發(fā)布時間：2018-05-09 01:16

  本文選題：危險貨物 + 液化氣體鐵路罐車�。� 參考：《北京交通大學(xué)》2017年碩士論文

【摘要】：現(xiàn)今國民經(jīng)濟高速發(fā)展,我國進入重化工時代,鐵路危險貨物的年運輸量不斷增長,實際運輸中出現(xiàn)的危險貨物種類、品名繁多、性質(zhì)復(fù)雜,運輸過程安全隱患復(fù)雜,對人身和財產(chǎn)均造成安全威脅。鐵路危險貨物運輸中發(fā)生事故最多的是液化氣體鐵路罐車泄漏事故,因此,有必要對液化氣體鐵路罐車泄漏事故規(guī)律、事故機制以及安全影響因素進行研究,為實際運輸?shù)陌踩芽靥峁├碚撝С帧１疚闹饕芯績?nèi)容如下:(1)對液化氣體鐵路罐車泄漏事故進行分類和事故致因分析,明確泄漏事故種類與致因機制;(2)搜集PHMSA和我國的液化氣體鐵路罐車相關(guān)的泄漏事故數(shù)據(jù),利用數(shù)據(jù)挖掘軟件SPSS Modeler 14.0對數(shù)據(jù)進行統(tǒng)計特征分析、事故因素的相關(guān)性分析,運用Apriori算法尋找泄漏事故內(nèi)部關(guān)聯(lián)規(guī)則;總結(jié)事故規(guī)律;(3)按AR和NAR兩類事故,通過總結(jié)經(jīng)驗和事故樹方法分析兩類泄漏事故的安全影響因素。建立液化氣體鐵路罐車泄漏事故運輸系統(tǒng)模型,利用馬爾科夫方法對已知故障率的罐車運輸系統(tǒng)進行可靠性分析;(4)采用KNN算法,在PHMSA泄漏事故案例庫的基礎(chǔ)上建立案例推理方法,為實際應(yīng)用提供解決方案。研究表明,1月、7月和10月為液化氣體鐵路罐車泄漏事故高發(fā)期,需要提高警惕;大部分液化氣體鐵路罐車泄漏事故發(fā)生在運輸途中,屬于C、D類事故;需要重點注意的品名為液氯、液氨、液化石油氣和丙烯.,在泄漏事故中故障最多的部件為閥件,其次為管道和附件,最常見的故障形式為組件或設(shè)備松動。泄漏事故可分為NAR和AR事故,前者安全影響因素與速度無關(guān),主要為人為失誤、質(zhì)量問題、工況因素、熱力輻射、外界沖擊和其他因素,后者安全影響主要為速度�？衫孟到y(tǒng)穩(wěn)態(tài)可用度和平均失效時間衡量各類泄漏事故發(fā)生的危險性,其中美國的液化氣體鐵路罐車綜合系統(tǒng)的穩(wěn)態(tài)可用度為0.01年,系統(tǒng)平均失效時間為0.02年。
[Abstract]:With the rapid development of the national economy and the age of heavy chemical industry in China, the annual transport volume of dangerous goods has been increasing. The types of dangerous goods in the actual transportation, various types of dangerous goods, complex properties, complex hidden dangers in the transportation process and the threat to the safety of people and property. The most accidents in the transportation of dangerous goods in railway are liquid. Therefore, it is necessary to study the law of leakage accident, the accident mechanism and the factors affecting the safety of the liquefied gas railway tanker, and provide theoretical support for the safety of the actual transportation. The main contents of this paper are as follows: (1) the classification of the leakage accidents of the tank car of the liquefied gas body and the cause of the accident caused by the liquefied gas are the main contents of the paper. Analysis, clear leakage accident types and cause mechanism; (2) collect PHMSA and China's liquefied gas railway tank car related leakage accident data, using data mining software SPSS Modeler 14 to analyze the statistical characteristics of the data, the correlation analysis of accident factors, using Apriori algorithm to find the leakage accident internal association rules; summarize the accident rules. Law; (3) according to the two kinds of accidents of AR and NAR, the safety factors of two kinds of leakage accidents are analyzed by summing up experience and accident tree method. The model of the transportation system for the leakage accident of the liquefied gas railway tank car is established, and the Markov method is used to analyze the reliability of the tanker transportation system with the known fault rate. (4) the KNN algorithm is used for the leakage accident of the PHMSA. On the basis of case base, case based reasoning method is established to provide a solution for practical application. The study shows that in January, July and October, it is necessary to be vigilant for the high incidence of liquefied gas railway tanker leakage accident. Most liquefied gas railway tanker leaks occurred in the way of transportation, belonging to C, D accidents. Chlorine, liquid ammonia, liquefied petroleum gas and propylene. The most malfunctioning components in the leakage accident are valve parts, followed by pipes and accessories. The most common forms of failure are components or equipment loosening. The leakage accident can be divided into NAR and AR accidents. The former is independent of the safety factors and speed, and the main factors are human error, quality, working conditions and thermal radiation. Outside impact and other factors, the latter is mainly the speed of safety. The stability availability of the system and the average failure time can be used to measure the risk of all kinds of leakage accidents. The steady-state availability of the United States liquefied gas railway tanker system is 0.01 years and the average failure time of the system is 0.02 years.

【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U298.3

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