechanics. Topics of interest include instabilities and localization, interface and surface phenomena, fracture and failure, multi-physics and other time-dependent phenomena, micromechanics and multi-scale methods, and inverse analysis and stochastic methods. Papers related to energy and environmental issues are particularly welcome. The illustration of the proposed methods and techniques to engineering problems is encouraged. However, manuscripts dealing with applications of existing methods, or proposing incremental improvements to existing methods – in particular marginal extensions of existing analytical solutions or numerical methods – will not be considered for review.
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