International Journal of Railway Research
Year:2016 | Volume:3 | Issue:1|Papers Count:5

This paper describes our contribution to improving the usual safety analysis methods used in the certification of railway transport systems. The methodology is based on the complementary and simultaneous use of knowledge acquisition and machine learning. The purpose is contributed to the generation of new accident scenarios that could help experts to conclude on the safe character of a new rail transport system. The method of analysis and evaluation is centered on the summarized failures (SFs) which are involved in accident scenarios capitalized. A summarized failure (SF) is a generic failure produced by the combination of a set of basic failures which has the same effect on the performance of the system. Each scenario brings into play one or more SFs.The purpose is to automatically generate a recognition function for each SF associated with a scenario class. The SF recognition function is a production rule which establishes a link between a set of facts (parameters which describe a scenario or descriptors) and the SF fact. A base of evaluation rules can be generated for each class of scenarios. The SF deduction stage requires a preliminary phase during which the rules which have been generated are transferred to an expert system in order to construct a scenario evaluation knowledge base. The evaluation knowledge base is exploited by forward chaining by an inference engine and generates the summarized failures (SFs) which must enter into the description of the scenario which is to be evaluated.

One of the most common solutions to deal with the power quality issues of electrical railway systems is employing Railway Power Conditioner (RPC). In the conventional mode of operation, the RPC power rating deployed in every Traction Power Substation (TPS) is significantly large. This paper mainly focuses on the power rating reduction of RPC through presenting of a novel combinatorial compensation method. The inductive and capacitive switching algorithm retrieved from Steinmetz circuit lead to additional auxiliary balance in sequential TPS which declines the RPC function in elimination of the Negative Sequence Current (NSC). The proposed method can reduce the voltage over Sectioning Posts (SP), DC-link operation voltage, back-to-back (B2B) converters rating and installation costs. The accuracy and effectiveness of the proposed strategy are confirmed via simulation results obtained by MATLAB/SIMULINK program.

The situation of other countries in rail transportation is an appropriate criterion for evaluating the existing performance of Iranian railways and the experiences of other countries can be used to improve the efficiency of Iran’s rail transportation. At the beginning of the study, in order to compare the Iranian railway performance with railways of countries from around the world and other countries in the Middle East and Central Asia, various efficiency indicators have been defined. The comparison based on data from the International Union of Railways for member states in 2012 show that the main priorities to meet the needs of Iran’s rail freight transportation are increasing the number of the fleet, developing railway lines, utilizing lines and fleet. In order to evaluate the efficiency of each of the areas listed above, nonparametric method of data envelopment analysis DEA (modified output-based BCC) has been used in the software MAXDEA. Based on the obtained results, the Iranian railway rank is 25 among 66 countries of the world with efficiency of 51 percent and its rank is 9 among 14 countries of the Middle East and Central Asia with efficiency of 55 percent. At the end of the study, time series performance index of countries from 2000 to 2012 were studied. And over these years, Iran has always had a constant downward trend with efficiency of 30 percent.

Interests of increasing the speed of high speed trains, brought more wryness about probable accidents. Whereas passenger wagon carbody is considered as a safe compartment for passengers, therefore, great attention should be paid on its design. In this study, a passenger carbody (made by Eastern Germany) and its chassis are modeled to simulate crash analysis according to EN 15227 standard. Then, obtained results are used in order to optimize the wagon chassis. This investigation is performed in two steps. In the first step, which consists of simulation of the original wagon model, it is found that due to the lack of efficiency in crash force absorbent, some modifications are needed to consider. In the second step, the original chassis is modified according to modern ones and by implementing honeycomb cores as energy absorbing device, higher absorbed energy is yielded. Also, impact stresses in mid-section of the chassis considerably decreased. The proposed energy absorbing device can be implemented in front end of the chassis to provide a crashworthy structure, however, other investigations such as modal analysis and strength determination should be conducted precede the final structure.

Numerical analysis of fluid sloshing in tank wagons is one of the updated matters focused by railway engineers. The free surface of fluid becomes unstable and turns into a dynamic complex non-linear problem for fluid-structure interaction (FSI). In this paper, first, the dynamic response of the tank, including lateral force analysis and pressure distribution during braking, is obtained using an explicit dynamic finite element model based on the Multi Material Arbitrary Lagrangian Eulerian method (MM-ALE); then, the simplified model is developed for sloshing during turning.Numerical finite element model is validated using a test setup. Comparing these models during turning with parametric studies for tank filling, it is observed that frequency and sloshing amplitude, when filling is less than 25%, have less than 10% of difference; therefore, the simplified model in the above conditions can be used with an acceptable accuracy because of a remarkable reduction in the time and cost of numerical calculations.