Several industries now use risk analysis to develop inspection programs to ensure acceptable mechanical integrity and reliability. These industries include nuclear and electric power generation, oil refining, gas processing, onshore and offshore exploration and production, chemical processing, and pipelines. Risk analysis may also be used as a decision-making tool in the railroad industry to develop systematic improvements in track maintenance and inspection strategies. In the course of conducting research in support of the Federal Railroad Administration, a Monte Carlo risk assessment model has been developed to simulate certain aspects of rail inspection (also referred to as rail testing) to find and remove defects that may grow to sufficient size to cause rail failures. In this paper, the model is used to examine the relationship between the occurrence of rail failures and various operational factors. These operational factors include rail size, average axle loading, and inspection frequency. In addition, the risk assessment model is used to evaluate an alternative rail testing concept in which detector cars would conduct inspections at speeds higher than those used in current practice.

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