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对松鲁楼(喀麦隆)土石坝的稳定性、安全性和可靠性指标进行先进的监测和数值建模。

Advanced monitoring and numerical modelling of the stability, safety and reliability indicators of the earthen dam of Songloulou (Cameroon).

机构信息

Laboratory of Energy Modelling Materials and Methods (E3M), National Higher Polytechnic School of Douala, University of Douala, Douala, Cameroon.

Department of Civil Engineering, National Higher Polytechnic School of Douala, University of Douala, Douala, Cameroon.

出版信息

PLoS One. 2023 Oct 11;18(10):e0292804. doi: 10.1371/journal.pone.0292804. eCollection 2023.

DOI:10.1371/journal.pone.0292804
PMID:37819948
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10566693/
Abstract

For the determination of global stability after long term advanced monitoring, artificial intelligence have been used for the data analysis of water level and displacements of Songloulou earth dam at Cameroon. Measurements of safety and reliability indicators follow changes set by piezometric and pendulums measurements. The results obtained from the artificial intelligence on the base of many years recording data have confirmed the relevance and robustness of this model. The ANFIS model combining the concept of neural network and fuzzy logic was used to simulate the behaviour of piezometers and pendulums in the dam. This model has provided satisfactory results, given in the large amount of data to be processed. The water level evolution is modelled using the ANFIS function integrated in the MATLAB software and the result is compared to that obtained by the HST method. Afterwards, the state of stress on the structure and stability of the slope at shear have been assessed based on the hydro mechanical behaviour using the GEOSTUDIO Finite Element computation software. The input parameters are: the head of water recorded in the piezometers and geotechnical parameters of the dam. The modelling results in terms of displacement are accurately consistent with the displacement measurements. The horizontal displacement of pendulums obtained by GEOSTUDIO is 80 mm and those measured directly of the pendulums have 70 mm of average value. The safety factor for slope stability according to 530 m water level is 1.5.

摘要

为了确定长期先进监测后的整体稳定性,已将人工智能用于喀麦隆 Songloulou 土坝水位和位移的数据分析。安全和可靠性指标的测量遵循由测压计和摆锤测量设置的变化。基于多年记录数据的人工智能获得的结果证实了该模型的相关性和稳健性。将神经网络和模糊逻辑的概念结合起来的 ANFIS 模型被用于模拟坝中测压计和摆锤的行为。该模型在处理大量数据方面提供了令人满意的结果。使用集成在 MATLAB 软件中的 ANFIS 函数对水位演变进行建模,并将结果与 HST 方法获得的结果进行比较。然后,基于使用 GEOSTUDIO 有限元计算软件的水力学行为,评估结构上的应力状态和剪切处边坡的稳定性。输入参数是:测压计中记录的水头和坝的岩土参数。位移方面的建模结果与位移测量准确一致。GEOSTUDIO 获得的摆锤水平位移为 80mm,直接测量的摆锤水平位移平均值为 70mm。根据 530m 水位的边坡稳定性安全系数为 1.5。

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