REDUCTION OF IMPACT DAMAGE IN AUTOMATIC MARSHALLING YARDS
A simulation of marshalling yard operations has been developed, representing a significant advance over previous simulations. With emphasis on the frequency of overspeed (potentially damaging) impacts, it was validated using traffic and layout data from the Dorval Yard of Canadian National Railways. It reveals the dependency of overspeed impacts and poor track utilization on retarder release-speed policy and on the profile of the classification tracks. It is readily adapted to other yards and traffic flows. Features of the Monte Carlo approach include nine classification tracks, dual humpleads, realistic traffic flow features, and interactions between moving cuts. The simulation program is in FORTRAN IV. Trial runs on a representative yard configuration indicate that substantial improvements at any yard may be possible through such means as (1) incorporation of a retarder release-speed policy which, in addition to "Distance-to-Go" information, uses a measurement of the velocity of the preceding car, (2) alternation of the gradients in the classification tracks, (3) minor alteration to the target speed.
- Sponsored by Canadian National Railways.
Canadian Institute of Guided Ground TransportQueen's University
Kingston, Ontario K7L 3N6, Canada
- Kerr, C N
- Publication Date: 1977-6
- Features: Figures; References; Tables;
- Pagination: 40 p.
- TRT Terms: Computer programs; Highway grades; Hump yards; Impact; Layout; Monte Carlo method; Railroad yards; Retarder control; Simulation; Slopes; Speed; Speed control; Speeding; Yard operations
- Identifier Terms: FORTRAN (Computer program language)
- Uncontrolled Terms: Impact speed
- Old TRIS Terms: Yard layout; Yard simulation models
- Subject Areas: Freight Transportation; Railroads; Terminals and Facilities;
- Accession Number: 00163808
- Record Type: Publication
- Source Agency: Canadian Institute of Guided Ground Transport
- Report/Paper Numbers: CIGGT-77-11 Final Rpt.
- Files: TRIS
- Created Date: Nov 9 1977 12:00AM