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一种结合改进遗传算法与非饱和等效连续介质模型反演坝基渗透系数的新方法及其应用

A New Method for Inversion of Dam Foundation Hydraulic Conductivity Using an Improved Genetic Algorithm Coupled with an Unsaturated Equivalent Continuum Model and Its Application.

作者信息

Peng Jiayi, Shen Zhenzhong, Xu Liqun, Gan Lei, Tan Jiacheng

机构信息

College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China.

State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China.

出版信息

Materials (Basel). 2023 Feb 16;16(4):1662. doi: 10.3390/ma16041662.

DOI:10.3390/ma16041662
PMID:36837293
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9963247/
Abstract

Seepage is a main cause of dam failure, and its stability analysis is the focus of a dam's design, construction, and management. Because a geological survey can only determine the range of a dam foundation's hydraulic conductivity, hydraulic conductivity inversion is crucial in engineering. However, current inversion methods of dam hydraulic conductivity are either not accurate enough or too complex to be directly used in engineering. Therefore, this paper proposes a new method for the inversion of hydraulic conductivity with high application value in hydraulic engineering using an improved genetic algorithm coupled with an unsaturated equivalent continuum model (IGA-UECM). This method is implemented by a new code that fully considers engineering applicability. In addition to overcoming the premature convergence shortcomings of traditional genetic algorithms, it converges faster than Bayesian optimization and tree-structured Parzen estimator inversion algorithms. This method is verified by comparing the water head from drilling exploration and inversion. The results of the inversion are used to study the influence of a cement grouting curtain layout scheme on the seepage field of the Hami concrete-face rockfill dam in China, which is used as an engineering application case of the IGA-UECM. The law of the seepage field is reasonable, which verifies the validity of the IGA-UECM. The new inversion method of hydraulic conductivity and the proposed cement grouting curtain layout in this study offer possible strategies for the design, construction, and management of concrete-face rockfill dams.

摘要

渗流是大坝失事的主要原因之一,其稳定性分析是大坝设计、施工和管理的重点。由于地质勘察只能确定大坝基础渗透系数的范围,因此渗透系数反演在工程中至关重要。然而,目前大坝渗透系数的反演方法要么不够精确,要么过于复杂,无法直接应用于工程。因此,本文提出了一种在水利工程中具有较高应用价值的渗透系数反演新方法,即改进遗传算法与非饱和等效连续体模型(IGA-UECM)相结合的方法。该方法通过一个充分考虑工程适用性的新程序来实现。除了克服传统遗传算法的早熟收敛缺点外,它比贝叶斯优化和树状帕曾估计器反演算法收敛更快。通过比较钻孔勘探水头与反演水头对该方法进行了验证。反演结果用于研究水泥灌浆帷幕布置方案对中国哈密混凝土面板堆石坝渗流场的影响,作为IGA-UECM的工程应用实例。渗流场规律合理,验证了IGA-UECM的有效性。本文研究的渗透系数反演新方法及提出的水泥灌浆帷幕布置方案,为混凝土面板堆石坝的设计、施工和管理提供了可能的策略。

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A Suggested Equivalent Method for a Drainage Structure to Analyze Seepage in Tailings Dam.一种用于排水结构分析尾矿坝渗流的等效方法建议
Materials (Basel). 2022 Oct 14;15(20):7154. doi: 10.3390/ma15207154.
2
A deep learning model designed for Raman spectroscopy with a novel hyperparameter optimization method.一种用于拉曼光谱学的深度学习模型,采用了新颖的超参数优化方法。
Spectrochim Acta A Mol Biomol Spectrosc. 2022 Nov 5;280:121560. doi: 10.1016/j.saa.2022.121560. Epub 2022 Jun 25.
3
Deep learning-based mixed-dimensional Gaussian mixture model for characterizing variability in cryo-EM.
基于深度学习的混合维度高斯混合模型,用于刻画冷冻电镜中的变异性。
Nat Methods. 2021 Aug;18(8):930-936. doi: 10.1038/s41592-021-01220-5. Epub 2021 Jul 29.
4
A review on genetic algorithm: past, present, and future.关于遗传算法的综述:过去、现在与未来。
Multimed Tools Appl. 2021;80(5):8091-8126. doi: 10.1007/s11042-020-10139-6. Epub 2020 Oct 31.
5
Improved protein structure prediction using potentials from deep learning.利用深度学习势进行蛋白质结构预测的改进。
Nature. 2020 Jan;577(7792):706-710. doi: 10.1038/s41586-019-1923-7. Epub 2020 Jan 15.