Dynamic risk assessment for underground gas storage facilities based on Bayesian network

Loss of the underground gas storage process can have significant effects, and risk analysis is critical for maintaining the integrity of the underground gas storage process and reducing potential accidents. This paper focuses on the dynamic risk assessment method for the underground gas storage process. First, the underground gas storage process data is combined to create a database, and the fault tree of the underground gas storage facility is built by identifying the risk factors of the underground gas storage facility and mapping them into a Bayesian network. To eliminate the subjectivity in the process of determining the failure probability level of basic events, fuzzy numbers are introduced to determine the prior probability of the Bayesian network. Then, causal and diagnostic reasoning is performed on the Bayesian network to determine the failure level of the underground gas storage facilities. Based on the rate of change of prior and posterior probabilities, sensitivity and impact analysis are combined to determine the significant risk factors and possible failure paths. In addition, the time factor is introduced to build a dynamic Bayesian network to perform dynamic assessment and analysis of underground gas storage facilities. Finally, the dynamic risk assessment method is applied to underground gas storage facilities in depleted oil and gas reservoirs. A dynamic risk evaluation model for underground gas storage facilities is built to simulate and validate the dynamic risk evaluation method based on the Bayesian network. The results show that the proposed method has practical value for improving underground gas storage process safety.     

An integrated EDIB model for probabilistic risk analysis of natural gas pipeline leakage accidents

Natural gas pipeline construction is developing rapidly worldwide to meet the needs of international and domestic energy transportation. Meanwhile, leakage accidents occur to natural gas pipelines frequently due to mechanical failure, personal operation errors, etc., and induce huge economic property loss, environmental damages, and even casualties. However, few models have been developed to describe the evolution process of natural gas pipeline leakage accidents (NGPLA) and assess their corresponding consequences and influencing factors quantitatively. Therefore, this study aims to propose a comprehensive risk analysis model, named EDIB (ET-DEMATEL-ISM-BN) model, which can be employed to analyze the accident evolution process of NGPLA and conduct probabilistic risk assessments of NGPLA with the consideration of multiple influencing factors. In the proposed integrated model, event tree analysis (ET) is employed to analyze the evolution process of NGPLA before the influencing factors of accident evolution can be identified with the help of accident reports. Then, the combination of DEMATEL (Decision-making Trial and Evaluation Laboratory) and ISM (Interpretative Structural Modeling) is used to determine the relationship among accident evolution events of NGPLA and obtain a hierarchical network, which can be employed to support the construction of a Bayesian network (BN) model. The prior conditional probabilities of the BN model were determined based on the data analysis of 773 accident reports or expert judgment with the help of the Dempster-Shafer evidence theory. Finally, the developed BN model was used to conduct accident evolution scenario analysis and influencing factor sensitivity analysis with respect to secondary accidents (fire, vapor cloud explosion, and asphyxia or poisoning). The results show that ignition is the most critical influencing factor leading to secondary accidents. The occurrence time and occurrence location of NGPLA mainly affect the efficiency of emergency response and further influence the accident consequence. Meanwhile, the weight ranking of economic loss, environmental influence, and casualties on social influence is determined with respect to NGPLAs.     

Dynamic-risk-informed safety barrier management: An application to cost-effective barrier optimization based on data from multiple sources

An integrated approach for performance assessment and management of safety barriers in a systemic manner is needed concerning the prevention and mitigation of major accidents in chemical process industries. Particularly, the effects of safety barriers on system risk reduction should be assessed in a dynamic manner to support the decision-making on safety barrier establishments and improvements. A simulation approach, named Simulink-based Safety Barrier Modeling (SSBM), is proposed in this paper to conduct dynamic risk assessment of chemical facilities with the consideration of the degradation of safety barriers. The main functional features of the SSBM include i) the basic model structures of SSBM can be determined based on bow-tie diagrams, ii) multiple data (periodic proof test data, continuous condition-monitoring data, and accident precursor data) may be combined to update barrier failure probabilities and initiating event probabilities, iii) SSBM is able to handle uncertainty propagation in probabilistic risk assessment by using Monte Carlo simulations, and iv) cost-effectiveness analysis (CEA) and optimization algorithms are integrated to support the decision-making on safety barrier establishments and improvements. An illustrative case study is demonstrated to show the procedures of applying the SSBM on dynamic risk-informed safety barrier management and validate the feasibility of implementing the SSBM for cost-effective safety barrier optimization.     

Methodology for Natech coupling risk assessment using correlative multi-criteria decision-making method

When a natural disaster occurs, it may damage multiple industrial facilities in a certain area at the same time, and the resulting Natech events may have an impact on the surrounding industrial facilities, generating coupling risk. In this study, the assessment of Natech events coupling risk is conducted using the method of correlated multi-criteria decision-making, and the knowledge of fuzzy measures is introduced to solve the uncertainty problem in Natech coupling risk. Natech Coupling Risk Index is constructed to involve physical and functional facilities. The concept of equivalent population is proposed to compare the risks generated by physical facilities and functional facilities. And economic indicators are added to calculate the comprehensive risk value. The purpose of this contribution is to enable local government managers to use their expertise and resources and the existing risk assessment of the plants themselves and rely on the scoring of experts limitedly to quickly and easily identify potential high Natech risk areas. In the calculation process of coupling risk, the government can also take the lead to promote information communication between different plants and other industrial subjects. The proposed method was applied in a realistic chemical industry area in Guangzhou, China and in a hypothetical town. The result shows that the physical risk may be transferred to the population and economy through the coupling between industrial facilities and the functional link between functional facilities and population and economy.     

A thermal hazard risk evaluation of emulsion polymerisation and vinyl acetate monomers in the latex manufacturing process

Latex is extensively used in industrial products. However, completing some processes at scale leads to unacceptable levels of risk that need to be quantified and mitigated. Systemic risks must be eliminated wherever possible, and safety takes priority over efficiency and quality. To assess the process risks accurately, four raw materials were examined in this study: polyvinyl acetate (PVA), latex process-initiator-ammonium persulfate (APS) and hydrogen peroxide (H₂O₂), and vinyl acetate monomer (VAM). The physicochemical composition of the PVA latex process was determined via calorimeters, including differential scanning calorimetry (DSC) and vent sizing package 2 (VSP2). The calorimetry results showed that the protective colloid was a critical component in the polymerisation reaction. In addition, when adding initiators to the system, it is vital to observe the normal ratio of materials and keep the stirring system operating. The scenario system also simulated the effects of shutting down various inhibitory programs, including the build-up of free radicals that could result in a runaway reaction when the initiator was added in excess. On the other hand, the result of the risk matrix displayed as a medium level, indicating that although the probability of an accident is low, the resulting severity is at disaster level. As a result, this study provides process safety engineers with a reliable frame of reference for assessing the potential dangers in the PVA latex manufacturing process.     

淮河流域安徽段水体和沉积物微塑料赋存特征及风险评估

为探究淮河流域安徽段水体与沉积物微塑料赋存特征及生态风险级别,采用野外采样、体式显微镜、扫描电镜、傅里叶红外光谱（FTIR）以及风险指数（H）和污染负荷指数（PLI）模型等方法,分析了流域水体和沉积物微塑料现状,并进行了微塑料生态风险评估.结果表明,流域各点位微塑料检测率为100%,表层水与沉积物微塑料平均丰度分别为（39800±3367） n ·m^-3和（5078±447） n ·kg^-1,下游微塑料平均丰度要高于上游和中游.水体和沉积物微塑料粒径以20~150 μm为主,占比分别为82.96%和80.77%.微塑料形状主要为纤维（水体76.05%、沉积物84.53%）、薄膜（水体21.83%、沉积物15.43%）和碎片（水体2.12%、沉积物0.04%）.水体和沉积物中微塑料主要以透明颜色为主,占比分别为63.31%和83.69%.水体和沉积物主要以聚乙烯（水体65.74%、沉积物80.62%）和聚丙烯（水体18.43%、沉积物9.71%）为主,微塑料主要来源于农业薄膜、废弃渔具渔网和港口人为废弃的塑料袋.微塑料风险指数（H）模型评估表明部分点位风险指数较高,淮河流域安徽段微塑料风险等级为Ⅱ级,污染负荷指数（PLI）模型评估表明流域地表水体和沉积物总体上生态风险较低.     

飞机实验室气候试验风险识别及分析

目的 研究飞机实验室气候试验过程中风险的识别及分析问题.方法 根据飞机实验室气候试验流程,针对试验设计、试验准备、试验实施和试验确认等阶段进行风险识别和分析.结果 及结论识别并分析出实验室气候试验各阶段的风险,并在国内首次某民机实验室气候试验中得到应用.     

北江中上游地表水和沉积物中PAHs和PCBs污染特征和风险评估

采用气相色谱-质谱法（GC-MS）测定了北江中上游流域地表水和沉积物样品中多环芳烃（PAHs）和多氯联苯（PCBs）类污染物的含量,分析了PAHs和PCBs的污染水平和空间分布,并评估了污染物的健康风险和生态风险.结果表明,16种PAHs单体在所有水样和沉积物样品中均被检出,检出范围分别为41.82~443.04 ng·L^-1和59.58~635.73 ng·g^-1,北江中上游PAHs的污染水平为中、轻度.水中PAHs以二环芳烃和三环芳烃为主,沉积物中以三环芳烃和四环芳烃为主.在水样中检出了17种PCBs,浓度范围0.81~287.50 ng·L^-1,以六氯联苯和七氯联苯为主;沉积物中检出了8种PCBs,含量范围0.13~3.96 ng·g^-1,以五氯联苯和七氯联苯为主.整个调查区域内地表水中PAHs和PCBs的终生致癌风险指数小于10^-4,处于中、低水平;非致癌风险指数均小于1,不存在非致癌风险.采用风险商值（RQ）法对地表水中污染物进行生态风险评价,研究区域内地表水中PAHs和PCBs生态风险总体处于中低风险水平,个别点位存在重度风险的污染物单体,值得引起重视.采用沉积物质量基准法（SQGs）对沉积物中污染物进行生态风险评估,沉积物中PAHs和PCBs均处于较低的生态风险水平.     

水生生物对三唑磷的物种敏感度分布研究

针对水环境中日益严重的有机磷农药污染问题,选择广泛使用的三唑磷作为研究对象,利用其对水生生态系统中不同营养层次生物物种的半数效应浓度(median effective concentration, EC₅₀),建立了基于对数-逻辑斯蒂分布的水生生物物种敏感度分布(species sensitivity distribution, SSD)模型,并采用概率图和吻合度检验方法对该模型进行了检验和评价.结果表明,水生生物对三唑磷的 SSD 服从对数-逻辑斯蒂分布,其参数为 α=-0.4788±0.2381,β=0.7546±0.1078.基于该 SSD 模型,获得三唑磷的 5% 危害浓度(hazardous concentration for 5% of the species, HC₅)值为 1.992×10^-3 mg/L,并推导出三唑磷的最大浓度基准值(criteria maximum concentration, CMC)值为 9.96×10^-4 mg/L.对 HC₅、CMC 与单一物种的安全浓度的比较研究指出,基于 SSD 方法制定环境质量标准更为严格,也更接近于真实的生态环境.另外,根据渤海莱州湾海域中三唑磷的监测数据,预测了其对物种的潜在影响比例(potentially affected fraction, PAF)为 0.36%,对该水域生态环境的影响处于较低风险水平.     

基于不确定性分析的健康环境风险评价

基于对水源地石油污染等现场调查数据为基础,选取典型污染物苯,利用可传递参数差异的蒙特卡罗技术方法,分析了乙烯厂不同分区苯污染经过呼吸和饮水暴露途径造成人体健康风险的不确定性,量化不确定性因素影响的A地区人体健康风险水平.结果表明,裂解装置区是苯污染影响人体健康风险水平的主要来源,产生的健康风险水平均值为1.17×10^-4,而其他3个分区的影响较小;所有分区苯污染对A地区产生的人体健康总风险均值为1.18×10^-4,大于美国环保局人体健康风险建议值10^-6,对人体健康已产生影响;受不确定性因素影响,根据不同的人体健康可以承受的风险水平限值,污染对人体健康产生影响的概率存在差异.因此量化不确定性对风险水平的影响,可为污染场地的风险管理和修复行动提供科学依据.