Real-Time Warning and Risk Assessment of Tailings Dam Disaster Status Based on Dynamic Hierarchy-Grey Relation Analysis
The consequences of tailings dam breaks are disastrous; although various factors can often result in tailings dam damage, the main cause is poor management. To reduce human supervision errors and ensure that real-time early warnings alerts are sent for any risks, 22 evaluation indexes that affect da...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2019/5873420 |
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| author | Wen Li Yicheng Ye Nanyan Hu Xianhua Wang Qihu Wang |
| author_facet | Wen Li Yicheng Ye Nanyan Hu Xianhua Wang Qihu Wang |
| author_sort | Wen Li |
| collection | DOAJ |
| description | The consequences of tailings dam breaks are disastrous; although various factors can often result in tailings dam damage, the main cause is poor management. To reduce human supervision errors and ensure that real-time early warnings alerts are sent for any risks, 22 evaluation indexes that affect dam breaks were set up based on inherent and frequency risk. To efficiently predict an early dam break signal for a tailings dam, 12 key evaluation indexes of a dynamic early warning system were screened and a comprehensive consideration of the risk trend was undertaken. The current and future states of the 12 indexes were analyzed based on a borda count and dynamic analytic hierarchy process (AHP) methods and early warning grades for tailings dam damage were evaluated using the dynamic grey relation analysis method. The dynamic AHP method, which avoids the tedious testing and risks of static early warning states, was compared to the traditional method. This research provides a useful basis upon which mining enterprises can select reasonable and effective prediction indexes for risk assessment, fully implement and promote intelligent management of major risks, and conduct accurate and authentic supervision at all levels. |
| format | Article |
| id | doaj-art-e72ce026272b4965a0fab1dcedc082a3 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-e72ce026272b4965a0fab1dcedc082a32025-08-20T03:26:11ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/58734205873420Real-Time Warning and Risk Assessment of Tailings Dam Disaster Status Based on Dynamic Hierarchy-Grey Relation AnalysisWen Li0Yicheng Ye1Nanyan Hu2Xianhua Wang3Qihu Wang4School of Resource and Environmental Engineering, Wuhan University of Science and Technology, Wuhan 430081, Hubei, ChinaSchool of Resource and Environmental Engineering, Wuhan University of Science and Technology, Wuhan 430081, Hubei, ChinaSchool of Resource and Environmental Engineering, Wuhan University of Science and Technology, Wuhan 430081, Hubei, ChinaSinosteel Wuhan Safety and Environmental Protection Research Institute Co., Ltd., Wuhan 430081, Hubei, ChinaSchool of Resource and Environmental Engineering, Wuhan University of Science and Technology, Wuhan 430081, Hubei, ChinaThe consequences of tailings dam breaks are disastrous; although various factors can often result in tailings dam damage, the main cause is poor management. To reduce human supervision errors and ensure that real-time early warnings alerts are sent for any risks, 22 evaluation indexes that affect dam breaks were set up based on inherent and frequency risk. To efficiently predict an early dam break signal for a tailings dam, 12 key evaluation indexes of a dynamic early warning system were screened and a comprehensive consideration of the risk trend was undertaken. The current and future states of the 12 indexes were analyzed based on a borda count and dynamic analytic hierarchy process (AHP) methods and early warning grades for tailings dam damage were evaluated using the dynamic grey relation analysis method. The dynamic AHP method, which avoids the tedious testing and risks of static early warning states, was compared to the traditional method. This research provides a useful basis upon which mining enterprises can select reasonable and effective prediction indexes for risk assessment, fully implement and promote intelligent management of major risks, and conduct accurate and authentic supervision at all levels.http://dx.doi.org/10.1155/2019/5873420 |
| spellingShingle | Wen Li Yicheng Ye Nanyan Hu Xianhua Wang Qihu Wang Real-Time Warning and Risk Assessment of Tailings Dam Disaster Status Based on Dynamic Hierarchy-Grey Relation Analysis Complexity |
| title | Real-Time Warning and Risk Assessment of Tailings Dam Disaster Status Based on Dynamic Hierarchy-Grey Relation Analysis |
| title_full | Real-Time Warning and Risk Assessment of Tailings Dam Disaster Status Based on Dynamic Hierarchy-Grey Relation Analysis |
| title_fullStr | Real-Time Warning and Risk Assessment of Tailings Dam Disaster Status Based on Dynamic Hierarchy-Grey Relation Analysis |
| title_full_unstemmed | Real-Time Warning and Risk Assessment of Tailings Dam Disaster Status Based on Dynamic Hierarchy-Grey Relation Analysis |
| title_short | Real-Time Warning and Risk Assessment of Tailings Dam Disaster Status Based on Dynamic Hierarchy-Grey Relation Analysis |
| title_sort | real time warning and risk assessment of tailings dam disaster status based on dynamic hierarchy grey relation analysis |
| url | http://dx.doi.org/10.1155/2019/5873420 |
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