Quantitative Risk Assessment Methods Research Articles

Integrating DMAIC Philosophy and Bow-Tie Model for Quantitative Risk Assessment in Health Care.

Medical risks are considered to endanger patients and impact the health care system. Such iatrogenic risks necessitate hospitals taking a more proactive method to quantitatively analyze medical risk, and then to implement more targeted precautions. To address this problem, a novel quantitative risk assessment framework is proposed and further applied in radiotherapy risk assessment. A framework combining DMAIC (Define, Measure, Analyze, Improve, Control) and bow-tie model is used to assess health care risk. The uncertainty of medical risks is quantified with fuzzy set theory. The impact and the priority of medical risks were classified based on the risk matrix, and then the precautions were implemented to mitigate their impact. A case study of radiation treatment is provided. The probabilities and impacts of risk events for radiation treatment were quantified based on the proposed framework, and risk protection measures were proposed to mitigate the undesired consequence. The proposed framework showing an effective method of quantitative risk assessment of health care. The study also enriches the risk assessment methods in health care by providing a conductive and normalized framework.

Generalized Modular Method of Project Risk Management

The article discusses risk management models and frameworks implemented during the development of multi-user cross-platform distributed IT projects. For this class of pro-jects, the use of quantitative risk assessment methods, rules for absorbing and adding risks, which make it pos¬sible to systematically assess the likelihood of negative events and their impact on each stage of the project, are observed. Authors propose a method of modular risk management, present the main indicators for assessing the progress of the implementation of the i-th module and its operational ma¬nagement, and provide a formula for calculating project efficiency. These calculated indicators can be used to estimate the cost of resources at a certain point in time, estimate the timeframe for completing the module, and decide on the feasibility of further development.

An review of research on liquid hydrogen leakage: regarding China’s hydrogen refueling stations

Hydrogen is regarded as the premier energy source for future sustainability and renewability. However, its distinct physicochemical properties render it prone to explosions in the event of a leak. Therefore, there is a need for more comprehensive research dealing with hydrogen leakage, explosion scenarios, and risk assessment. This paper provides an overview of the current hydrogen policies adopted in China. It reviews the processes of hydrogen refueling station construction and the thermophysical mechanisms of liquid hydrogen leakage. In this regard, the effects of various factors, including leakage rate, leakage time, leakage hole size, wind direction and speed, and building location, on the hydrogen leakage rate are analyzed and evaluated. Additionally, the impacts of different factors on hydrogen explosion overpressure are reported, including hydrogen concentration, wind speed, obstacles, and ignition position, in addition to the current applications of quantitative risk assessment methods in hydrogen refueling stations. Finally, the limitations of current research on liquid hydrogen leakage and explosion accidents are highlighted, along with the shortcomings of current risk assessment methods for liquid hydrogen refueling stations.

Quantitative risk assessment of coal mine gas explosion based on a Bayesian network and computational fluid dynamics

A gas explosion is one of the most serious coal mine accidents. The complexity and dynamics of gas explosion accidents, resulting from both multiple risk factors and time-dependent physical parameters, necessitates the use of risk assessment techniques to analyze the accident. A quantitative risk assessment method is proposed for coal mine gas explosions based on a Bayesian Network (BN) and Computational Fluid Dynamics (CFD). The results show that, in addition to the problems of “low vigilance” and “substandard safety education”, the “irrational design of mine gas extraction” has become another major risk factor at the new stage of development of mine excavation technology. Three typical gas explosion areas are selected to analyze the possible consequences of an accident. Based on the probabilistic risk assessment model, time-dependent physical parameters such as accident conditions, location and time are analyzed. The probability of occurrence of time-dependent risk factors is quantified to calculate the risk values of the consequences of explosion accidents corresponding to different times. The proposed method helps to improve the calculation accuracy of updating the risk probability value over time and provides theoretical support for the risk analysis of coal mine gas explosion accidents.

A case study showing highly traceable sources of bacteria on surfaces of university buildings

University students predominantly spend their time indoors, where prolonged exposure raises the risk of contact with microorganisms of concern. However, our knowledge about the microbial community characteristics on university campus and their underpinnings is limited. To address it, we characterized bacterial communities from the surfaces of various built environments typical of a university campus, including cafeterias, classrooms, dormitories, offices, meeting rooms, and restrooms, in addition to human skin. The classrooms harbored the highest α-diversity, while the cafeterias had the lowest α-diversity. The bacterial community composition varied significantly across different building types. Proteobacteria, Actinobacteria, Firmicutes, Bacteroidetes, and Cyanobacteria were common phyla in university buildings, accounting for more than 90 % of total abundance. Staphylococcus aureus was the most abundant potential pathogen in classrooms, dormitories, offices, restrooms, and on human skin, indicating a potential risk for skin disease infections in these buildings. We further developed a new quantitative pathogenic risk assessment method according to the threat of pathogens to humans and found that classrooms exhibited the highest potential risk. The fast expectation-maximization algorithm identified 59 %-86 % of bacterial sources in buildings, with the human skin as the largest bacterial source for most buildings. As the sources of bacteria were highly traceable, we showed that homogeneous selection, dispersal limitation, and ecological drift were major ecological forces that drove community assembly. Our findings have important implications for predicting the distribution and sources of indoor dust bacterial communities on university campus.

Quantitative microbial risk assessment (QMRA) of the work of manual pit emptiers, commonly known as bayakous.

In Haiti, manual pit emptiers, known as bayakous, face significant health risks. They work by descending naked into latrine pits, exposing themselves to pathogens and contributing to environmental contamination. This study employs the quantitative microbial risk assessment (QMRA) method to evaluate the microbial risks associated with this practice, considering nine prevalent pathogens in Haiti. Three ingestion scenarios were developed: hand-to-mouth contact, ingestion while immersed in excreta, and a combination of both. A sensitivity analysis assessed the impact of input data on study outcomes. The results indicate a high probability of infection and illness during pit emptying operations annually for all scenarios and pathogens. Recommendations include adopting personal protective equipment (PPE) and using a manual Gulper waste pump to eliminate the need to descend directly into the pits, thereby reducing the risk of injury from sharp objects. The study proposes the establishment of intermediate disposal points approximately 5 km from collection sites to deter illegal dumping. National regulations and professionalization of the bayakou profession are suggested, along with awareness campaigns to promote PPE and Gulper pump usage. Addressing these issues is crucial for safeguarding the health of bayakou and public health in Haiti.

Occupational exposure, carcinogenic and non-carcinogenic risk assessment of formaldehyde in the pathology labs of hospitals in Iran

Formaldehyde, a known carcinogenic compound, is commonly used in various medical settings. The objective of this study was to assess the carcinogenic and non-carcinogenic risks associated with occupational exposure to formaldehyde. This study was conducted in the pathology labs of four hospitals in Tehran. Cancer and non-cancer risks were evaluated using the quantitative risk assessment method proposed by the United States environmental protection agency (USEPA), along with its provided database known as the integrated risk information system (IRIS). Respiratory symptoms were assessed using the American thoracic society (ATS) questionnaire. The results indicated that 91.23% of exposure levels in occupational groups exceed the NIOSH standard of 0.016 ppm. Regarding carcinogenic risk, 41.03% of all the studied subjects were in the definite carcinogenic risk range (LCR > 10−4), 23.08% were in the possible carcinogenic risk range (10−5 < LCR < 10−4), and 35.90% were in the negligible risk range (LCR < 10−6). The highest index of occupational carcinogenesis was observed in the group of lab technicians with a risk number of 3.7 × 10−4, followed by pathologists with a risk number of 1.7 × 10−4. Furthermore, 23.08% of the studied subjects were within the permitted health risk range (HQ < 1.0), while 76.92% were within the unhealthy risk range (HQ > 1.0). Overall, the findings revealed significantly higher carcinogenic and non-carcinogenic risks among lab technicians and pathologists. Therefore, it is imperative to implement control measures across various hospital departments to mitigate occupational formaldehyde exposure levels proactively. These findings can be valuable for policymakers in the health sector, aiding in the elimination or reduction of airborne formaldehyde exposure in work environments.

Quantitative risk assessment of gas leakage and explosion in open kitchens and partitioned kitchens

ABSTRACT In recent years, natural gas companies have faced more and more gas supply applications for open kitchens in China. However, natural gas cannot be utilized in open kitchens according to the current compulsory regulations. The numerical models for three typical open kitchen layouts and the corresponding partition kitchen layouts were developed, respectively. The experimental setup of gas leakage and explosion, like a residential kitchen, was established based on the similarity theory. The accuracy and reliability of numerical models have been validated by three sets of experiments. An innovative quantitative risk assessment method was proposed to quantify the integrated risks for the open kitchen layout and the partition kitchen layout. The effectiveness of the proposed risk reduction measures was assessed using a modified LOPA (i.e. Layer Of Protection Analysis). The results show that the integrated risk for the open kitchen layout in different apartments is 1.37 ~ 4.65 times than that for the partition kitchen layouts. The integrated risk of gas leakage explosion in three open kitchen layout arrangements was reduced by 94.8%, 50%, and 94.5%, respectively, by setting two layers of protection. Meanwhile, the increased expense of ¥400 can be generally acceptable for the majority of residential users. The achievements could provide theoretical and technological guidance for gas safety supply in open kitchens.

한국제품 데이터기반의 소비자제품 정량적 리스크평가방법연구

The purpose of this study is to contribute to enhancing consumer safety by researching a quantitative product risk assessment method that allows for annual monitoring of product hazards. The study proposes a method for conducting rapid and straightforward evaluations annually using accident data from the Korea Consumer Agency, product usage survey data, and resident population data. Based on the number of accidents, usage rates, and population, probabilities of occurrences were derived, and severity was calculated based on injuries and affected body parts to perform quantitative evaluations. As a result of the research, 262 consumer products were evaluated using the proposed method, identifying 12 products with severe risk ratings, 6 products with increased risk, and 11 products with decreased risk annually. These evaluation results have the significant advantage of being able to observe changes in product hazards annually. They can be utilized not only for enhancing safety, easing regulations, and consumer education policy formulation but also as foundational data for various sectors including consumers, parents, children, and educators, thereby contributing to raising awareness and policy formulation regarding domestic consumer safety.

Health Risk Assessment from Exposure to Ambient Volatile Organic Compounds (VOCs) at a Truck Tire Factory in the Yangtze River Delta, China

Occupational health risk assessments of exposure to VOCs still need to be extensively studied to improve the safety standards in the industry. Based on the monitoring of organic pollutants at various workstations in a truck tire factory in Jiangsu Province, both semi-quantitative and quantitative health risk assessment methods were employed to assess health risk levels. The findings indicated that VOCs were categorized into five classes, which included alkanes, aromatics, halocarbons, carbon disulfide, and oxygenated volatile organic compounds (OVOCs). The highest concentration of total volatile organic compounds (TVOCs) was found in shaping workshop; alkanes were the most abundant class (74.2%), followed by aromatics (24.02%) and OVOCs (1.96%). Although the results of the semi-quantitative risk assessment showed that most of the organic compounds had low R values, various kinds of VOCs were detected; particularly, many harmful organic compounds (such as toluene, ethyl benzene) were detected in all the sampling sites. The quantitative risk in the calendering and vulcanizing workshop exceeded the acceptable level; both the carcinogenic risk of ethylbenzene in the tire-strip storage room, and trichloroethylene and perchloroethylene in the calendering workshop were unacceptable. Thus, the calendering and vulcanizing processes in rubber tire manufacturing should be priority-controlled processes.

Quantitative risk assessment of a spill fire caused by the continuously leaked fuel in a sealed ship engine room

There are a large number of high-temperature heat sources in a ship engine room. Once the oil leakage occurs, it is likely to be ignited and form a spreading and burning spill fire. In this paper, spill fire experiments are conducted in a model-scale ship engine room to investigate their characteristic parameters. The quantitative models of flame height and thermal radiant surface emission power applicable to such fires are verified by the experimental data. Based on that, the classical quantitative risk assessment method is adopted to assess the risk of spill fires using thermal radiation hazard as the main reference, and a detailed framework for quantitative risk assessment of spill fires in ship engine room is established, which includes hazard identification, probability of failure calculation, consequence assessment, and risk quantification. The possible causes of spill fire accidents are briefly analyzed based on the bow-tie model. In cases where thermal threats above the risk threshold for larger leakage rates (70 mL/min), the probability method outperforms the threshold method in terms of accuracy in risk quantification. Additionally, the variation of thermal radiation with combustion diameter is analyzed, and some recommendations for fire emergency rescue are presented.

A two-stage clustering ensemble algorithm applicable to risk assessment of railway signaling faults

Knowledge graph (KG) modeling constructs a connected network of hazard/fault events by drawing on historical reports, helping extract risk factors and propagation features in railway signaling safety. For the huge graph structure of the knowledge system, efficiently and accurately transforming the event information with text for risk level prediction is the crucial topic of this paper. To establish a quantitative risk assessment method based on KG modeling, we innovatively introduce text clustering technology to intelligently divide the entity short text data set in the KG, assign standardized entity names to the cluster partitions, and then complete the calculation and analysis according to the characteristic parameter formula, greatly reducing the labor and time consumption of data annotation and approximate text repetitive processing. Significantly, a two-stage clustering ensemble algorithm (TSCEA) integrating base clusterer optimization and hierarchical clustering prediction is proposed, whose innovative approach lies in describing sample similarity by the co-association matrix, while considering the contribution discrepancy of samples for decision-making. Specifically, Stage One selects and optimizes various base clusterers with different method kernels, while Stage Two emphasizes the contribution discrepancy of the cluster core and the cluster halo to make the final clustering decision, with the ensemble strategy serving as the bridge between these two. The KG established on field investigation is used to complete the experiment and analysis of the novel algorithm. Another clustering ensemble algorithm (based on a direct weighting strategy) and each base clusterer are applied to verify clustering performance, while the evaluation depends on external indicators. The results indicate that the proposed clustering ensemble algorithm outperforms others in various indicators, significantly improving clustering accuracy and robustness.

Optimization of Enterprise Economic Management Model and Risk Control Based on Marginal Analysis Approach

Abstract As an effective economic decision-making tool in enterprise economic management, Marginal Analysis is crucial to reflect the small change relationship between costs and benefits. This paper aims to develop a multi-objective marginal analysis optimization algorithm (MMAOA) that utilizes marginal analysis to optimize the enterprise economic management model and risk control. This algorithm's improvement of the population initialization method and constraint handling enhances the quality of understanding and search efficiency. In this study, an improved population initialization method is designed to ensure that the population is within the upper and lower limits of the output power. Then the constraints are reasonably handled by the penalty function method and the correction method to enhance the feasibility and robustness of the algorithm. Guided by the concept of Pareto optimality, MMAOA is successfully applied to multi-objective optimization problems, and the algorithm can efficiently generate a set of Pareto optimal solutions under the consideration of equilibrium constraints and inequality constraints, in which the objective function values of certain optimization instances are improved by more than 10%. Following marginal analysis, this study presents the disparity in ROI between the East and West and the three stages of agricultural economic efficiency. This article provides a new optimization tool for enterprise financial management and a quantitative analysis method for risk assessment.

Research on quantitative risk assessment method of dust explosion based on Bayesian network

In order to effectively prevent the occurrence of dust explosion accidents in industrial enterprises and reducing the risk of dust explosion accidents, the article builds dust explosion risk assessment index system for industrial enterprises, taking Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) as theoretical basis and establishes dust explosion risk Bow-Tie Analysis (BT) diagram model. Mapping BT model into Bayesian Networks (BN) reveals the coupling mechanism of dust explosion risk nodes and constructs a generic dust explosion risk assessment BN model, which provides a quantitative assessment of the probability of occurrence of dust explosion accidents. The causative mechanism of dust explosion accidents is investigated by learning risk inference from this model. It is also demonstrated that appropriate safety barrier measures can effectively reduce the probability of accidents, thereby changing the accident level and improving the safety and reliability of the system. Finally, the validity and applicability of the model is verified through empirical analyses. The research results contribute to the scientific prediction of the probability of dust explosion risk and reasoning learning, which provides a scientific basis for enterprises to formulate effective dust explosion safety measures as well as to realize the hierarchical control of dust explosion risk.

Dynamic risk assessment method for urban hydrogen refueling stations: A novel dynamic Bayesian network incorporating multiple equipment states and accident cascade effects

Hydrogen refueling stations are increasingly being built in densely populated urban areas and operating under high temperature and pressure conditions. Therefore, the safety of hydrogen refueling stations has received great attention. In present work, a new dynamic quantitative risk assessment method is established for hydrogen leakage at refueling stations based on Bayesian networks (BN). Firstly, risk factors are identified using a fault tree, considering multiple equipment operating states. A Dynamic Bayesian Network (DBN) is established, and event tree analysis is combined to determine accident consequence probabilities. Furthermore, a Bayesian Domino Model is constructed to assess the impact of accident consequence propagation on the probability and risk of hydrogen leakage accidents. Through a typical case study of an off-site hydrogen refueling station, the practicality of the proposed method is validated, the risk factors and safety barriers, the dynamic evolution of hydrogen leakage probabilities within a three-year period are obtained. The probability of hydrogen leakage in hydrogen station is 2.69 × 10−2 in the first month and 2.45 × 10−2 in the 36th month. Simultaneously, the maximum personal risk value for the first month is 5.07 × 10−4. When the Domino effect is considered, the maximum accident probability is 1.96 × 10−3 is obtained in the first month, and the equipment unit with the greatest impact of the accident is A2. Measures were also proposed to reduce hydrogen leakage risks during the operation of off-site hydrogen refueling stations, with an emphasis on prioritizing safety measures for hydrogen storage bundles and risk mitigation strategies.

Risk assessment of liquid ammonia tanks based on Bayesian network and Probit model

AbstractThis paper presents a quantitative risk assessment method to predict the potential risks of liquid ammonia tanks. The method combines probabilistic prediction and consequence assessment: the former is predicted by Bayesian networks derived from bow‐tie mapping, in which the conditional probabilities are determined by analytic hierarchy process, the latter is calculated based on numerical simulation of accident consequences and Probit probability model. The application results show that the method can be used for quantitative risk assessment of liquid ammonia storage tank, and the Bayesian network model is efficient and stable, which can realize risk prediction, accident causes analysis and risk mitigation analysis. Human errors during production or maintenance and corrosion are the main causes of liquid ammonia leakage. Toxicity has the greatest effect on the risk of liquid ammonia tanks. Risk mitigation measures can significantly reduce individual risk and societal risk. The obtained results provide meaningful guidance for the prevention and risk mitigation strategies of liquid ammonia leakage accidents, so as to improve the safety level of liquid ammonia during storage.

Research Status and Development Prospect of Wellbore Integrity in China

Summary As the exploration and development of oil and gas move into increasingly challenging locations and harsher environments, well integrity becomes more difficult to maintain. High temperatures, pressures, and corrosion can all contribute to wellbore integrity failure. Such failures can have significant financial and environmental consequences, including gas leakage and fluid spills. In this paper, we review the development and technical advancements of wellbore integrity research both in China and abroad and look forward to the development direction of wellbore integrity in China. We provide basic background knowledge for those interested in wellbore integrity and also share the progress and development direction of integrity research for wellbore integrity researchers. Through research and analysis, some conclusions can be drawn. Countries around the world are actively studying wellbore integrity and have developed a large number of standards, especially the United States and Norway, which have the most standards. The most common way to analyze wellbore integrity is to first divide the entire wellbore into different wellbore barrier units according to different standards, such as ISO 16530-1, and then study risk factors and integrity management measures in different units. Mainstream research is mostly carried out around the integrity of casing, cement, and tubing, and many achievements have been made, but the study of packer and downhole safety valve is still on the way. Wellbore integrity risk assessment aims to quantify potential risks and establish risk levels to support decision-making for on-site wellbore integrity control. This is achieved by identifying factors affecting wellbore integrity, establishing an evaluation index system and processing evaluation indicators to determine failure probability and impact consequences. The resulting risk value can be divided into different areas using the “as low as reasonably practicable principle” or a risk matrix graph. However, due to the complexity of the factors involved and the subjectivity of risk classification rules, there are still challenges in promoting the evaluation model and reducing errors in the evaluation results. China should actively promote interdisciplinary integration and respond to the call for “dual carbon goals” to break through the current bottleneck in wellbore integrity research. This can be achieved by promoting the development of quantitative wellbore integrity risk assessment methods, developing supporting evaluation software based on big data, and by tackling the integrity challenges faced by different types of wells and promoting the development of wellbore integrity discipline.

Towards a procedure to manage safety on construction sites of rockfall protective measures

Construction sites represent ones of the most dangerous workplaces, due to the huge number of hazards related to the performed activities that can cause discomfort, health diseases, and even death to workers. These issues might be even more amplified in construction sites of structures aiming at preventing or protecting against natural hazards. Among these lasts, rockfall represents one of the most unpredictable and dangerous. In these sites, the inherent added hazard is represented by the occurrence of the event against which the protection is required to be installed, i.e. the detachment of a rock block. As in the other situations, workers might be aware of the danger to which they are subjected and all the possible measures to mitigate the risk should be implemented. To address these issues and increase safety of workers, this paper proposes a quantitative risk assessment method to compute the probability of death of workers due to the occurrence of a rockfall event in the considered work duration. In addition, preliminary suggestions to improve safety of workers are delineated.

Quantitative microbial risk assessment associated with the use of container-based toilets in Haiti.

A container-based toilet (CBT) is a type of ecological toilet that allows users to compost their feces. During emptying, bucket washing, and composting operations, operators are exposed to microbial risks. This paper aims to evaluate these risks using the Quantitative Microbial Risk Assessment (QMRA) method. Nine pathogens prevalent in Haiti were targeted: Ascaris lumbricoides, Campylobacter spp., Cryptosporidium parvum, Escherichia coli O157:H7, Giardia intestinalis, poliovirus, Salmonella spp., Shigella spp., and Vibrio cholerae. Information regarding pathogens' concentration in feces came from scientific literature data. The exposure scenarios considered were those in which operators accidentally ingested a low dose of feces during the aforementioned operations. A Monte Carlo simulation was conducted to address uncertainties. The results showed that the probability of infection is highly elevated, while the probability of illness is generally moderate or minor, except for poliovirus and Ascaris. Preventive measures can be implemented to reduce these risks during various operations, such as wearing gloves, disposable protective masks, and appropriate clothing. It is up to the political authorities to develop guidelines in this regard and to organize awareness-raising activities with the help of local organizations mandated by the relevant authorities to ensure the safer use of technology by households.

TRANSFORMATION OF VALUES OF THE HIGH TECHNOLOGY PROJECTS FROM A VUCA TO A BANI ENVIRONMENT MODEL

The article is dedicated to the study of impact of a BANI-world conditions to implementation of the high technology industrial projects and in particular of the nuclear industry projects. The purpose of the article is to analyze tendencies of changes of different factors related to the high technology nuclear project implementation against the changing conditions of the environment. The object is the project management methodologies in the BANI environment. The subject is theoretical analysis of the values differentiation in between the VUCA and BANI worlds, key aspects of BANI impacting implementation of the nuclear projects. Tasks to be solved: to analyze the transformation from the VUCA model to the BANI model, to present values and their differentiation as the basis for survival in the new world order, to develop a method for assessing project risks in the BANI environment. Methods: practical empirical analysis of nuclear project risks in comparison with BANI-model forecasts, applied research, project risk management methodology, probability theory. The following results were obtained: the differences between the values of s VUCA and BANI are determined, an understanding of the general changes that have arisen due to the functionality of the environment is provided, the project management methodology applicable in the BANI environment is analyzed, a qualitative and quantitative risk analysis based on BANI projections is implemented on the example of a nuclear project in Ukraine, and the grounds for determining the most influential BANI forecast are proposed. The main results of the research are identification and analysis of values and their differentiation in the process of transformation from the VUCA to the BANI world, proposals for the project management approach which could cover the needs of the nuclear project and the consequences of this transformation. To estimate risks, it was proposed to use qualitative and quantitative methods of risk assessment. The case study of one of the nuclear projects in Ukraine, and a mixed classic-Agile methodology for the management of the nuclear project was performed. Conclusions: risk management of the nuclear projects has to be carried out based on the impact of the BANI-projections to identified risks.