Critical derailment incidents associated with crude oil and ethanol transport have led to a renewed focus on improving the performance of tank cars against the potential for puncture under derailment conditions. Proposed strategies for improving accident performance have included design changes to tank cars, as well as, operational considerations such as reduced speeds.
In prior publications, the authors have described the development of a novel methodology for quantifying and characterizing the reductions in risk that result from changes to tank car designs or the tank car operating environment. The methodology considers key elements that are relevant to tank car derailment performance, including variations in derailment scenarios, chaotic derailment dynamics, nominal distributions of impact loads and impactor sizes, operating speed differences, and variations in tank car designs, and combines these elements into a consistent framework to estimate the relative merit of proposed mitigation strategies.
The modeling approach involves detailed computer simulations of derailment events, for which typical validation techniques are difficult to apply. Freight train derailments are uncontrolled chain events, which are prohibitively expensive to stage and instrument; and their chaotic nature makes the unique outcome of each event extremely sensitive to its particular set of initial and bounding conditions. Furthermore, the purpose of the modeling was to estimate the global risk reduction expected in the U.S. from tank car derailments, not to predict the outcome of a specific derailment event.
These challenges call into question which validation techniques are most appropriate, considering both the modeling intent as well the availability and fidelity of the data sets available for validation. This paper provides an overview of the verification and validation efforts that have been used to enhance confidence in this methodology.