scholarly journals Optimal location of cutoff walls for seawater intrusion

2021 ◽  
Vol 11 (11) ◽  
Author(s):  
Han Zheng ◽  
Lu Wenxi ◽  
Fan Yue ◽  
Miao Tiansheng ◽  
Lin Jin ◽  
...  
Keyword(s):  
Seawater Intrusion ◽  
Optimization Model ◽  
Surrogate Model ◽  
Model Simulation ◽  
Water Sources ◽  
Optimal Location ◽  
Chlorine Concentration ◽  
Kriging Surrogate Model ◽  
Cutoff Wall ◽  
Cutoff Walls

AbstractIn this paper, the simulation–optimization method is used to study the optimal location of cutoff walls for seawater intrusion. The optimization model is based on minimizing the chlorine concentration of two water sources after 50 years. In order to reduce the computational complexity, a Kriging surrogate model simulation is coupled with the optimization model. Finally, a hypothetical case is used to evaluate the accuracy of the surrogate model and the performance of the optimization model. The results show that the outputs of the Kriging surrogate model and the variable density groundwater simulation model for the same cutoff wall design fit well, and the average relative error of the two outputs is only 2.2% which proves that it is feasible to apply the Kriging surrogate model to this problem. By solving the optimization model, the location of the cutoff wall which minimizes the sum of chlorine concentration of the two water sources after 50 years is obtained. This provides a stable and reliable method for the site selection of cutoff walls for future projects intended to prevent and control seawater intrusion.

Optimization of Denser Nonaqueous Phase Liquids-contaminated groundwater remediation based on Kriging surrogate model

2013 ◽  
Vol 8 (2) ◽  
pp. 304-314 ◽  
Author(s):  
Wenxi Lu ◽  
Haibo Chu ◽  
Ying Zhao ◽  
Jiannan Luo
Keyword(s):  
Simulation Model ◽  
Optimization Model ◽  
Surrogate Model ◽  
Groundwater Remediation ◽  
Groundwater Resources ◽  
Optimal Strategies ◽  
Nonaqueous Phase Liquids ◽  
Kriging Surrogate Model ◽  
Aquifer Remediation ◽  
Remediation Process

Spillage of large amounts of Denser Nonaqueous Phase Liquids (DNAPLs) had resulted in serious pollution of groundwater resources throughout the world; a large number of studies had demonstrated surfactant-enhanced remediation is a more effective approach to remediate DNAPLs contaminations. In this paper, the remediation optimization process was carried out in three steps. Firstly, a water-oil-surfactant simulation model had been firstly established to simulate a surfactant enhanced aquifer remediation process. The Kriging surrogate model had been developed to get a similar input–output relationship with simulation model. In the final, a nonlinear optimization model was formulated for the minimum cost, and Kriging surrogate model had been embedded into the optimization model as a constrained condition. What is more, simulated annealing method was used to solve the optimization model and give the optimal Surfactant-Enhanced Aquifer Remediation strategy. The results showed Kriging surrogate model had reduced computational burden and make the optimization model easy to solve, and the optimal strategies gave an effective guide to contaminants remediation process.

Simulation of seawater intrusion and optimization of cutoff wall schemes based on surrogate model

2019 ◽  
Vol 25 (1-2) ◽  
pp. 297-313 ◽  
Author(s):  
Tiansheng Miao ◽  
Wenxi Lu ◽  
Jin Lin ◽  
Jiayuan Guo ◽  
Yue Fan
Keyword(s):  
Seawater Intrusion ◽  
Surrogate Model ◽  
Cutoff Wall

scholarly journals Updated Kriging-Assisted Shape Optimization of a Gravity Dam

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 87
Author(s):  
Yongqiang Wang ◽  
Ye Liu ◽  
Xiaoyi Ma
Keyword(s):  
Surrogate Model ◽  
Computational Cost ◽  
Region Of Interest ◽  
Optimization Procedure ◽  
Optimal Shape ◽  
Small Sample ◽  
Gravity Dam ◽  
Kriging Surrogate Model ◽  
Gravity Dams ◽  
Sample Set

The numerical simulation of the optimal design of gravity dams is computationally expensive. Therefore, a new optimization procedure is presented in this study to reduce the computational cost for determining the optimal shape of a gravity dam. Optimization was performed using a combination of the genetic algorithm (GA) and an updated Kriging surrogate model (UKSM). First, a Kriging surrogate model (KSM) was constructed with a small sample set. Second, the minimizing the predictor strategy was used to add samples in the region of interest to update the KSM in each updating cycle until the optimization process converged. Third, an existing gravity dam was used to demonstrate the effectiveness of the GA–UKSM. The solution obtained with the GA–UKSM was compared with that obtained using the GA–KSM. The results revealed that the GA–UKSM required only 7.53% of the total number of numerical simulations required by the GA–KSM to achieve similar optimization results. Thus, the GA–UKSM can significantly improve the computational efficiency. The method adopted in this study can be used as a reference for the optimization of the design of gravity dams.

scholarly journals Crack Parameters Identification Based on a Kriging Surrogate Model for Operating Rotors

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Danyang Wang ◽  
Chunrong Hua ◽  
Dawei Dong ◽  
Biao He ◽  
Zhiwen Lu
Keyword(s):  
Surrogate Model ◽  
Parameters Identification ◽  
The Finite Element Method ◽  
Breathing Crack ◽  
Kriging Surrogate Model ◽  
Crack Location ◽  
Rotor Bearing ◽  
Location Depth ◽  
Nondominated Sorting ◽  
Bearing System

Parameters identification of cracked rotors has been gaining importance in recent years, but it is still a great challenge to determine the crack parameters including crack location, depth, and angle for operating rotors. This work proposes a new method to identify crack parameters in a rotor-bearing system based on a Kriging surrogate model and an improved nondominated sorting genetic algorithm-III (NSGA-III). A rotor-bearing system with a breathing crack is established by the finite element method and the superharmonic components are used as index to detect the cracks, the Kriging surrogate model between crack parameters and the superharmonic component amplitudes of the vibration response for rotors are constructed, and an improved NSGA-III is proposed to obtain the optimal crack parameters. Numerical experiments show that the proposed method can identify the crack location, depth, and angle accurately and efficiently for operating rotors.

scholarly journals A Kriging Surrogate Model for the Interference Reduction in the Settlement Surveillance Sensors of Steel Transmission Towers

2019 ◽  
Vol 9 (16) ◽  
pp. 3343 ◽  
Author(s):  
Jiajia Shi ◽  
Liu Chu ◽  
Eduardo Souza de Cursi
Keyword(s):  
Surrogate Model ◽  
High Efficiency ◽  
Computational Cost ◽  
Element Model ◽  
Kriging Surrogate Model ◽  
Transmission Tower ◽  
Modal Frequency ◽  
Interference Reduction ◽  
Transmission Towers ◽  
Tower Foundation

The utilization of modal frequency sensors is a feasible and effective way to monitor the settlement problem of the transmission tower foundation. However, the uncertainties and interference in the real operation environment of transmission towers highly affect the accuracy and identification of modal frequency sensors. In order to reduce the interference of modal frequency sensors for transmission towers, a Kriging surrogate model is proposed in this study. The finite element model of typical transmission towers is created and validated to provide the effective original database for the Kriging surrogate model. The prediction accuracy and convergences of the Kriging surrogate model are measured and confirmed. Besides the merits in computational cost and high-efficiency, the Kriging surrogate model is proven to have a satisfied and robust interference reduction capacity. Therefore, the Kriging surrogate model is feasible and competitive for interference filtration in the settlement surveillance sensors of steel transmission towers.

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