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On Railroad Tank Car Puncture Performance: Part I — Considering Metrics

[+] Author Affiliations
David Y. Jeong, Benjamin Perlman

US Department of Transportation, Cambridge, MA

Karl Alexy, Francisco González, III

US Department of Transportation, Washington, DC

Paper No. JRC2016-5712, pp. V001T02A003; 9 pages
  • 2016 Joint Rail Conference
  • 2016 Joint Rail Conference
  • Columbia, South Carolina, USA, April 12–15, 2016
  • Conference Sponsors: Rail Transportation Division
  • ISBN: 978-0-7918-4967-5


This paper is the first in a two-part series on the puncture performance of railroad tank cars carrying hazardous materials in the event of an accident. Various metrics are often mentioned in the open literature to characterize the structural performance of tank cars under accident loading conditions. One of the consequences in terms of structural damage to the tank during accidents is puncture. This two-part series of papers focuses on four metrics to quantify the performance of tank cars against the threat of puncture: (1) speed, (2) force, (3) energy, and (4) conditional probability of release.

In this paper (Part I), generalized tank car impact scenarios are illustrated. Particular focus is given to the generalized shell impact scenario because performance-based requirements for shell puncture resistance are being considered by the regulatory agencies in United States and Canada. Definitions for the four performance metrics are given. Physical and mathematical relationships among these metrics are outlined. Strengths and limitations of these performance metrics are discussed.

In Part II, the multi-disciplinary approach to develop engineering tools to estimate the performance metrics will be described. The complementary connection between testing and modeling will be emphasized. Puncture performance metrics, which were estimated from other sources, will be compared for different tank car designs. These comparisons will be presented to interpret the metrics from a probabilistic point of view. In addition, sensitivity of the metrics to the operational and design factors will be examined qualitatively.



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