Regional Hazard Degree Evaluation and Prediction for Disaster Induced by Discharged Tailings Flow from Dam Failure

Wang, Guangjin; Tian, Sen; Hu, Bin; Chen, Jie; Kong, Xiangyun

doi:10.1007/s10706-020-01606-w

Cited by 9 publications

(5 citation statements)

References 33 publications

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“…The research trends in the last three years reflect the applications of new methodologies for the study of monitoring, prediction, and mitigation of disasters, using different techniques such as geosynthetics, e.g., [242,346,347], landslides and disaster prediction models, e.g., [243,348,349], remote sensing, e.g., [350,351], and numerical simulations and applied biotechnology to geotechnical problems, e.g., [319,352].…”

Section: Discussionmentioning

confidence: 99%

A Systematic Review of the Relationship between Geotechnics and Disasters

et al. 2022

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Landslides, earthquakes, and other natural events can change the landscape and generate human and economic losses, affecting transportation and public service infrastructure. In every geotechnical project, the investigation phase plays a fundamental role in reducing the risk of occurrence and mitigating catastrophes. As a result, governments have created entities to study disasters and identify triggering factors that generate huge losses worldwide. This research aims to conduct a systematic review of the relationship between geotechnics and disasters through bibliometric techniques, scientific production evaluation, and case studies analysis to recognize key topics, methods, and thematic development of the research worldwide. The research methodology consisted of three steps: (1) Database analysis, selection, and combination, (2) bibliometric analysis, and (3) systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. The systematic review with bibliometric analysis collected data from 1973 to 2021, with 1299 academic publications indexed in the Scopus and WoS database. These results indicated a growing trend of annual publications on disasters and their relationship with geotechnical studies, highlighting current issues and technological innovation. The main research trends in disaster risk assessment were topics mainly linked to landslides, earthquakes, liquefaction, and inappropriate analysis models with applications of geophysical methods, laboratory tests, remote sensing, and numerical models.

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Section: Discussionmentioning

confidence: 99%

A Systematic Review of the Relationship between Geotechnics and Disasters

et al. 2022

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“…With this model, they investigated the motion and pressure distribution characteristics of the outburst mudflow. Wang et al (2021) developed an evaluation index for classifying the hazard level of downstream buildings in the event of a dam failure debris flow disaster. The evaluation conclusions derived from their study exhibited a strong alignment with the conclusions drawn from physical and numerical models.…”

Section: Introductionmentioning

confidence: 99%

Study on the impact of debris flow from tailings dam failure on shale gas well station

Chen,

Mao,

et al. 2023

Front. Earth Sci.

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The shale gas well station plays a critical role in the extraction of shale gas, and its safety status exerts significant influence not only on shale gas production but also on the ecological balance of the surrounding environment. To investigate the response characteristics of the shale gas well station under the impact of tailings dam failure debris flow, a comprehensive analysis was conducted using a combination of physical modeling and numerical simulation. The analysis focused on the dynamic inundation process and the impact siltation law caused by the downstream flow of tailings dam failure debris at the shale gas well station. The depth of inundation and the extent of siltation damage were employed as key parameters for characterization. Experimental findings revealed that the downstream mudflow inundation process could be divided into three distinct stages: rapid increase (0–60 s), steady increase (60–106 s), and slow advance (106–250 s). The pattern of mudflow siltation height variation at the well station exhibited an initial rise, followed by a subsequent decline and eventual stabilization. The highest siltation volumes recorded at measurement points A to D were 4.4, 4, 5.2, and 6 m, respectively. Additionally, by employing computational fluid dynamics, numerical calculations were performed under unprotected conditions, with the error between the calculated conclusions and the test results not exceeding 15%. Furthermore, the blocking effect of 8 and 16 m debris flow blocking dam on the debris flow was thoroughly investigated. The study demonstrated that the check dam with a height of 16 m yielded the most effective blockage, resulting in the highest sediment siltation height of 0.4 m. The research results provide some reference for the prevention and control of debris flow disasters.

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“…This method is convenient to operate and intuitive in its evaluation results, but it has strong subjective randomness, and its accuracy and credibility are insufficient. In recent years, scholars have gradually introduced new mathematical methods and theories, such as fuzzy theory [16][17][18] and uncertainty measurement theory [19], which have improved the accuracy of safety evaluation. However, the methods are mostly used to deal with the relationship between indexes in the diagnosis system, and the diagnosis of the basic indexes is still mainly qualitative.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Diagnosis Method of the Health of Tailings Dams Based on Dynamic Weight and Quantitative Index

Dong

Yang

2022

Sustainability

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As a dangerous source of man-made debris flow with high potential energy, tailings dams can cause huge losses to people’s lives and property downstream once they break, and their safety control problem is particularly prominent. The health diagnosis of tailings dams is a complex and nonlinear problem full of uncertainty. At present, the health diagnosis of tailings dams is mostly qualitative evaluation or quantitative analysis aiming at a single index, so this study puts forward a comprehensive quantitative diagnosis method of tailings dam health based on dynamic weight. Slope stability, deformation stability and seepage stability are taken as project layers, and the diagnosis index system of the tailings dam is constructed. The quantitative methods of diagnosis indexes of project layers are proposed. For the dam slope stability project, the safety factor and the reliability index of tailings dams are determined based on the Monte Carlo method, which can consider the uncertainty of tailings material parameters. For the deformation stability project, the normal operation values of deformation rate and deformation amount are determined by analyzing the in situ observation data and combining them with the numerical simulation results. For the seepage stability project, through the analysis of seepage and stability, the relationship curve between the depth of saturation line and the safety factor of anti-sliding stability is established. The norms method is used to determine the quantitative standards for the diagnosis indexes of the basic layer. Based on the analytical hierarchy process method and the penalty variable weight method, the method of dynamic weight of the project layer index is proposed. The proposed methods are applied to a practical engineering project. The results show that the methods can accurately reflect the health status of tailings dams. This study provides a new method for evaluating the safety of tailings dams.

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Regional Hazard Degree Evaluation and Prediction for Disaster Induced by Discharged Tailings Flow from Dam Failure

Cited by 9 publications

References 33 publications

A Systematic Review of the Relationship between Geotechnics and Disasters

A Systematic Review of the Relationship between Geotechnics and Disasters

Study on the impact of debris flow from tailings dam failure on shale gas well station

Comprehensive Diagnosis Method of the Health of Tailings Dams Based on Dynamic Weight and Quantitative Index

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