Challenges to improve confidence level of risk assessment of hydrogen technologies

Making large-scale distribution and use of hydrogen successful will require adequate risk control. In turn, control requires risk assessment. Despite many years of experience, in general, methods to determine risk lack still robustness: results being much too dependent on choices made by the analyst due to uncertainties, lack of data and different views. This can create frustration amongst people dependent on results. HySafe and other groups work in the right direction. This paper will review existing methodological weaknesses, current improvements in e.g. the context of developing risk-informed standards and emphasize the challenges to raise quality further. The Standard Benchmark Exercise Problems, SBEPs, were a good start but shall produce recommendations for CFD use or even certification of models. Scenario generation shall take advantage of historical incident data and newer methods such as Bayesian belief nets, and cover the entire hydrogen distribution system and not only garages and refueling stations; the analyses shall more explicitly present confidence intervals on results. Knowledge gaps on e.g. ignition probability shall be defined and filled.

[1]  Jeffrey L. LaChance,et al.  Analyses to support development of risk-informed separation distances for hydrogen codes and standards. , 2009 .

[2]  I L Hirst,et al.  A "worst case" methodology for obtaining a rough but rapid indication of the societal risk from a major accident hazard installation. , 2002, Journal of hazardous materials.

[3]  I. Ziomas,et al.  Uncertainties in chemical risk assessment: Results of a European benchmark exercise , 1992 .

[4]  Dedy Ng,et al.  Risk measures constituting a risk metrics which enables improved decision making: Value-at-Risk , 2010 .

[5]  Tron Solberg,et al.  Investigations to improve and assess the accuracy of computational fluid dynamic based explosion models , 1996 .

[6]  Olav R. Hansen,et al.  FLACS CFD air quality model performance evaluation with Kit Fox, MUST, Prairie Grass, and EMU observations , 2004 .

[7]  P. Friis-Hansen,et al.  Risk modelling of a hydrogen refuelling station using Bayesian network , 2011 .

[8]  B. Carissimo,et al.  Development and test of an evaluation protocol for heavy gas dispersion models , 1997 .

[9]  E. Jaynes.  Probability theory : the logic of science , 2003 .

[10]  Jim Ohi,et al.  Risk-informed process and tools for permitting hydrogen fueling stations , 2009 .

[11]  Geoffrey Hankinson,et al.  Gas build-up in a domestic property following releases of methane/hydrogen mixtures , 2009 .

[12]  Christian Delvosalle,et al.  ARAMIS project: a comprehensive methodology for the identification of reference accident scenarios in process industries. , 2006, Journal of hazardous materials.

[13]  O. A. Rosyid,et al.  Risk analysis for the infrastructure of a hydrogen economy , 2007 .

[14]  Frank Markert,et al.  Assessment of Uncertainties in Risk Analysis of Chemical Establishments The ASSURANCE project Final summary report , 2002 .

[15]  John Spouge.  New generic leak frequencies for process equipment , 2005 .

[16]  Jesse D. Dean,et al.  INCIDENT REPORTING: LEARNING FROM EXPERIENCE , 2007 .

[17]  Cécile Fiévez,et al.  ARAMIS project: a more explicit demonstration of risk control through the use of bow-tie diagrams and the evaluation of safety barrier performance. , 2006, Journal of hazardous materials.