A new pre-assessment model for failure-probability-based-planning by neural network

At present, the prediction of failure probability is based on the operation period for laid pipelines, and the method is complicated and time-consuming. If the failure probability can be predicted in the planning stage, the risk assessment system of gas pipeline will be greatly improved. In this paper, the pre-laying assessment model is established to minimize risk of leakage due to piping layout. Firstly, Fault Tree Analysis (FTA) modeling is carried out for urban natural gas pipeline network. According to expert evaluation, 84 failure factors, which can be determined in the planning stage, are selected as the input variables of the training network. Then the FTA model is used to calculate the theoretical failure probability value, and the failure probability prediction model is determined through repeated trial calculation based on BP (Back Propagation Neural Network) and RBF (Radial Basis Function), for obtaining the optimal network parameter combination. Finally, two prediction models are used to calculate the same example. By comparing our pre-assessment model with the theoretical prediction consequences of the fault tree, the results show that the error of RBF prediction model can be close to 3%, which proves the validity and correctness of the method.     

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.     

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.     

Risk assessment of safety level in university laboratories using questionnaire and Bayesian network

Accidents in university laboratories not only create a great threat to students’ safety but bring significant negative social impact. This paper investigates the university laboratory safety in China using questionnaire and Bayesian network (BN) analysis. Sixteen influencing factors for building the Bayesian net were firstly identified. A questionnaire was distributed to graduate students at 60 universities in China to acquire the probability of safe/unsafe conditions for sixteen influencing factors, based on which the conditional probability of four key factors (human, equipment and material, environment, and management) was calculated using the fuzzy triangular theory and expert judgment. The determined conditional probability was used to develop a Bayesian network model for the risk analysis of university laboratory safety and identification of the main reasons behind the accidents. Questionnaire results showed that management problems are prominent due to insufficient safety education training and weak management level of management personnel. The calculated unsafe state probability was found to be 65.2%. In the BN analysis, the human factor was found to play the most important role, followed by equipment and material factor. Sensitive and inferential analysis showed that the most sensitive factors are personnel incorrect operation, illegal operation, and experiment equipment failure. Based on the analysis, countermeasures were proposed to improve the safe management and operation of university laboratories.     

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.     

Simulation of scenario characteristics of LPG tank explosion accident and its contribution to emergency planning: A case study

Leakage and explosion of hazardous chemicals during road transportation can cause serious building damage and casualties, and adoption of highly-efficient emergency rescue measures plays a critical role in reducing accidental hazards. Considering a liquefied petroleum gas (LPG) transport tanker explosion accident that occurred in Wenling, Zhejiang Province, China on June 13, 2020 as example, this study proposes a risk assessment framework. This framework recreates the leakage and explosion of the accident process using FLACS v10.9, suggests plans for evacuation, describes the rescue areas of different levels, and explores the influence of environmental factors on the evacuation and rescue areas. The results show that simulated and predicted distributions of fuel vapour cloud concentration and explosion overpressure can provide a reference basis for rapid rescue activities; the characterization of the dynamic effects of wind speed, wind direction, and temperature with respect to the evacuation and rescue areas can be used as theoretical support for on-site adjustment of rescue forces. The role of obstacles can prevent the expansion of the evacuation areas under low wind-speed conditions, and the presence of highly congested obstacles determines the level of the rescue area. The results obtained are important for the risk analysis and the development of emergency rescue measures in case of explosion accidents associated with transportation of hazardous chemicals on high-hazard and high-sensitive road sections.     

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.     

海洋风电场水下噪声评估与管理研究

总结了海洋风电场建设中水下噪声的主要类型与声学特性,基于国内外水下噪声对海洋生物影响的最新研究成果,分析了海洋风电场噪声对生态环境的可能影响,尤其是近岸海域海洋风电施工期冲击式打桩噪声对海洋生物的影响。在此基础上,参考《海上风电工程环境影响评价技术规范》的相关内容,提出了海洋风电场水下噪声测量与评估方法,以及控制与降低噪声的措施建议。     

水生态环境质量评价方法及在黄河流域的应用进展

开展水生态环境质量评价方法研究,建立合适的河流健康评价体系是解决河流健康问题的前提和实现河流健康管理的重要手段。黄河自上而下生态环境现状迥异,水生态环境脆弱,寻求一种或多种适合黄河流域水生态环境质量的评价方法具有重要意义。该文介绍了国内外水生态环境质量评价方法及在黄河流域的应用进展,总结了鱼类生物完整性指数(F-IBI)、底栖无脊椎动物完整指数(B-IBI)、着生藻类生物完整性指数(P-IBI)及水生态环境质量综合评价法的主要指标,以及黄河流域不同区域生物种类的评价指标,分析了各评价方法优缺点及应用范围,并根据目前研究基础评述了黄河流域水生态环境质量评价存在的问题,对黄河流域水生态环境质量评价方法、指示生物的选择及水生态环境质量综合评价法的研究等提出了具体建议。     

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.