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.     

A data-driven narratives skeleton pattern recognition from accident reports dataset for human-and-organizational-factors analysis

Accidents in the process industry involve several interacting factors, including human and organizational factors (HOFs). A long-standing obstacle to HOFs analysis is lack of data. Accident reports are an essential data source to learn from the past and contain HOFs-related data, but they are usually unstructured text in a not standardized format. Some studies have explored the extraction of information automatically from accident reports based on Natural Language Processing (NLP) techniques. However, they were not dedicated to HOFs. Risk communication is considered an essential pillar in safety and risk science. This research develops a HOFs-focused risk communication framework based on the NLP techniques that can support risk assessment and mitigation. The proposed approach automatically extracts the target groups oriented “Who, When, Where, Why” (4Ws) information from accident reports.This framework was applied to explore the eMARS database. The results show that the “4Ws” skeleton of narratives has appreciated performance in pattern recognition and holistic information analysis. The graphical representation interfaces are designed to display the features of HOFs-related accidents, which can better be communicated to the sharp-end operators and decision-makers.     

A bayesian network-based safety assessment method for solid propellant granule-casting molding process

The safety of the solid propellant molding process is vital for the stable production of high-quality propellants. Failure events caused by abnormal parameters in the molding process may have catastrophic consequences. In this paper, a Bayesian network (BN) model is proposed to assess the safety of the solid propellant granule-casting molding process. Fault tree analysis (FTA) is developed to construct a causal link between process variables and process failures. Subsequently, expert experience and fuzzy set theory (FST) are used to obtain failure probabilities of the basic events (BEs). Based on the mapping rules, FTA provides BN with reliable prior knowledge and a network structure with interpretability. Finally, when new evidence is obtained, the probability is updated with the diagnostic reasoning capability of BN. The results of the sensitivity analysis and diagnostic inference were combined to identify key parameters in the granule-casting molding process, including curing temperature, vacuum degree, extrusion, calendering roll distance, length setting value, holding time, and polish time. The results of this paper can provide effective supporting information for managers to conduct process safety analysis.     

中国主粮作物生物炭产量效应的Meta分析

为定量评估生物炭对主粮作物产量的影响,收集了公开发表的116篇相关文献,共866对数据,采用Meta分析法定量分析了生物炭对我国主粮作物产量的影响及其影响因子,同时构建结构方程模型(SEM)进一步解释了因子间的交互关系.结果表明,与不施用生物炭相比,生物炭施用后可改善主粮田土壤理化性质,提高主粮作物产量,平均增产率为8.77%.其中,当生物炭pH为7～8时,平均增产率最大,可达26.49%;其C/N<60时,平均增产率为13.73%,显著高于C/N≥60的平均增产率.将生物炭施入酸性或中性土壤中,更能发挥其增产效应.当施炭量为10～20 t·hm^-2时,小麦和玉米的平均增产率最大;施炭量为15～25 t·hm^-2时,水稻平均增产率最大.但是,不同施炭水平的水稻增产率相近,可考虑损失部分产量,适当减施以兼顾经济效益.此外,生物炭增产效应会随施用年限增加而不断减弱,一般3 a后增产不显著.SEM表明生物炭施用量不仅直接影响主粮作物产量,还通过改善土壤肥力间接影响主粮作物产量,而生物炭C/N和pH仅通过改善土壤肥力影响主粮作物产量.因此,今后...     

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.     

基于面积-高程积分的地下水动态分析——以泾惠渠灌区为例

为了研究泾惠渠灌区的地下水动态特征,探讨面积-高程积分在地下水动态分析中的可行性,利用ArcGIS空间分析工具计算了灌区地下水面积-高程积分数据,绘制了不同时期的地下水面积-高程积分曲线,分析了灌区地下水水位与储存量动态特征。结果显示:1978?—?2012年,泾惠渠灌区地下水面积-高程积分值为0.46、0.44、0.38、0.39,表明地下水水位与储存量整体呈下降趋势;1991?—?2012年,410.00?—?446.19 m水位区间面积由1978年的2.54下降为0,342.51?—?360.00 m水位区间面积多年持续增加,中等水位区间存在演化差异性,反映出不同时期地下水开发强度具有空间变异性;以1978年为基准,至2012年地下水储存量减少约7.08×10~8 m~3;降水、地表水引水量、人工开采是影响泾惠渠灌区地下水动态的重要因素,补排失衡是引起灌区地下水储存量下降的主要原因。研究表明:面积-高程积分曲线可以表征地下水水位空间结构特征和储存量的变化情况,利用面积-高程积分值能够近似估算地下水储存量变化量,证明了面积-高程积分在地下水动态研究中具有一定的实用性。     

贵阳市道路灰尘和土壤重金属来源识别比较

通过对89个城市土壤样和78个道路灰尘样中重金属含量的对比,利用多元统计方法识别研究区的元素来源.结果显示道路灰尘元素含量一般高于土壤.就均值而言,灰尘中Hg、Cd、Pb、Cu、Cr含量超过土壤中相应元素含量,灰尘中Zn含量与土壤中Zn含量相当,只有灰尘中As含量略低于土壤.灰尘中元素含量都高于中国和贵州表层土壤背景值,土壤中元素含量除Pb外都高于中国和贵州表层土壤背景值.Cd,Cr,Pb,Hg,Cu和Zn含量较高主要是受人为因素的影响.贵阳市道路灰尘和土壤中8种元素有着不同的来源.相关分析、主成分分析表明交通排放等人为因素是重金属主要来源,外来客土也是重金属重要来源;灰尘Pb主要来源于交通排放和钢铁厂;而土壤Cr具有复合污染的特征,主要来源于外来客土.     

含缺陷圆轴结构极限承载规律研究

目的 研究车辆传动轴在受损情况下极限承载能力的变化规律。方法 在圆轴上预制缺陷,并对含缺陷圆轴结构承受扭转载荷的能力进行试验和数值模拟研究。结果 当圆孔缺陷深径比保持不变时,圆轴极限扭矩下降比随圆孔缺陷孔径比的增加而减小;当圆孔缺陷孔径比保持不变时,圆轴极限扭矩下降比随圆孔缺陷深径比的增加而减小。当深径比大于0.4时,圆轴极限扭矩下降比与圆孔缺陷孔径比近似呈负线性相关。当缺陷孔径比大于0.4、深径比大于0.2时,圆轴最大扭角减小为15°~35°,各存在缺陷的圆轴的最大扭角差距不大。结论 圆轴扭转失效时,其最大扭角、极限扭矩与圆孔缺陷孔径比、深径比整体均呈负相关趋势。在孔径比和深径比逐渐增大的过程中,极限扭矩呈近似线性关系逐渐降低,而最大扭角先急剧减小,后逐渐趋于平稳。     

泰山云雾水中多环芳烃的特征与来源分析

于2008年10月18日~11月26日在泰山采集云雾水样品,分析了泰山云雾水中PAHs的含量特征及其与气象条件和pH值、电导的相互关系.结果表明,泰山云雾水中菲含量最多,芴和苊的含量次之;云雾水样品中PAHs浓度与气温有很好的相关性.应用特征分子比值法和因子分析法对云雾水中PAHs的来源进行解析,得出泰山云雾水中PAHs的主要来源为煤炭燃烧源,石油源的贡献相对较小.