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Xiao Fu
National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China

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Journal article
Published: 03 August 2020 in Sustainability
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A large proportion of the dams in China are earth-rock dams. Regarding the well-studied loss of life and economic consequences due to dam breaks, this paper introduces the causes and modes of earth-rock dam breaks and the corresponding dam-break losses in terms of the social and environmental aspects. This study formulates the evaluation index system and criteria of earth-rock dam breaks’ impact on society and the environment based on a fuzzy comprehensive evaluation method. The results show that the evaluation grade of the social and environmental impact of the dam break of the Liujiatai Reservoir was “serious”. Therefore, similar dams in China should take corresponding measures in advance to reduce the social and environmental impact of earth-rock dam breaks.

ACS Style

Hao Gu; Xiao Fu; Yantao Zhu; Yijun Chen; Lixian Huang. Analysis of Social and Environmental Impact of Earth-Rock Dam Breaks Based on a Fuzzy Comprehensive Evaluation Method. Sustainability 2020, 12, 6239 .

AMA Style

Hao Gu, Xiao Fu, Yantao Zhu, Yijun Chen, Lixian Huang. Analysis of Social and Environmental Impact of Earth-Rock Dam Breaks Based on a Fuzzy Comprehensive Evaluation Method. Sustainability. 2020; 12 (15):6239.

Chicago/Turabian Style

Hao Gu; Xiao Fu; Yantao Zhu; Yijun Chen; Lixian Huang. 2020. "Analysis of Social and Environmental Impact of Earth-Rock Dam Breaks Based on a Fuzzy Comprehensive Evaluation Method." Sustainability 12, no. 15: 6239.

Journal article
Published: 13 April 2020 in Mathematical Problems in Engineering
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A dam deformation prediction model based on adaptive weighted least squares support vector machines (AWLSSVM) coupled with modified Ant Lion Optimization (ALO) is proposed, which can be utilized to evaluate the operational states of concrete dams. First, the Ant Lion Optimizer, a novel metaheuristic algorithm, is used to determine the punishment factor and kernel width in the least squares support vector machine (LSSVM) model, which simulates the hunting process of antlions in nature. Second, aiming to solve the premature convergence phenomenon, Levy flight is introduced into the ALO to improve the global optimization ability. Third, according to the statistical characteristics of the datum error, an improved normal distribution weighting rule is applied to update the weighted value of data samples based on the learning result of the LSSVM model. Moreover, taking a concrete arch dam in China as an example, the horizontal displacement recorded by a pendulum is used as a study object. The accuracy and validity of the proposed model are verified and evaluated based on the four evaluating criteria, and the results of the proposed model are compared with those of well-established models. The simulation results demonstrate that the proposed model outperforms other models and effectively overcomes the influence of outliers on the performance of the model. It also has high prediction accuracy, produces excellent generalization performance, and can be a promising alternative technique for the analysis and prediction of dam deformation and other fields, including flood interval prediction, the stock price market, and wind speed forecasting.

ACS Style

Yijun Chen; Chongshi Gu; Chenfei Shao; Hao Gu; Dongjian Zheng; Zhongru Wu; Xiao Fu. An Approach Using Adaptive Weighted Least Squares Support Vector Machines Coupled with Modified Ant Lion Optimizer for Dam Deformation Prediction. Mathematical Problems in Engineering 2020, 2020, 1 -23.

AMA Style

Yijun Chen, Chongshi Gu, Chenfei Shao, Hao Gu, Dongjian Zheng, Zhongru Wu, Xiao Fu. An Approach Using Adaptive Weighted Least Squares Support Vector Machines Coupled with Modified Ant Lion Optimizer for Dam Deformation Prediction. Mathematical Problems in Engineering. 2020; 2020 ():1-23.

Chicago/Turabian Style

Yijun Chen; Chongshi Gu; Chenfei Shao; Hao Gu; Dongjian Zheng; Zhongru Wu; Xiao Fu. 2020. "An Approach Using Adaptive Weighted Least Squares Support Vector Machines Coupled with Modified Ant Lion Optimizer for Dam Deformation Prediction." Mathematical Problems in Engineering 2020, no. : 1-23.

Journal article
Published: 02 January 2020 in International Journal of Environmental Research and Public Health
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As an important feature, deformation analysis is of great significance to ensure the safety and stability of arch dam operation. In this paper, Jinping-I arch dam with a height of 305 m, which is the highest dam in the world, is taken as the research object. The deformation data representation method is analyzed, and the processing method of deformation spatiotemporal data is discussed. A deformation hybrid model is established, in which the hydraulic component is calculated by the finite element method, and other components are still calculated by the statistical model method. Since the relationship among the measuring points is not taken into account and the overall situation cannot be fully reflected in the hybrid model, a spatiotemporal hybrid model is proposed. The measured values and coordinates of all the typical points with pendulums of the arch dam are included in one spatiotemporal hybrid model, which is feasible, convenient, and accurate. The model can predict the deformation of any position on the arch dam. This is of great significance for real-time monitoring of deformation and stability of Jinping-I arch dam and ensuring its operation safety.

ACS Style

Chongshi Gu; Xiao Fu; Chenfei Shao; Zhongwen Shi; Huaizhi Su. Application of Spatiotemporal Hybrid Model of Deformation in Safety Monitoring of High Arch Dams: A Case Study. International Journal of Environmental Research and Public Health 2020, 17, 319 .

AMA Style

Chongshi Gu, Xiao Fu, Chenfei Shao, Zhongwen Shi, Huaizhi Su. Application of Spatiotemporal Hybrid Model of Deformation in Safety Monitoring of High Arch Dams: A Case Study. International Journal of Environmental Research and Public Health. 2020; 17 (1):319.

Chicago/Turabian Style

Chongshi Gu; Xiao Fu; Chenfei Shao; Zhongwen Shi; Huaizhi Su. 2020. "Application of Spatiotemporal Hybrid Model of Deformation in Safety Monitoring of High Arch Dams: A Case Study." International Journal of Environmental Research and Public Health 17, no. 1: 319.

Research article
Published: 14 August 2019 in Advances in Civil Engineering
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Real-time monitoring of the actual elastic modulus is essential and necessary to ensure the safe operation of arch dams. The zoning elastic modulus of a high arch dam is inversed by using deformation safety monitoring data in the operation period, based on the particle swarm optimization with gravitation search algorithm for support vector machine (PSOGSA-SVM) method. Firstly, the measured data of multipoints with a pendulum are separated to construct the initial sample training set; then, an optimal inversion model is established to reflect the complex nonlinear relationship between the mechanical parameters of the high arch dam and the deformation of measured points; finally, the PSOGSA-SVM method is used to train and dynamically update the training set so as to realize the optimization solution of the inversion model. The proposed inversion method is successfully applied to a high arch dam in China to verify its feasibility and validity. The results show that the actual elastic modulus of the dam body is much larger than the initial elastic modulus, which is beneficial to structural stability.

ACS Style

Bo Chen; Xiao Fu; Xuyuan Guo; Chongshi Gu; Chenfei Shao; Xiangnan Qin. Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method. Advances in Civil Engineering 2019, 2019, 1 -13.

AMA Style

Bo Chen, Xiao Fu, Xuyuan Guo, Chongshi Gu, Chenfei Shao, Xiangnan Qin. Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method. Advances in Civil Engineering. 2019; 2019 ():1-13.

Chicago/Turabian Style

Bo Chen; Xiao Fu; Xuyuan Guo; Chongshi Gu; Chenfei Shao; Xiangnan Qin. 2019. "Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method." Advances in Civil Engineering 2019, no. : 1-13.

Journal article
Published: 29 April 2018 in International Journal of Environmental Research and Public Health
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Earth-rock dams make up a large proportion of the dams in China, and their failures can induce great risks. In this paper, the risks associated with earth-rock dam failure are analyzed from two aspects: the probability of a dam failure and the resulting life loss. An event tree analysis method based on fuzzy set theory is proposed to calculate the dam failure probability. The life loss associated with dam failure is summarized and refined to be suitable for Chinese dams from previous studies. The proposed method and model are applied to one reservoir dam in Jiangxi province. Both engineering and non-engineering measures are proposed to reduce the risk. The risk analysis of the dam failure has essential significance for reducing dam failure probability and improving dam risk management level.

ACS Style

Xiao Fu; Chong-Shi Gu; Huai-Zhi Su; Xiang-Nan Qin. Risk Analysis of Earth-Rock Dam Failures Based on Fuzzy Event Tree Method. International Journal of Environmental Research and Public Health 2018, 15, 886 .

AMA Style

Xiao Fu, Chong-Shi Gu, Huai-Zhi Su, Xiang-Nan Qin. Risk Analysis of Earth-Rock Dam Failures Based on Fuzzy Event Tree Method. International Journal of Environmental Research and Public Health. 2018; 15 (5):886.

Chicago/Turabian Style

Xiao Fu; Chong-Shi Gu; Huai-Zhi Su; Xiang-Nan Qin. 2018. "Risk Analysis of Earth-Rock Dam Failures Based on Fuzzy Event Tree Method." International Journal of Environmental Research and Public Health 15, no. 5: 886.