公交车火灾安全及人员疏散分析

公交车作为最常用的交通工具之一,其空间密闭、人员密度大,一旦发生火灾,极易造成群死群伤事故,社会影响恶劣.首先采用鱼刺图分析法(FBF)分析公交车火灾事故发生的原因;再采用事故树分析法(FTA),得出公交车安全门对公交车内人员安全疏散的重要性;在此基础上,以大容量公交车为研究对象,针对不同开门情况设置4个疏散场景,并运用Building Exodus对车内人员疏散情况进行模拟,提出相应建议.结果表明,公交车右侧前门为1.1m、后门为1.Sm,右侧前、后门均为1.Sm,前门、左右两侧后门均为1.5m3种情况下均较原始设计(右侧前、后门均为1.1m)不同程度缩短了人员疏散时间.     

基于可靠性理论的事件树分析方法研究

事件树分析过程中事件树的编制和分析方法缺乏系统性,导致实际运用中事件树的编制缺乏可操作性。从目标系统的选择、环节事件逻辑关系的确定、定量分析中基本数据的来源和确定方法等三个问题进行了系统研究,并以可靠性的相关理论为基础,提出"从控制和影响初始事件发展演化的角度,调查分析对初始事件做出响应的安全功能,按系统工作原理对目标系统进行重构,构建目标系统的功能结构图,画出系统的可靠性框图"入手,对"传统的事件树绘制程序"进行修正,解决了事件树分析过程中目标系统的选择、环节事件逻辑关系的确定以及定量分析基本数据的确定方法等问题。修正后的方案对实现事件树的正确编制和系统分析逻辑更清晰,操作指导性更强。     

中小型在役桥梁安全预警研究

为了准确评估中小型在役桥梁安全状况,提出利用灰色关联故障树分析法对中小型在役桥梁进行安全预警研究。首先建立中小型在役桥梁安全预警故障树;其次采用专家打分法确定故障树各底事件的不可靠概率,得到各底事件的重要度,并利用灰色关联理论求出故障树各底事件的关联度;根据预警理论将各底事件的关联度与各底事件的重要度加权平均确定预警值所处的警限区间,从而确定警度及需要发出的预警信号灯,完成预警工作,并提出相应的预控对策。最后通过实例分析,结果表明该方法具有可行性与实用性。     

连续型空间故障树中因素重要度分布的定义与认知

为了解工作环境条件因素对系统故障概率的影响的特征,同时丰富连续型空间故障树(CSFT)的理论框架,提出因素重要度分布的概念。因素重要度分布从经典故障树的概率重要度发展而来,目的是研究系统所处环境因素变化导致系统可靠性变化的程度。给出元件和系统的因素重要度分布概念、公式及所需基础数据,并分析因素重要度分布的正负分布特点。使用该概念研究元件X1和系统T的因素t重要度分布和因素c重要度分布。结果表明:在不同环境中,对于因素t或c变化影响元件或系统的故障概率变化程度是不同的。因素重要度分布有效地表达了t和c对元件或系统的故障概率影响特征。     

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.     

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.     

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.     

Formation of Two Xylem Frost Injuries in One Annual Ring in Siberian Spruce under Conditions of Western Siberian Forest-Tundra

The phenomenon of the formation of two damaged xylem layers in one frost ring is described in Siberian spruce grown in western Siberian forest-tundra. Temperature conditions providing for the formation of pathological cell and tissue structures are determined. The relationship between the formation of double frost injuries and cold periods is demonstrated.     

秦皇岛市4种常见绿化植物滞尘效应研究

通过对秦皇岛市4种常见绿化植物的叶片滞尘量、单株滞尘能力及相关因素的研究,发现绿化植物单位叶面积的滞尘量最大可以相差2.5倍左右,树种叶片滞尘能力的大小排序为：国槐＞悬铃木＞金银木＞连翘,单株滞尘能力的大小排序为：悬铃木＞国槐＞金银木＞连翘;绿化植物的滞尘量与环境中粉尘含量成正比,树木滞尘能力还与叶片表面性状、叶面积指数及植物所处环境等因素有关。     

Organic farmers in islands: Agricultural management and attitude towards the environment

SUMMARY

This study explores differences among organic farmers who live in islands and have isolated small-size operations. The relationships between farmers' characteristics and attitudes and farm management were interpreted by studying how they manage their land, their attitudes towards the environment and alternative farming systems, and their involvement in organic farming. The research was carried out using questionnaires addressed to organic farmers on the island of Thassos. Nonlinear canonical correlation was applied for data analysis. This information could contribute to adjustment of policy decisions for on-farm diversification. Agricultural policy makers should approach organic farmers in northern Thassos (productive irrigated olive orchards with gentle slopes) by enacting standards to reduce the cost of alternative plant protection methods and promoting their products in order to maintain and expand organic farming. They should also approach organic farmers in southern Thassos (less productive, dry cultivated olive orchards with steep slopes, overgrazed and often abandoned) by providing them with the necessary information and appropriate agricultural know-how to effectively manage their farms. Organic farmers with stable off-farm income are more aware of environmental values and consider that they risk less than others in order to gain the benefits of alternative farming systems. However, they should attend training programmes to achieve economic success to allow them to continue farming organically.