Location selection of emergency supplies repositories for emergency logistics management: A variable weighted algorithm

With the development of the city, the number of establishments that are proposed or under construction is increasing year by year, and if they are industries that handle flammable, explosive, toxic, harmful, and dangerous substances, the public safety will face great threats, which will bring great challenges to emergency rescue work. Therefore, providing reasonable solutions to the problem of location selection of emergency supplies repositories are necessary for improving the emergency response efficiency in chemical industrial parks. A mathematical model for location selection of emergency supplies repositories in emergency logistics management are presented considering more actual factors. The optimization objectives of the model are to minimize total transport length and cost. And then a Variable Weighted Algorithm is designed to solve the model, where an auxiliary function was constructed with different methods of building weighting factors based on the theory and method of solving multi-objective optimization problems in operational research. Simulation results show the effectiveness and feasibility of the models and algorithms presented in this paper.     

基于统计学方法的南方某市管网水水质特征研究

为综合解析南方某市管网末梢水水质的时空变化特征、识别主要响应指标及指标间相关性,以该市近4年供水管网末梢水水质监测数据为研究对象,利用主成分分析法和对应分析法对管网末梢水质进行了特征研究。主成分分析法评价结果表明:该市管网末梢水年度总体水质存在差异,其中以2016年为最佳;夏秋季节更易发生水质异常现象,5~9月应加强管网末梢水水质管控;区域上看已完成深度处理改造的梅林水厂供水覆盖区管网末梢水水质最优,南山水厂供水覆盖区管网末梢水水质最差;水质指标硫酸盐、氯化物、硬度之间,Fe、浊度、总氯之间具有相对其他水质指标更高的相关性。对应分析法结果表明:管网末梢水水质主要响应指标可重点关注Fe、浊度、耗氧量、总氯和硫酸盐;其中Fe、浊度、耗氧量呈正相关性强,上述指标与硫酸盐、总氯呈负相关性。     

Hierarchical pre-positioning of emergency resources for a chemical industrial parks concentrated area

Accidents in chemical industrial parks always cause fateful damage which can be reduced greatly by providing emergency resources sufficiently and timely. One effective way to enhance the emergency response capacity and agility is by pre-positioning of emergency resources for the potential accidents. The Yangtze River Delta of China is a large region where a large number of chemical industrial parks are concentrated. According to the distributing characteristics of demand points in this region, a mathematical model of hierarchical pre-positioning of emergency resources is proposed to ensure that accidents in all chemical industrial parks in this region can be responded timely and effectively. Considering accident domino effect and minimizing the total cost, the model gives optimal decisions of pre-positioning emergency resources, including the location and inventory of depots. The innovative hierarchical pre-positioning method greatly reduces the total cost in the premise of sufficient preparation for supplying emergency resources. Finally, in a visual graph of the Yangtze River Delta, the model is applied and the result shows its applicability.     

A Bayesian network-based approach for the assessment and management of ageing in major hazard establishments

Currently, there is an increasing attention towards ageing of industrial equipment, as the phenomenon has been recognised as a cause of severe accidents, recorded in the last years in many process establishments. Recent studies described ageing through a number of key-factors affecting the phenomenon by accelerating or slowing it down. The Italian Competent Authority for the prevention of chemical accidents (Seveso III Directive) adopted a short-cut method, accounting for the assessment of these factors, to evaluate the adequateness of ageing management during inspections at Seveso sites. In this paper, a Bayesian Network was developed, by using the data gathered during the first application of the short-cut method, with the aim to verify the robustness of the approach for ageing assessment and the validity of the a priori assumptions used in assessing the key-factors. The structure of the Bayesian network was established by using experts’ knowledge, whereas the Counting Learning algorithm was adopted to execute the parameter learning by means of the software Netica. The results showed that this network could effectively explore the complex logical and uncertain relationships amongst factors affecting equipment ageing. Results of the present study were exploited to improve the short-cut method.     

环境规制、省际产业转移对污染迁移的空间溢出效应

目前我国正在积极地探寻经济增长高质量发展,生态环境与经济持续、稳定的和谐发展至关重要。虽然政府制定了相关的环境治理政策,但我国环境治理整体效果仍然欠佳。自从分税制改革以来,地方政府为了获得较高经济效益,会放松对环境管理,导致环境治理高投入低成效。同时,由于区域经济发展不平衡导致政府在制定相关环境治理政策时带有区域性特点,迫使高污染高能耗企业迁移至环境规制相对薄弱的地区,由此产生污染迁移的现象。基于此,对2003—2017年30个省区市(港澳台和西藏除外)环境污染总指数的空间溢出效应进行探讨,构建动态空间杜宾模型研究环境规制、省际产业转移对污染迁移的影响。研究结果表明:①环境规制总体上对环境污染具有显著直接效应且存在正向空间溢出效应,当某省环境规制强度增加,环境污染总指数会降低,从而引起污染向相邻省份转移,造成相邻省份的环境污染总指数上升。②省际产业转移整体上对环境污染具有显著直接效应且存在负向空间溢出效应,当某省的产业转移到相邻省份时,会缓解本省环境污染,却加重相邻省份的环境污染程度。这就需要中央政府加强对于各省区市的环境管控,统筹各区域的联防联治机制。产业转移承接省份在招商引资的过程中不仅要考虑本省环境承载能力和环境治理能力,还要考虑入驻企业自身污染排放处理能力,并将污染排放指数纳入筛选条件。同时,产业转移承接省份要引入企业的生产工艺、技术、研发团队等,运用技术溢出效应提升区域环境治理水平。     

公路网规划环境影响评价中的困难和不确定性分析

首先分析了公路网规划环境影响评价中的困难,即评价方法的不成熟和获取资料的困难;然后重点分析了评价中的公路网规划方案的不确定、环境信息的不确定、空间信息的不确定和环境影响程度的不确定;最后提出了 4种解决困难和降低不确定的方法,即制定公路网规划环境影响评价技术导则,使用基于情景分析的预测方法,广泛开展公众参与以及通过多方协作的方式开展环境影响评价工作.     

改善太仓城区水环境原型调水实验研究及模型建立

为达到改善太仓城区水环境的目的,于2004年4月21日进行了调水实验.调水历时14 h,期间向城区调水21.8万m3.通过对监测点采样,得到水量、水质实测数据.根据实验数据,建立了符合太仓河网的水量水质数学模型,分析了从长江引水对太仓城区水环境的改善程度.同时对不同引水方案情况下城区水环境改善效果,以及截污和清淤对水环境的影响做了分析.研究表明,引水只能短期改善水环境;要根治水环境,必须从源头抓起,进行截污.     

基于网络层次分析法的石油化工设施安全风险评估

为评估石油化工设施的安全风险,提出了一种基于网络层次分析法的安全风险评估模型。在构建石油化工设施安全风险网络层次分析模型的基础上,采用Saaty标度法对安全风险参数进行量化,利用SD软件对安全风险参数进行排序。仿真结果表明,网络层次分析法考虑了安全风险参数之间的相互作用和相互影响,能改进基于线性组合关系的递阶层次分析模型的不足,评估结果可为石油化工企业制定安全风险管理措施提供决策依据。     

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.     

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.