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On Railroad Tank Car Puncture Performance: Part II - Estimating Metrics
  • Published Date:
    2016-04-12
  • Language:
    English
Filetype[PDF-685.60 KB]


Details:
  • Publication/ Report Number:
    JRC2016-5713
  • Resource Type:
  • Geographical Coverage:
  • NTL Classification:
    AGR-SAFETY AND SECURITY-SAFETY AND SECURITY ; NTL-RAIL TRANSPORTATION-Rail SafetyNTL-RAIL TRANSPORTATION-RAIL TRANSPORTATION ; NTL-SAFETY AND SECURITY-Vehicle Design ; NTL-SAFETY AND SECURITY-Rail Safety ;
  • Format:
  • Abstract:
    This paper is the second 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 Part I, generalized tank car impact scenarios were 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 were given. Physical and mathematical relationships among these metrics were outlined. Strengths and limitations of these performance metrics were discussed.

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

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