Evaluating uncertainty in accident rate estimation at hydrogen refueling station using time correlation model

Mahesh Kodoth, Shu Aoyama, Junji Sakamoto, Naoya Kasai, Tadahiro Shibutani, Atsumi Miyake

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


Hydrogen, as a future energy carrier, is receiving a significant amount of attention in Japan. From the viewpoint of safety, risk evaluation is required in order to increase the number of hydrogen refueling stations (HRSs) implemented in Japan. Collecting data about accidents in the past will provide a hint to understand the trend in the possibility of accidents occurrence by identifying its operation time However, in new technology; accident rate estimation can have a high degree of uncertainty due to absence of major accident direct data in the late operational period. The uncertainty in the estimation is proportional to the data unavailability, which increases over long operation period due to decrease in number of stations. In this paper, a suitable time correlation model is adopted in the estimation to reflect lack (due to the limited operation period of HRS) or abundance of accident data, which is not well supported by conventional approaches. The model adopted in this paper shows that the uncertainty in the estimation increases when the operation time is long owing to the decreasing data.

Original languageEnglish
Pages (from-to)23409-23417
Number of pages9
JournalInternational Journal of Hydrogen Energy
Issue number52
Publication statusPublished - Dec 27 2018
Externally publishedYes


  • Accident rate
  • Hydrogen refueling station
  • Time correlation model
  • Uncertainty analysis

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Condensed Matter Physics
  • Energy Engineering and Power Technology


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