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Thursday, July 16, 2020 | History

2 edition of Statistical analysis of wheel derailment probability based on the derailment coefficient found in the catalog.

Statistical analysis of wheel derailment probability based on the derailment coefficient

Dale B. Cherchas

Statistical analysis of wheel derailment probability based on the derailment coefficient

by Dale B. Cherchas

  • 123 Want to read
  • 24 Currently reading

Published by University of Toronto/York University Joint Program in Transportation in [Toronto] .
Written in English

    Subjects:
  • Railroad accidents.,
  • Probabilities.

  • Edition Notes

    Includes bibliographical references.

    Statementby Dale B. Cherchas.
    SeriesResearch report / Joint Program in Transportation -- no.67, Research report (Joint Program in Transportation) -- no. 67
    Classifications
    LC ClassificationsHE131 .J65 no.67, HE1783C2 C44
    The Physical Object
    Pagination16, [16] p. --
    Number of Pages16
    ID Numbers
    Open LibraryOL19942296M

      Similarly, the probability that the maximum wind speed does not exceed m/s (corresponds to the assurance coefficient of ), calculated by statistics analysis, is %; this is approximately equal to the theoretical value (%) mentioned in Section Wheel/rail contact analysis of tramways and LRVs against derailment. Wear , – doi: / CrossRef Full Text | Google Scholar.

    Paper contains a report of the part of works conducted in the research and development project concerned with a modernization of freight wagons during their periodic repair. The aim of this research was to obtain better exploitation conditions of freight cars. Two elements of those works are presented: a computer aided analysis of the freight car’s CAD model and results and analysis of the. parametric studies on ΔT all, refer to [5, 6].The track will buckle whenever the thermal load P t exceeds the strength P thermal load P t is expressed through the relationship, P t = AEα(T R-T N), where T R is the rail temperature and T N is the rail neutral temperature. It should be noted that in practice track buckling is a “dynamic” event i.e. needing the wheel/rail loads to.

    TRB’s Transit Cooperative Research Program (TCRP) Rep Track-Related Research, Vol. 5: Flange Climb Derailment Criteria and Wheel/Rail Profile Management and Maintenance Guidelines for Transit Operations examines flange climb derailment criteria for transit vehicles that include lateral-to-vertical ratio limits and a corresponding flange-climb-distance limit. Derailment Mechanism. By Sr. Prof. (RST)/IRIMEE Derailment Definition Derailment of rolling stock is defined as a wheel or set of wheels leaving their due place from the rail top surface. There are two type of derailments: (a) Sudden derailments instant dismounting of wheel from wheel.


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Statistical analysis of wheel derailment probability based on the derailment coefficient by Dale B. Cherchas Download PDF EPUB FB2

The theoretical probability is then compared with the experimental probability as determined in (5). Theoretical Calculation of the Probability of Wheel Climb Nadal's formula () states the critical value Q of derailment coefficient to be Q - tan a - y (1) l+y tan a where (see Fig.

1) a = vertical contact plane angle, y = coefficient of Cited by: 6. In terms of train derailment severity analysis, the response variable is the number of cars derailed.

A ZTNB model is developed based on a set of broken-rail-caused freight-train derailments on Class I mainlines from to The model accounts for main effect, higher-order component and their interaction terms of explanatory by: DERAILMENT COEFFICIENT AND CLIMBING PROBABILITY OF WHEEL FLANGE.

Derailment coefficients in running of 2, wagons of different categories, loaded or empty, were measured and the data collected were analyzed. Meanwhile, using a derailment test car, the climbing of three different wheels on five types of rails was observed and the data on their Cited by: 2.

The formula for the critical derailment coefficient concerning wheelset yaw angles and wheel-rail creep forces is deduced based on the three-dimensional (3D) force equilibrium relationship in the. derailment is a function of the quality of track, the length of train, and the exposure in terms of miles traveled.

The probability of derailment for individual cars within a derailed train consist is a function of the point-of-derailment (POD), train length, train speed, and the accident cause.

The criterion for derailment is based on the derailment coefficient, i.e., ratio of wheel flange/railhead lateral force to vertical wheel load. More specifically, the computer simulation utilizes a relationship between the probability of wheel climb commencing and the derailment coefficient, established by Japan National Railways based on their.

Angle of wheel flange, friction coefficient, axle load and train speed are effective parameters in investigation of train derailment probability. In this paper, by using statistical distributions, aforementioned parameters are investigated and derailment probability is calculated using.

The influence of adhesion coefficient on the wheel climb derailment was analysed. Zeng et al. [9, 10] studied the wheel flange climb derailment based on theoretical analysis and a single-wheelset test stand.

It was revealed that large wheel lateral force and reduced vertical force were responsible for the wheel climb derailment. The influences of wheelset lateral impact velocity, flange angle, wheel/rail friction coefficient, wheel vertical load and impact time interval on wheelset derailment are analyzed.

View Show abstract. This research provides a method to estimate the derailment probability of a railway vehicle where track irregularities are assumed to be random, and the interaction of the track and the moving train is considered using advanced dynamic analysis. For this purpose, the limit state function of derailment was estimated using the response surface.

Derailment coefficient is an important criterion to evaluate the operating safety of rail vehicles. A derailment coefficient prediction method based on neural network is proposed in this paper.

First, the basic concepts of derailment coefficient are briefly discussed. CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Summary: We conducted statistical analyses and used modeling techniques to develop derailment probabilities for freight trains and freight cars operating on North American railroads.

Knowing the expected frequency of derailment and the conditional probabilities of derailment for individual cars enables estimation of. Relying on the experiment and regarding the derailment coefficient and rate of wheel load reduction as the safety assessment standard, study is conducted concerning the safety of C 62BK-wagon loaded running on sharp curves of Beijing-Chengde line, through statistical analysis of experimental data.

The research status of train derailment is summarized. Major problems existing in current derailment research are pointed out. By applying system dynamics stability concepts, the mechanical mechanism of train derailment is described. The theory of random energy analysis for train derailment is then further expounded and preventive measures for train derailment and a calculation method for.

wheel loads, based on analytic equations and measured data. This paper describes the equations used, shows how the derailment coefficient is calculated, and compares it with the results achieved by measurements.

KeywordsKeywords: flange-climb derailment, vehicle dynamics simulation, derailment coefficient, Q/P estimation equations, estimated Q.

The formula for the critical derailment coefficient concerning wheelset yaw angles and wheel-rail creep forces is deduced based on the three-dimensional (3D) force equilibrium relationship in the critical wheel derailment state under quasistatic assumption.

The change of critical derailment coefficient and wheel-rail contact patch normal force/creep force as wheelset yaw angles change under.

Due to the damage, derailment of vehicle can not measure the static wheel load. But according to the result of measuring the same models and manufacturing records, it indicates that the derailed wheel has great imbalance.

So this factor is considered to be the main cause of the derailment. (2) coefficient of friction between the wheel/rail vehicles. Statistical Method for Investigating Transient Enhancements of Dynamical Responses due to Random Disturbances: Application to Railway Vehicle Motion Effect of Track Irregularities on Running Safety of Railway Vehicle—Statistical Analysis of Derailment Coefficient,” Variance-Based Wheel/Rail Contact Sensitivity Analysis in Respect of.

The current paper summarises some key findings from the project and also gives an insight into the adopted methodologies. Figure 1: a) Low-reaching axle journal parts that may have prevented large lateral deviations in the Shinkansen earthquake derailment inb) Clear evidence of lateral contact between the AWS support bracket and inner rail side that may have prevented further lateral.

interaction of the track and the moving train is considered using advanced dynamic analysis. For this purpose, the limit state function of derailment was estimated using the response surface method and advanced simulation.

The probability of derailment was then estimated using a. The influence of adhesion coefficient on the wheel climb derailment was analysed. Zeng et al. [9, 10] studied the wheel flange climb derailment based on theoretical analysis and a single-wheelset test stand. It was revealed that large wheel lateral force and reduced vertical force were responsible for the wheel climb derailment.A Study on the Prevention of Wheel-Climb.

Derailment at Low Speed Ranges • Keywords: Wheel-climb derailment, Wheel turning, Equivalent friction coefficient, Nadal’s L/V limit criterion. Wheel-climb derailment is considered to be profoundly influenced by the friction coefficient between the wheel flange and the rail.Based on this information, what is the probability that between and auto physical damage claims will occur next year?

Assume that the expected safe life of a heating element for a particular type of furnace is 4, hours with a standard deviation of hours, and that the expected safe life conforms to a normal distribution.