Comprehensive Risk Assessment Method Research Articles

The Comprehensive Whole Process Risk Assessment Method of Mine Multi-factor

The Comprehensive Whole Process Risk Assessment Method of Mine Multi-factor

A comprehensive risk assessment method for hot work in underground mines based on G1-EWM and unascertained measure theory

A risk assessment method for hot work based on G1-EWM and unascertained measurement theory was proposed to prevent hot work accidents in underground mines. Firstly, based on the risk influencing factors and classification criteria for underground hot work operations in mines, a single indicator measurement matrix was constructed using unascertained measurement theory; Secondly, a risk assessment index system for mine underground hot work operations was established. The combination weight coefficient of each index was determined using the order relationship analysis method (G1) and entropy weight method (EWM) and coupled with the single index measurement evaluation vector to calculate the multi-index comprehensive evaluation vector of the evaluation object; Finally, the model was validated and examined using engineering examples, and the evaluation level was determined using confidence identification criteria. The results showed that the proposed method, when used to evaluate the risk of hot work operations in tunnels and vertical shafts in metal mines, produces risk levels that are in line with reality III (Moderate Risk) for the vertical shaft and IV (High Risk) for the tunnels. The evaluation model results are consistent with the risk evaluation results the whole process of on-site hot work, which verifies the model feasibility. A unique strategy and method for risk management in hot work operations in underground mines is provided by the combination of weighting and unascertained measure models, which has theoretical and practical value. Future research could focus on refineing this model by exploring the applicability in diverse mining environments and integrating advanced analytical techniques to enhance the predictive accuracy and operational efficiency.

Comprehensive risk assessment for the esterification processes based on Dempster-Shafer evidence theory and cloud model

As a typical chemical process, esterification is usually exothermic and has a high risk of fire and explosion. To recognize and control the risk, it is vital to conduct risk assessment. Therefore, a comprehensive risk assessment method for the esterification process was proposed in this study. By analyzing the characteristics and hazards of the esterification process, a comprehensive evaluation index system was established. It covers four aspects including risk of materials, risk of reaction, possibility of thermal runaway inhibition and risk of process conditions. The improved Dempster-Shafer evidence theory integrates the Hellinger distance and the Pignistic vector angle. It effectively deals with the conflicts between different experts when determining weights. And the cloud model was used to grade index criteria, converting qualitative and quantitative assessment results. This was done to deal with the randomness and ambiguity in the assessment process. Syntheses of butl acetate and tert-butyl peroxyacetate were adopted as case study to validate the proposed method. The assessment results are generally consistent with the Dow's Fire and Explosion Index (F&EI) and the Inherent Benign⁃ness Indicator (IBI). This work will provide a new method for comprehensive risk assessment of the esterification process and can be further used for process optimization.

Dynamic risk assessment for train brake system considering time-dependent components and human factors

The train brake system (TBS) is a critical segment for the safety of train system whose failure can lead to serious consequences. Due to the dynamic and multi-factors coupling characteristics of TBS failure, it is important to construct a comprehensive risk assessment method to capturing the time-dependent and human factors. This paper proposes a model that incorporates degraded components and human factors into dynamic Bayesian networks to formulate dynamic risk assessment for the TBS. In the proposed method, FT is employed to determine the logical structure of the failure process. DBN is used to capture the dynamic features of TBS failure in which the human factors are modelled by the CREAM method and the degraded components are formulated by MC. Meanwhile, different maintenance strategies are considered in the proposed hybrid method. In particular, we evaluate the degradation of four common failures, that is, the insufficient braking, brake test failure, brake release failure, and wheel lock. The risk-influencing factors of the brake system and their relevance are identified. When considering the cause of brake system failure, we analyse the human factors in the system through the reliability analysis method. The results show that the proposed method is able to capture the spatial variability of parameters and simulates the evolution of brake faults in time and space domains. Some practical suggestions are provided to the operators of the system based on the sensitivity analysis.

Methods for risk assessment of old overhead transmission lines

In view of the problem that the transmission line body elements are not considered comprehensively in the current evaluation methods of old transmission lines, this paper proposes a comprehensive risk assessment method for old overhead transmission lines based on practical operation experience. Firstly, the risk factors affecting the safe operation of the old overhead transmission lines were summarized. The pylons in the line segment were investigated item by item. All the hidden trouble points in the line segment were sorted out, and the risk value was calculated by danger source identification and risk assessment method. Secondly, according to the possibility of fault caused by technical factors on the old line, the weight coefficient is given to calculate the deduction value to judge the risk grade state. Finally, when the total deduction is greater than 60 points, or the single deduction is greater than 24 points, it is necessary to formulate a corresponding management plan to guide the orderly management of line hidden dangers.

Risk assessment of disconnect operations of MNPP using similarity aggregation method based fuzzy dynamic Bayesian networks model

Marine Nuclear Power Platforms (MNPP) have the potential to provide a safe and efficient energy supply for offshore oil extraction and remote islands. During the service, MNPP is subject to disconnect operations and return to the dock for repair and maintenance. However, the failure of disconnect operations of MNPP can have catastrophic consequences. It is essential to carry out an accurate risk assessment of the disconnect operation process. In this study, a comprehensive dynamic quantitative dynamic risk assessment method is proposed to study the whole process of MNPP disconnect operations from preparation to towing. Firstly, a similarity aggregation method (SAM) is used to solve the expert fuzzy opinion aggregation problem, and then the probability of failure of the event consistent with the group consensus opinion is obtained. Secondly, a dynamic Bayesian networks (DBNs) model is developed for three stages, including YOKE offloading operation, YOKE dropping operation, and equipment recovery operation, and then predicts the dynamic probability of failure during the disconnect operations. Finally, the prediction, sensitivity, and diagnostic analysis techniques in DBNs are used to simulate the evolution of the whole risk system. Meanwhile, the basic events probabilities were updated based on new evidence, and the most likely causes of accidents were found. Safety control measures are developed to effectively reduce the risks faced by the MNPP in the disconnect operations.

An extended fuzzy bow-tie approach with SLIM to assess risk for anchor dredging in cargo ships

Anchoring is one of the frequent processes undertaken by the crew on-board ship. Improper anchoring has significant consequences, such as anchor dredging, which may pose serious risks to the ship crew, marine environment and commodities. This paper aims to present a robust approach combining bow-tie approach with SLIM (Success Likelihood Index Method) under fuzzy sets theory. Since the fuzzy bow-tie represents a comprehensive quantitative risk assessment (QRA) method, the SLIM predicts the probability of a human error occurring during a specific task's completion. In this context, anchor dredging risk can be calculated for a specific case. This paper's novelty lies in consideration of human error's contribution to risk for ship anchor dredging and combining quantitative and qualitative analysis in maritime risk assessment. The finding of the paper shows that the occurrence probability of anchor dredging risk for cargo ships is 7.31E-02. Besides its robust theoretical background, cargo ship owners, superintendents, safety inspectors, and health, safety, environment and quality (HSEQ) managers can utilise the paper's findings to minimise potential risk and enhance operational safety during anchoring operations.

Electrical fire risk indexing using fuzzy Petri nets

Electrical fires are a significant cause of dwelling fires, but the existing information on electrical fires is often vague and imprecise, making it challenging to develop a comprehensive risk assessment method. To address this problem, this paper proposes a risk assessment method based on Fuzzy Petri nets (FPNs), a modeling tool that is suitable for complex systems under uncertainty. This approach allows for modeling various relationships between risk factors and their respective importance, supplying a flexible and comprehensive way to perform risk assessment. The proposed method involves responding to a yes/no questionnaire based on code recommendations, which allows for the prediction of the failure mode response. Based on the simulation results, it can be evaluated the overall risk, determined the relevance of each electrical issue in a residential distribution system, or assessed the impact of electrical installation improvements and alterations on safety. Despite the complexity of failure modes modeling, this approach offered a practical and straightforward means of identifying potential electrical fire risks.

Overview of Comprehensive Risk Assessment Methods and Hazards Early Warning System for Geological Hazards in the Mountain Area

Many major projects are under construction in the mountain and surrounding areas [...]

Construction and empirical testing of comprehensive risk evaluation methods from a multi-dimensional risk matrix perspective: taking specific types of natural disasters risk in China as an example

Global climate change, continuous economic development and accelerated urbanisation have increased the frequency and complexity of various incidents. Risk assessment is an important means to deal with different crises and incidents. Based on the systematic analysis of the basic connotation, attribute relationship and main contents of risk assessment, this study extends the traditional two-dimensional risk matrix to multi-dimensional risk matrix. On this basis, this study further proposes four comprehensive risk assessment methods, including total ordinal, weighted average, Euclidean distance and two-norm methods. Empirical research was conducted by selecting three types of natural disasters, regional agro-meteorological disasters, geological disasters and forest fires, in 30 related regions in China between 2010 and 2019. The results indicated that compared to the two-dimensional risk matrix, the multi-dimensional risk matrix can intuitively characterise and compare the all-round risk situation of different regions, periods, types and dimensions, which is more helpful for a systematic analysis and risk comparison. All four evaluation methods proposed in this paper proved able to effectively conduct comprehensive regional risk evaluations with consistent results. However, when considering the fitting coefficient between the results obtained by various evaluation methods and the comprehensive evaluation results, it can be found that the accuracy (i.e. fitting coefficient) of Euclidean distance method is significantly higher than that of the other three methods. In the last 10 years, the temporal order of natural disaster risk in China has been more volatile, with Beijing, Shanxi, Tianjin, Hebei, Liaoning, Ningxia, Zhejiang, Shaanxi, Fujian and Gansu experiencing higher volatility in the ranking of natural disaster risk.

A nuclear emergency partition evacuation framework based on comprehensive risk assessment

Nuclear power has incomparable advantages over traditional fossil energy and has become one of major power sources. Meanwhile, the huge losses in nuclear accidents place higher requirements for emergency response. Nuclear emergency evacuation is an effective protective measure to prevent or reduce the public’s exposure to radioactive materials. However, nuclear emergency evacuation is affected by a variety of factors, including environment, resources, transportation, and radiation, etc. It is difficult for decision makers to analyze a large amount of complex information so as to design effective nuclear emergency evacuation schemes. Considering the potential risk and characteristics of emergency traffic evacuation, a partition evacuation framework based on risk assessment is proposed in this paper. First, to deal with nuclear radiation and traffic evacuation vulnerability, a comprehensive risk assessment method is put forward that can be used for potential risk quantification during nuclear emergency evacuation. Second, according to the risk assessment results, this paper proposes a partition evacuation organization strategy and a cell transmission model (CTM) to minimize the exposure risk of during nuclear emergency evacuation. Finally, taking a coastal nuclear power plant in China as the research object, extensive and in-depth analysis is performed. As suggested by the simulation results, the partition evacuation strategy we proposed could effectively reduce the exposure risk by 36.0% and the average delay is shortened by 50.4%. Compared with traditional evacuation strategies, our framework is useful for increasing the nuclear emergency evacuation efficiency and alleviating traffic congestion.

Quantitative risk assessment of typhoon storm surge for multi-risk sources

Typhoon storm surge (TSS) is a complex marine disaster affected by multi-risk sources. Quantitative risk assessment is an important prerequisite for identifying risk areas and designing risk reduction strategies. This paper aims to propose a rapid, accurate, and comprehensive quantitative risk assessment method for TSS under multi-risk sources, including disaster occurrence probability and severity. First, identify the primary risk sources according to the disaster-causing mechanism of TSS. Then, based on the official public data from 1989 to 2020, the dependence structure among multi-risk sources is constructed using Copulas to calculate the probability of each superposition scenario. Meanwhile, build visual scenario databases employing Geographical Information System (GIS) techniques. Subsequently, the extent and depth of inundation are translated into economic risk and population risk using GIS and depth-damage functions. Finally, taking the “Mangkhut” as a case study, the method’s feasibility and accuracy are verified. The results show that the primary risk sources of TSS are storm tide, astronomical tide and coastal waves. The Gumbel Copula is optimal, with OLS (ordinary least squares) and D of 0.0186 and 0.1831, respectively. The probability assessment under different superposition scenarios indicates that the greatest threat of TSS in Guangzhou comes from the storm tide and the astronomical tide. As for the “Mangkhut” case study in Jiangmen City, the assesses occurrence probability is 0.0355%, the accuracy of economic risk assessment (except mariculture) is 95.28%, and the accuracy of population risk assessment is 98.60%. Residences and the disaster-bearing bodies in 0–3 m inundation depth are most severely affected by TSS disasters. Measures such as locating residential and important buildings away from the shoreline (at least 10 km) and ground (above 3 m), formulating disaster emergency plans, and developing the forecast and prevention of storm tides and astronomical tides will help ensure the safety of residents’ life and property. This paper provides an efficient and accurate method, which is of great significance for disaster control, sustainable development, and decision-making.

Developing a risk assessment method for infectious diseases focusing on COVID-19 based on the Delphi method and fuzzy analytical hierarchy process.

Given the coronavirus 2019 (COVID-19) risk, it is essential to develop a comprehensive risk assessment method to manage the risk of the infectious diseases. This study aimed to develop a risk assessment method for infectious diseases focusing on COVID-19. This study was based on the fuzzy Delphi method (FDM) and fuzzy analytical hierarchical process (FAHP) in three steps: (a) designing the preliminary risk assessment algorithm by reviewing the literature, (b) corroborating the designed structure based on the majority opinions of the expert panel and assigning scores to different factors according to the Delphi method, and (c) determining the weight of components and their factors based on the FAHP. The COVID-19 risk index (CVRI) was found to be affected by four components and 19 factors. The four components consisted of the probability of getting sick (5 factors), disease severity (4 factors), health beliefs level (3 factors), and exposure rate (6 factors). The identified components and their relevant factors had different weights and effects on the CVIR. The weights of probability, severity, health beliefs level, and exposure rate components were 0.27, 0.20, 0.14, and 0.38, respectively. The CVRI was found to range from 0.54 to 0.82, defined in three levels. Given the significant effects of identified components, factors, and parameters on the incidence of COVID-19 on the one hand and using the FDM and FAHP on the other, the proposed method can be considered as an appropriate method for managing the risk of COVID-19 and other infectious diseases.

A comprehensive risk assessment method for coal and gas outburst in underground coal mines based on variable weight theory and uncertainty analysis

Coal and gas outburst is one of the main disasters that seriously affect the underground safety production of coal. It is crucial to accurately assess the risk level of coal seam outbursts under different conditions and take effective prevention and control measures to avoid the occurrence of such disasters. To solve this problem, a new assessment method combining variable weight theory and unascertained theory is proposed. Based on qualitative and quantitative risk factors, eight indicators and four classification criteria are constructed. The constant weights (CW) are determined by the fuzzy analytic hierarchy process, while the variable weights (VW) of different parameters by constructing a partitioned variable weight model through the VW theory. Meanwhile, four membership functions of linear (L), parabolic (P), S, and Weibull (W) are proposed to measure the uncertainty level of risk. Based on the calculation of 45 sets of sample data, the differences between the maximum membership principle and the confidence criterion in risk identification were considered, and the optimal hybrid model for the risk evaluation of underground coal seam outburst was derived as VW-P-M. The reliability of the model was determined by further validation of the field data. Finally, the limitations of traditional identification approach are analyzed and the stability of the model under various indicators changes is examined with global sensitivity analysis (GSA). The model fully considers the uncertainty in the outburst risk assessment and the influence of index parameters change on the weight. In addition, it can well solve the risk misjudgment problem caused by low indicators parameters in the production process, providing a reasonable idea and method for the accurate assessment of outburst risk in the early stage of coal mining.

Comprehensive Water Inrush Risk Assessment Method for Coal Seam Roof

In order to prevent coal mine water inrush accidents, it is necessary to appropriately assess the water abundance of coal mines based on drilling and geophysical data. This paper studied a comprehensive risk assessment method of water inrush. First, a water inrush risk index was proposed based on the analytic hierarchy process-entropy method (AHP-EM) and the water-rich structure index was proposed based on the geological data coupled calculation, then weighted two indices above which established the comprehensive water inrush risk assessment method. Secondly, eight factors were chosen as risk control factors of water inrush: core recovery, aquifer thickness, distance from the indirect aquifer to the coal seam, aquiclude thickness, height of water-conducting fracture zone, sand-mud ratio, total layers of aquifer and aquiclude, and the equivalent thickness of sandstone. Finally, the No. 2 coal seam of Dahaize coal mine was taken as the research object, the factors were calculated, and a comprehensive water inrush assessment model was constructed. With site investigation and observation, the water inrush risk assessment model of the No.2 coal seam roof is consistent with the actual mining situation, which verifies the validity of the model. In addition, this method was used to evaluate the water-richness of the weathered bedrock fractured aquifer in the Zhangjiamao coal mine. The practical application of the two mines has verified the generality of the approach. The research could provide scientific assistance for mine water hazard mitigation and mining safety.

Risk identification and quantitative assessment method of offshore platform equipment

Equipment failure risk identification and risk assessment are essential part of offshore platform equipment integrity management. Realizing the risk identification and quantitative assessment of offshore platform equipment and failure modes will help to formulate more reasonable risk management measures. However, the previous methods are not enough to support precise risk assessment of offshore platform equipment. Therefore, this paper proposes a new quantitative risk assessment method based on fuzzy set theory, gray correlation analysis and fuzzy Borda method. This paper creatively proposed the approach, which integrates the solid expressive ability of the fuzzy set theory to vagueness and uncertainty information, the strong point of GRA method in studying the dependence of failure modes, and the advantage of FBM for aggregating experts’ diversity evaluations. Based on the above integrated approach, the proposed risk assessment model can favorably capture and aggregate diversity evaluations of FMECA team members. In addition, the effectiveness of this method is verified by the risk assessment of offshore platform equipment. The new method solves the problem existing in the quantitative risk assessment of multiple risks and multiple FMECA reports. This comprehensive quantitative risk assessment method can screen out high-risk failure modes and essential components in a system, and provide a reference for maintenance decision-making of complex industrial systems. This paper is conducive to promote the application of PHM, RCM and AIM in high-risk industries such as oil and gas production.

Ecological risk assessment of toxic metal(loid)s for land application of sewage sludge in China

Sewage sludge, including those after biological or thermochemical treatments, has the potential to be used as fertilizers for recycle of resources. However, its potential ecological risk is also of great concern to policy making. This study employed comprehensive ecological risk assessment (ERA) methods to evaluate the risk caused by the toxic metal(loid)s in sewage sludge throughout China. The conventional geo-accumulation index and potential ecological risk index revealed that cadmium (Cd) and mercury (Hg) were of significant concern in treating sewage sludge before land application, but chromium (Cr) and zinc (Zn) were preferred by potential affected proportion (PAF) and overall risk probability (ORP) of species sensitivity distribution (SSD). Because SSD considered both the community and the ecotoxicity of toxic metal(loid)s, it was more advantageous and promising in assessing ecological risks caused by land application of sewage sludge. Based on the predicted no-effect concentration (PNEC) of toxic metal(loid) calculated by hazardous concentration that cause death of 50% of species (HC50) by SSD, the maximum allowable disposal amount (MADA) of sewage sludge in the whole China indicated that chromium (Cr) should be totally eliminated because of its high risks in the present background soil. After excluding Cr, the MADA of sewage sludge in China was 3.24 × 106 t and 6.47 × 107 t under land application scenarios with high and low ecological risks, respectively. Additionally, the MADA could be increased by mixing sewage sludge with deeper soil in wider areas. This study emphasized that local laws and regulations on land application of sewage sludge and the subsequent ERA system need to be addressed in the future.

Improved urban flood risk assessment based on spontaneous-triggered risk assessment conceptual model considering road environment

Urban flood risk assessment is an important tool for urban disaster management. The current research mainly considered area itself as the evaluation object. Urban road networks are extremely vulnerable to floods as a basis for all socio-economic activities in the city. However, most studies on road environmental risk assessment only took road itself as the evaluation object and did not consider potential regional system risks such as traffic jam caused by road inundation. Based on this, this study proposes a spontaneous-triggered risk assessment (STRA) conceptual model that comprehensively considers the spontaneous risk (SR) caused by the subregional hazard, socio-economic exposure, and triggered risk (TR) from the cross-subregional traffic jam or interruption caused by the road inundation in the evaluated subregion. Taking Haidian Island in Haikou as an example, six indices were selected for the SR assessment based on the combined weight-gray fuzzy comprehensive risk assessment method. The maximum mean inundation depth of road (RMD), maximum inundation duration of road (RID), road betweenness centrality (RBC), and number of road bus lines (RBL) were selected for the TR assessment. Total flood risk (FR) of the study area was obtained by combining the two. The results indicate that, compared with the traditional SR, the highest and higher risk subregions are more concentrated in the study area center, and the risk of the outer ring subregions is reduced overall after considering the TR. According to statistics, the FR level of 68 subregions is lower than the SR level, most of which are in the outer ring of the study area, and the FR level of 17 subregions is higher than the SR level, most of which are located around the intersection of Haidian Fifth Road and People Road. The study outcomes provide a novel approach for flood risk assessment.

Assessment of Groundwater Contamination Risk in Oilfield Drilling Sites Based on Groundwater Vulnerability, Pollution Source Hazard, and Groundwater Value Function in Yitong County

Oilfield drilling sites are the potential dispersive pollution source of groundwater, especially to shallow groundwater. The pollution risk assessment in these areas is an important reference for effective groundwater management and protection. The vulnerability assessment alone is not sufficient for groundwater contamination risk assessment. In this study, we developed a comprehensive groundwater pollution risk assessment method for oilfield drilling sites that combine groundwater vulnerability, pollution source hazard, and groundwater value function to produce a more comprehensive result. Consider the oilfield drilling area in Yitong County of Jilin Province, China, as an example. Thematic maps of the three aspects (groundwater vulnerability, pollution source hazard, and groundwater value function) were generated in ArcGIS environment to assess the contamination risk of groundwater in quaternary pore unconfined aquifer. The results show that 9.92% of the study area is characterized as being at high risk. These areas are mainly distributed around the center position of the oil drilling site, floodplains, and the reservoir. The moderate risk area accounts for 21.04% of the total area. It is distributed in the first-level terrace, mainly because of the high function value of groundwater. The remaining 69.04% of the study area is characterized as none and mild risk, mainly distributed in the valleys and terraces. This integrated groundwater contamination risk assessment method is suited for comparative assessment of multiple-point sources of contamination at a regional scale. Finally, the groundwater contamination risk grade distributed in this area provides a reference for effective protection and sustainable supply of groundwater in the oilfield drilling area.

A Comprehensive Risk-Assessment Method for Prefabricated Buildings Using EPC: A Case Study from China

The prefabricated building has been proven to be an effective approach for enhancing the sustainability of the construction industry. In recent years, the Chinese government has promulgated a series of policy documents to promote the advancement of prefabricated buildings. However, in practice, there are still numerous problems related to design, production, and construction, as well as the coordination between various stages. This study aimed to fill the gap in research regarding the application of EPC (Engineering–Procurement–Construction) in prefabricated buildings in China. As most of the risks of projects are borne by general contractors in the EPC mode, the risks faced by prefabricated building projects using EPC were systematically analyzed in this study from the perspective of general contractors. After learning about the risks of assembly construction in different countries, this study conducted a questionnaire survey to establish an evaluation system, and a comprehensive evaluation method was put forward to determine the weight of each indicator. Furthermore, an evaluation model based on grey–fuzzy theory was developed in this study, which was applied to a real project in Nanjing, China. The results indicated the applicability of the established evaluation system and model and determined the risk level of the project. Additionally, in this case study, it was found that construction and design were the major factors determining the risk level of the project. This study contributes to the body of knowledge regarding the integration of EPC in prefabricated buildings, which has practical application value for general contractors when conducting risk assessments.