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

被引:9
|
作者
Lu, Wenxi [1 ]
Chu, Haibo [1 ]
Zhao, Ying [1 ]
Luo, Jiannan [1 ]
机构
[1] Jilin Univ, Coll Environm & Resources, 2519,Jiefangdalu Rd, Changchun 130021, Peoples R China
关键词
DNAPLs; groundwater remediation; Kriging; optimization; surrogate model;
D O I
10.2166/wpt.2013.031
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
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.
引用
收藏
页码:304 / 314
页数:11
相关论文
共 50 条
  • [1] An Adaptive Dynamic Kriging Surrogate Model for Application to the Optimal Remediation of Contaminated Groundwater
    Zhang, Shuangsheng
    Qiang, Jing
    Liu, Hanhu
    Wang, Xiaonan
    Zhou, Junjie
    Fan, Dongliang
    WATER RESOURCES MANAGEMENT, 2022, 36 (13) : 5011 - 5032
  • [2] An Adaptive Dynamic Kriging Surrogate Model for Application to the Optimal Remediation of Contaminated Groundwater
    Shuangsheng Zhang
    Jing Qiang
    Hanhu Liu
    Xiaonan Wang
    Junjie Zhou
    Dongliang Fan
    Water Resources Management, 2022, 36 : 5011 - 5032
  • [3] Adaptive Kriging surrogate model for the optimization design of a dense non-aqueous phase liquid-contaminated groundwater remediation process
    Chu, Haibo
    Lu, Wenxi
    WATER SCIENCE AND TECHNOLOGY-WATER SUPPLY, 2015, 15 (02): : 263 - 270
  • [4] Anionic surfactant remediation of soil columns contaminated by nonaqueous phase liquids
    Dwarakanath, V
    Kostarelos, K
    Pope, GA
    Shotts, D
    Wade, WH
    JOURNAL OF CONTAMINANT HYDROLOGY, 1999, 38 (04) : 465 - 488
  • [5] Optimization design based on ensemble surrogate models for DNAPLs-contaminated groundwater remediation
    Chu, Haibo
    Lu, Wenxi
    JOURNAL OF WATER SUPPLY RESEARCH AND TECHNOLOGY-AQUA, 2015, 64 (06): : 697 - 707
  • [6] Optimal Latin hypercube sampling-based surrogate model in NAPLs contaminated groundwater remediation optimization process
    Luo, Jiannan
    Ji, Yefei
    Lu, Wenxi
    Wang, He
    WATER SCIENCE AND TECHNOLOGY-WATER SUPPLY, 2018, 18 (01): : 333 - 346
  • [7] Online surrogate multiobjective optimization algorithm for contaminated groundwater remediation designs
    Jiang, Xue
    Na, Jin
    APPLIED MATHEMATICAL MODELLING, 2020, 78 (78) : 519 - 538
  • [8] Surrogate model of numerical simulation model of groundwater based on Kriging
    An, Yong-Kai
    Lu, Wen-Xi
    Dong, Hai-Biao
    Luo, Jian-Nan
    Zhongguo Huanjing Kexue/China Environmental Science, 2014, 34 (04): : 1073 - 1079
  • [9] Hydraulic Capture Optimization and Risk Assessment of Polluted Groundwater Based on Kriging Surrogate Model
    Zhang, Shuangsheng
    Qiang, Jing
    Liu, Hanhu
    Lv, Hongli
    Wu, Jingwen
    Zhou, Junjie
    WATER AIR AND SOIL POLLUTION, 2022, 233 (04):
  • [10] Hydraulic Capture Optimization and Risk Assessment of Polluted Groundwater Based on Kriging Surrogate Model
    Shuangsheng Zhang
    Jing Qiang
    Hanhu Liu
    Hongli Lv
    Jingwen Wu
    Junjie Zhou
    Water, Air, & Soil Pollution, 2022, 233