A simulation model of railroad reliability

A simulation model is used to study the relative reliability of struc tures subject to failure caused by fatigue cracking. This general model can be applied to most structures maintained by periodic inspections, including airplanes, bridges, pressure vessels, and nuclear reactors. The models of init...

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Bibliographic Details
Published in:Simulation (San Diego, Calif.) Calif.), 1985-01, Vol.44 (4), p.168-180
Main Authors: Kesling, G.D., Whittaker, I.C.
Format: Article
Language:English
Subjects:
Computer simulation
Crack propagation
Fatigue failure
Fracture mechanics
Inspection
mechanical strength
modeling
Railroad engineering
Railroads
Rails
railway engineering
reliability
software
software development
stress
structural analysis
transportation
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Summary:A simulation model is used to study the relative reliability of struc tures subject to failure caused by fatigue cracking. This general model can be applied to most structures maintained by periodic inspections, including airplanes, bridges, pressure vessels, and nuclear reactors. The models of initiation and growth of cracks and the resulting fractures use a grid of stress cells to approx imate the cross-sectional shape of the structural components. Included in the analysis is a general model of the probabilitistic detection of cracks during an inspection. The reliabiltiy of struc tural components can be combined in the analysis to obtain overall structural reliability. The model was applied to railroad rails as a subcontract for the Department of Transportation. 29 Measurements of the rail's material characteristics and operating environment are used to estimate its reliability for a specified inspection schedule. The crack growth model selected for the rail application performs well for steel compositions, though alternative growth models are recommended for other materials. For the rail application, a model for computing the stress exposure of railroad rails is also included. Results from the rail application and use of these results to improve efficiency of resource allocations are presented.
ISSN:0037-5497
1741-3133
DOI:10.1177/003754978504400402