scholarly journals Risk Analysis of Tunnel Water and Mud Inrush Using Interpretive Structural Modeling and Fault Tree

2022 ◽  
Author(s):  
Min Han ◽  
Teng Xia ◽  
Maoxin Su ◽  
Yiguo Xue
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Structural Modeling ◽  
Geological Structure ◽  
Geological Hazard ◽  
Analysis Model ◽  
Interpretive Structural Modeling ◽  
Water And Mud Inrush

Abstract Water and mud inrush is a common geological hazard in tunnel construction. Risk analysis of tunnel water and mud inrush has always been an important subject. In order to avoid the geological hazard, this paper presents a risk analysis model of tunnel water and mud inrush. The model combines the interpretive structural modeling method (ISM) and fault tree analysis (FTA). Relying on the Qinyu tunnel in the Weiwu expressway project, water and mud inrush risk factors are obtained by using ISM. Fundamental risk factors include formation lithology, attitude of stratum, strata combination, topography and geomorphology, geological structure and weather. ISM core risk factors are used as FTA basic events. Fuzzy importance of FTA basic events is obtained by using fuzzy interval calculation. The results show that geological structure is the primary risk factor causing Qinyu tunnel water and mud inrush. The model achieves qualitative and quantitative analysis of tunnel water and mud inrush. It accurately determines the main factors affecting the tunnel water and mud inrush, which is conducive to accident prevention.

Cybersecurity risk analysis model using fault tree analysis and fuzzy decision theory

2018 ◽  
Vol 43 ◽  
pp. 248-260 ◽  
Author(s):  
Ana Paula Henriques de Gusmão ◽  
Maisa Mendonça Silva ◽  
Thiago Poleto ◽  
Lúcio Camara e Silva ◽  
Ana Paula Cabral Seixas Costa
Keyword(s):  
Risk Analysis ◽  
Decision Theory ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Fuzzy Decision ◽  
Analysis Model ◽  
Tree Analysis

scholarly journals Integration of Interpretive Structural Modeling with Fuzzy Bayesian Network for Risk Assessment of Tunnel Collapse

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Leping He ◽  
Tao Tang ◽  
Qijun Hu ◽  
Qijie Cai ◽  
Zhijun Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Bayesian Network ◽  
Risk Model ◽  
Multicriteria Decision Making ◽  
Structural Modeling ◽  
Interpretive Structural Modeling ◽  
Construction Risk ◽  
Tunnel Collapse ◽  
The Relationship

Frequent collapse accidents in tunnels are associated with many construction risk factors, and the interrelationship among these risk factors is complex and ambiguous. This study’s aim is to clarify the relationship among risk factors to reduce the tunnel collapse risk. A multicriteria decision-making method is proposed by combining interpretive structural modeling (ISM) and fuzzy Bayesian network (FBN). ISM is used to determine the hierarchical relationships among risk factors. FBN quantitatively analyzes the strength of the interaction among risk factors and conducts risk analysis. The ISM-FBN method contains three steps: (1) drawing the ISM-directed graph; (2) obtaining the probability of the FBN nodes; and (3) using GeNle to implement risk analysis. The proposed method is also used to assess the collapse risk and detect the critical factors in the Canglongxia Tunnel, China. This method’s tunnel collapse risk model can provide managers with clear risk information and better realize project management.

A risk analysis model for mining accidents using a fuzzy approach based on fault tree analysis

2018 ◽  
Vol 31 (4) ◽  
pp. 577-594 ◽  
Author(s):  
Fatma Yasli ◽  
Bersam Bolat
Keyword(s):  
Risk Analysis ◽  
Management Strategies ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Fuzzy Approach ◽  
Analysis Model ◽  
Basis Risk ◽  
Tree Analysis ◽  
Content Type ◽  
Essential Components

Purpose Risk analysis is a critical investigation field for many sectors and organizations to maintain the information management reliable. Since mining is one of the riskiest sectors for both workers and management, comprehensive risk analysis should be carried out. The purpose of this paper is to explore comprehensively the undesired events that may occur during a particular process with their main reasons and to perform a risk analysis for these events, by developing a risk analysis methodology. For performing risk analysis, discovering and defining the potential accidents and incidents including their root causes are important contributions of the study as distinct from the related literature. The fuzzy approach is used substantially to obtain the important inferences about the hazardous process by identifying the critical risk points in the processes. In the scope of the study, the proposed methodology is applied to an underground chrome mine and obtaining significant findings of mining risky operations is targeted. Design/methodology/approach Fault tree analysis and fuzzy approach are used for performing the risk analysis. When determining the probability and the consequences of the events which are essential components for the risk analysis, expressions of the heterogeneous expert group are considered by means of the linguistic terms. Fault tree analysis and fuzzy approach present a quiet convenience solution together to specify the possible accidents and incidents in the particular process and determine the values for the basis risk components. Findings This study primarily presents a methodology for a comprehensive risk analysis. By implementing the proposed methodology to the underground loading and conveying processes of a chrome mine, 28 different undesired events that may occur during the processes are specified. By performing risk analysis for these events, it is established that the employee’s physical constraint while working with the shovel in the fore area, the falling of materials on employees from the chute and the scaling bar injuries are the riskiest undesired events in the underground loading and conveying process of the mine. Practical implications The proposed methodology provides a confidential and comprehensive method for risk analysis of the undesired events in a particular process. The capability of fault tree analysis for specifying the undesired events systematically and the applicability of fuzzy approach for converting the experts’ linguistic expressions to the mathematical values provide a significant advantage and convenience for the risk analysis. Originality/value The major contribution of this paper is to develop a methodology for the risk analysis of a variety of mining accidents and incidents. The proposed methodology can be applied to many production processes to investigate the dangerous operations comprehensively and find out the efficient management strategies. Before performing the risk analysis, determining the all possible accidents and incidents in the particular process using the fault tree analysis provides the effectiveness and the originality of the study. Also, using the fuzzy logic to find out the consequences of the events with experts’ linguistic expressions provides an efficient method for performing risk analysis.

scholarly journals Analysis Model of Risk Factors of Urban Bus Operation Based on FTA-CLR

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jianfeng Xi ◽  
Yunhe Zhao ◽  
Tongqiang Ding ◽  
Jian Tian ◽  
Lianjie Li
Keyword(s):  
Risk Factors ◽  
Goodness Of Fit ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Economic Loss ◽  
Analysis Model ◽  
Goodness Of Fit Test ◽  
High Risk Factors ◽  
Accident Data ◽  
Urban Bus

In order to comprehensively analyze the risk factors and accurately find the high risk factors related to accidents, an analysis model of risk factors of urban bus operation is proposed, in which the advantages of the structural analysis of the Fault Tree Analysis (FTA) and the correlation analysis of the Cumulative Logistic Regression (CLR) are combined. Firstly, based on the accident data in Northeast China, FTA is used to compile the urban bus operation fault tree. In the fault tree, 16 bus operation risk factors are classified, while the risk factors are sorted and compared from three aspects: structural importance, probability importance, and critical importance. And then, the 11 higher risk factors are selected according to the discriminant principle. Secondly, bus operation accidents are divided into fatal accidents, injury accidents, and major economic loss accidents. The CLR model is used to fit the much higher risk factors that lead to urban bus operation accidents from above 11 higher risk factors. Finally, the scientific rationality and applicability of the model are verified, through the goodness of fit test and the comparison test with the actual probability of occurrence.

Scenario based evaluation of a cost risk model through sensitivity analysis

2015 ◽  
Vol 22 (4) ◽  
pp. 403-423 ◽  
Author(s):  
Önder Ökmen ◽  
Ahmet Öztaş
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Risk Model ◽  
Practical Method ◽  
Cost Evaluation ◽  
Sensitivity Analyses ◽  
Analysis Model ◽  
Content Type ◽  
Detailed Evaluation ◽  
Cost Risk

Purpose – Actual costs frequently deviate from the estimated costs in either favorable or adverse direction in construction projects. Conventional cost evaluation methods do not take the uncertainty and correlation effects into account. In this regard, a simulation-based cost risk analysis model, the Correlated Cost Risk Analysis Model, previously has been proposed to evaluate the uncertainty effect on construction costs in case of correlated costs and correlated risk-factors. The purpose of this paper is to introduce the detailed evaluation of the Cost Risk Analysis Model through scenario and sensitivity analyses. Design/methodology/approach – The evaluation process consists of three scenarios with three sensitivity analyses in each and 28 simulations in total. During applications, the model’s important parameter called the mean proportion coefficient is modified and the user-dependent variables like the risk-factor influence degrees are changed to observe the response of the model to these modifications and to examine the indirect, two-sided and qualitative correlation capturing algorithm of the model. Monte Carlo Simulation is also applied on the same data to compare the results. Findings – The findings have shown that the Correlated Cost Risk Analysis Model is capable of capturing the correlation between the costs and between the risk-factors, and operates in accordance with the theoretical expectancies. Originality/value – Correlated Cost Risk Analysis Model can be preferred as a reliable and practical method by the professionals of the construction sector thanks to its detailed evaluation introduced in this paper.

A fuzzy fault tree analysis based risk assessment approach for enterprise resource planning projects

2018 ◽  
Vol 35 (5) ◽  
pp. 1115-1141 ◽  
Author(s):  
Mina Moeinedini ◽  
Sadigh Raissi ◽  
Kaveh Khalili-Damghani
Keyword(s):  
Risk Factors ◽  
Enterprise Resource Planning ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Resource Planning ◽  
Successful Implementation ◽  
Tree Analysis ◽  
Content Type ◽  
Cause And Effect ◽  
Fuzzy Fault Tree Analysis

Purpose Enterprise resource planning (ERP) is assumed as a commonly used solution in order to provide an integrated view of core business processes, including product planning, manufacturing cost, delivery, marketing, sales, inventory management, shipping and payment. Selection and implementation of a suitable ERP solution are not assumed a trivial project because of the challenging nature of it, high costs, long-duration of installation and customization, as well as lack of successful benchmarking experiences. During the ERP projects, several risk factors threat the successful implementation of the project. These risk factors usually refer to different phases of the ERP projects including purchasing, pilot implementation, teaching, install, synchronizing, and movement from old systems toward new ones, initiation and utilization. These risk factors have dominant effects on each other. The purpose of this paper is to explore the hybrid reliability-based method is proposed to assess the risk factors of ERP solutions. Design/methodology/approach In this regard, the most important risk factors of ERP solutions are first determined. Then, the interactive relations of these factors are recognized using a graph based method, called interpretive structural modeling. The resultant network of relations between these factors initiates a new viewpoint toward the cause and effect relations among risk factors. Afterwards, a fuzzy fault tree analysis is proposed to calculate Failure Fuzzy Possibility (FFP) for the basic events of the fault tree leading to a quantitative evaluation of risk factors. Findings The whole proposed method is applied in a well-known Iranian foodservice distributor as a case study. The most impressive risk factors are identified, classified and prioritized. Moreover, the cause and effect diagram between the risk factors are identified. So, the ERP leader can plan a low-risk project and increase the chance of success. Originality/value According to the authors’ best knowledge, such approach was not reported before in the literature of ERP risk assessments.

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