Jing Zhang , Haiyong Cheng , Shunchuan Wu , Guanghua Wu , Rujun Tuo , Weihua Liu , Xinglong Feng , Zhengrong Li
{"title":"基于耦合加权贝叶斯网络的矿井地下泥石流风险分析","authors":"Jing Zhang , Haiyong Cheng , Shunchuan Wu , Guanghua Wu , Rujun Tuo , Weihua Liu , Xinglong Feng , Zhengrong Li","doi":"10.1016/j.ijdrr.2024.104922","DOIUrl":null,"url":null,"abstract":"<div><div>Mines mined by the natural caving method are prone to underground debris flow disasters, resulting in mud gushing blocking roadways, equipment damage and even casualties, which seriously affect the safe operation of mines. To carry out a risk analysis of underground debris flows in mines, quantify the interactions among risk factors in the process of disasters, and identify the main disaster-causing paths, DEMATEL-ISM was used to analyze 18 risk factors related to material sources, geology, water sources and processes. A multilevel network structure model was constructed, and the model was mapped to a Bayesian network (BN). Based on the N-K model, the degree of risk coupling was calculated, the nodes in the BN were coupled and weighted, and diagnostic reasoning for underground debris flows was realized based on posterior probability. The results showed that the risk of debris flow increases with increasing coupling factor. The factors of water source, geology and ore drawing ranked at the top in terms of the probability change rate of the BN nodes, and a main disaster-causing path was obtained by diagnostic reasoning, which provides a theoretical basis for the formulation of underground debris flow prevention and control measures.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"114 ","pages":"Article 104922"},"PeriodicalIF":4.2000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Risk analysis of underground debris flows in mines based on a coupled weighted Bayesian network\",\"authors\":\"Jing Zhang , Haiyong Cheng , Shunchuan Wu , Guanghua Wu , Rujun Tuo , Weihua Liu , Xinglong Feng , Zhengrong Li\",\"doi\":\"10.1016/j.ijdrr.2024.104922\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Mines mined by the natural caving method are prone to underground debris flow disasters, resulting in mud gushing blocking roadways, equipment damage and even casualties, which seriously affect the safe operation of mines. To carry out a risk analysis of underground debris flows in mines, quantify the interactions among risk factors in the process of disasters, and identify the main disaster-causing paths, DEMATEL-ISM was used to analyze 18 risk factors related to material sources, geology, water sources and processes. A multilevel network structure model was constructed, and the model was mapped to a Bayesian network (BN). Based on the N-K model, the degree of risk coupling was calculated, the nodes in the BN were coupled and weighted, and diagnostic reasoning for underground debris flows was realized based on posterior probability. The results showed that the risk of debris flow increases with increasing coupling factor. The factors of water source, geology and ore drawing ranked at the top in terms of the probability change rate of the BN nodes, and a main disaster-causing path was obtained by diagnostic reasoning, which provides a theoretical basis for the formulation of underground debris flow prevention and control measures.</div></div>\",\"PeriodicalId\":13915,\"journal\":{\"name\":\"International journal of disaster risk reduction\",\"volume\":\"114 \",\"pages\":\"Article 104922\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of disaster risk reduction\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2212420924006848\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of disaster risk reduction","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212420924006848","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Risk analysis of underground debris flows in mines based on a coupled weighted Bayesian network
Mines mined by the natural caving method are prone to underground debris flow disasters, resulting in mud gushing blocking roadways, equipment damage and even casualties, which seriously affect the safe operation of mines. To carry out a risk analysis of underground debris flows in mines, quantify the interactions among risk factors in the process of disasters, and identify the main disaster-causing paths, DEMATEL-ISM was used to analyze 18 risk factors related to material sources, geology, water sources and processes. A multilevel network structure model was constructed, and the model was mapped to a Bayesian network (BN). Based on the N-K model, the degree of risk coupling was calculated, the nodes in the BN were coupled and weighted, and diagnostic reasoning for underground debris flows was realized based on posterior probability. The results showed that the risk of debris flow increases with increasing coupling factor. The factors of water source, geology and ore drawing ranked at the top in terms of the probability change rate of the BN nodes, and a main disaster-causing path was obtained by diagnostic reasoning, which provides a theoretical basis for the formulation of underground debris flow prevention and control measures.
期刊介绍:
The International Journal of Disaster Risk Reduction (IJDRR) is the journal for researchers, policymakers and practitioners across diverse disciplines: earth sciences and their implications; environmental sciences; engineering; urban studies; geography; and the social sciences. IJDRR publishes fundamental and applied research, critical reviews, policy papers and case studies with a particular focus on multi-disciplinary research that aims to reduce the impact of natural, technological, social and intentional disasters. IJDRR stimulates exchange of ideas and knowledge transfer on disaster research, mitigation, adaptation, prevention and risk reduction at all geographical scales: local, national and international.
Key topics:-
-multifaceted disaster and cascading disasters
-the development of disaster risk reduction strategies and techniques
-discussion and development of effective warning and educational systems for risk management at all levels
-disasters associated with climate change
-vulnerability analysis and vulnerability trends
-emerging risks
-resilience against disasters.
The journal particularly encourages papers that approach risk from a multi-disciplinary perspective.