表面活性剂强化含水层修复过程的全局灵敏度

吉林大学学报(地球科学版)

表面活性剂强化含水层修复过程的全局灵敏度

罗建男^1,2，卢文喜^1,2，康柱³，宋晶⁴，张一博⁵

1.吉林大学地下水资源与环境教育部重点实验室，长春130021;
2.吉林大学环境与资源学院，长春130021;
3.中国建筑材料工业地质勘查中心吉林总队，长春130033;
4.吉林省水文水资源局辽源分局，吉林辽源136200;
5.河南省地质矿产勘查开发局第一水文地质工程地质队，郑州450004

收稿日期:2012-05-02 出版日期:2013-03-26 发布日期:2013-03-26
通讯作者: 卢文喜（1956-），男，教授，博士生导师，主要从事地下水数值模拟及优化管理方面的研究 E-mail:luwenxi@jlu.edu.cn
作者简介:罗建男(1987-)，女，博士研究生，主要从事地下水污染修复模拟-优化耦合模型方面的研究，E-mail:luojiannan01@126.com
基金资助:
国家自然科学基金项目(41072171); 高等学校博士学科点专项科研基金项目(20120061110058); 中国地质调查局地质环境调查评价与区划项目 (1212011140027)

Global Sensitivity for Surfactant Enhanced Aquifer Remediation Process

Luo Jiannan^{1, 2}, Lu Wenxi^{1, 2}, Kang Zhu³, Song Jing⁴，Zhang Yibo⁵

1.Key Laboratory of Groundwater Resources and Environment，Ministry of Education, Jilin University, Changchun130021, China;
2.College of Environment and Resources, Jilin University, Changchun130021, China;
3.Jilin Team,Geological Survey Center of China Building Materials Industry, Changchun130033, China;
4.Liaoyuan SubBureau Jilin Province Hydrology and Water Resources Bureau, Liaoyuan136200,Jilin，China;
5.First Hydrogeology and Engineering Geology Team, Survey and Development Bureau of Geology and Mineral Resources of Henan Province，Zhengzhou450004，China

Received:2012-05-02 Online:2013-03-26 Published:2013-03-26

摘要/Abstract

摘要：

针对非水相流体污染含水层的表面活性剂强化修复过程，在多相流数值模拟模型以及径向基函数人工神经网络替代模型的基础上，应用Sobol法对影响修复效果的变量进行全局灵敏度分析。当替代模型的训练集包含12组和22组数据时，替代模型与模拟模型拟合的确定性系数分别为0.977 8和0.981 6，表明随着训练集数据的增多，替代模型与模拟模型的近似精度逐渐增加。灵敏度分析结果表明：对修复效果贡献最大的决策变量为总抽水量(总灵敏度为0.491 2)，其次为修复时间(总灵敏度为0.468 5)，表面活性剂浓度对修复效果的贡献最小(总灵敏度为0.124 2)；各个变量之间存在着相互作用，但相互作用对输出响应的影响不大。

关键词: 灵敏度分析, Sobol法, 替代模型, 地下水污染, 修复

Abstract:

Based on the multi phase flow simulation model and radial basis function artificial neural network surrogate model, sensitivity of design variables, which affected the surfactant enhanced remediation efficiency of NAPLs contaminated aquifer, was analyzed using the Sobol global sensitivity analysis method. The coefficients of determination were 0.977 8 and 0.981 6 when the number of training data were 12 and 22, which demonstrated that with the number of training data increasing, the approximation accuracy increased. The results of sensitivity analysis indicated that total pumping rates had the greatest percentage contribution to the remediation efficiency (total sensitivity was 0.491 2), and the next was remediation duration (total sensitivity was 0.468 5), surfactant concentration had the smallest percentage contribution to the remediation efficiency (total sensitivity was 0.124 2). The interaction of variables also had contribution to the remediation efficiency, but the interaction effect was small. Sensitivity analysis results lay a foundation for optimization design of aquifer remediation.

Key words: sensitivity analysis, Sobol method, surrogate model, groundwater pollution, remediation

中图分类号:

P641.8

罗建男，卢文喜，康柱，宋晶，张一博. 表面活性剂强化含水层修复过程的全局灵敏度[J]. 吉林大学学报(地球科学版), 2013, 43(2): 558-0563.

Luo Jiannan, Lu Wenxi, Kang Zhu, Song Jing，Zhang Yibo. Global Sensitivity for Surfactant Enhanced Aquifer Remediation Process[J]. Journal of Jilin University(Earth Science Edition), 2013, 43(2): 558-0563.

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