Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2016WR019518 |
Efficient evaluation of small failure probability in high-dimensional groundwater contaminant transport modeling via a two-stage Monte Carlo method | |
Zhang, Jiangjiang1; Li, Weixuan2; Lin, Guang3,4; Zeng, Lingzao1; Wu, Laosheng5 | |
2017-03-01 | |
发表期刊 | WATER RESOURCES RESEARCH
![]() |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2017 |
卷号 | 53期号:3 |
文章类型 | Article |
语种 | 英语 |
国家 | Peoples R China; USA |
英文摘要 | In decision-making for groundwater management and contamination remediation, it is important to accurately evaluate the probability of the occurrence of a failure event. For small failure probability analysis, a large number of model evaluations are needed in the Monte Carlo (MC) simulation, which is impractical for CPU-demanding models. One approach to alleviate the computational cost caused by the model evaluations is to construct a computationally inexpensive surrogate model instead. However, using a surrogate approximation can cause an extra error in the failure probability analysis. Moreover, constructing accurate surrogates is challenging for high-dimensional models, i.e., models containing many uncertain input parameters. To address these issues, we propose an efficient two-stage MC approach for small failure probability analysis in high-dimensional groundwater contaminant transport modeling. In the first stage, a low-dimensional representation of the original high-dimensional model is sought with Karhunen-Loeve expansion and sliced inverse regression jointly, which allows for the easy construction of a surrogate with polynomial chaos expansion. Then a surrogate-based MC simulation is implemented. In the second stage, the small number of samples that are close to the failure boundary are re-evaluated with the original model, which corrects the bias introduced by the surrogate approximation. The proposed approach is tested with a numerical case study and is shown to be 100 times faster than the traditional MC approach in achieving the same level of estimation accuracy. |
英文关键词 | failure probability contaminant transport dimension reduction |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000400160500014 |
WOS关键词 | BAYESIAN EXPERIMENTAL-DESIGN ; SLICED INVERSE REGRESSION ; POLYNOMIAL CHAOS EXPANSION ; WASTE MANAGEMENT SITES ; SURROGATE-BASED METHOD ; COLLOCATION METHOD ; ENGINEERING DESIGN ; REGULATORY POLICY ; KARHUNEN-LOEVE ; RISK ANALYSIS |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/21359 |
专题 | 资源环境科学 |
作者单位 | 1.Zhejiang Univ, Inst Soil & Water Resources & Environm Sci, Coll Environm & Resource Sci, Zhejiang Prov Key Lab Agr Resources & Environm, Hangzhou, Zhejiang, Peoples R China; 2.Pacific Northwest Natl Lab, Richland, WA USA; 3.Purdue Univ, Dept Math, W Lafayette, IN 47907 USA; 4.Purdue Univ, Sch Mech Engn, W Lafayette, IN 47907 USA; 5.Univ Calif Riverside, Dept Environm Sci, Riverside, CA 92521 USA |
推荐引用方式 GB/T 7714 | Zhang, Jiangjiang,Li, Weixuan,Lin, Guang,et al. Efficient evaluation of small failure probability in high-dimensional groundwater contaminant transport modeling via a two-stage Monte Carlo method[J]. WATER RESOURCES RESEARCH,2017,53(3). |
APA | Zhang, Jiangjiang,Li, Weixuan,Lin, Guang,Zeng, Lingzao,&Wu, Laosheng.(2017).Efficient evaluation of small failure probability in high-dimensional groundwater contaminant transport modeling via a two-stage Monte Carlo method.WATER RESOURCES RESEARCH,53(3). |
MLA | Zhang, Jiangjiang,et al."Efficient evaluation of small failure probability in high-dimensional groundwater contaminant transport modeling via a two-stage Monte Carlo method".WATER RESOURCES RESEARCH 53.3(2017). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论