This paper summarises the results from a blind-prediction study for consequence models used for estimating the reduced explosion pressure and structural response in vented hydrogen deflagrations. The work is part of the project Improving hydrogen safety for energy applications through pre-normative research on vented deflagrations (HySEA). The scenarios selected for the blind-prediction entailed vented explosions with homogeneous hydrogen-air mixtures in a 20-foot ISO (International Organization for Standardization) container. The test program included two configurations and six experiments, i.e. three repeated tests for each scenario. The comparison between experimental results and model predictions reveals reasonable agreement for some of the models, and significant discrepancies for others. The results from the first blind-prediction study in the HySEA project should motivate developers to improve and validate their models, as well as to update documentation and guidelines for users of the models.

Blind-prediction: Estimating the consequences of vented hydrogen deflagrations for homogeneous mixtures in 20-foot ISO containers

Carcassi M.
Primo
;
2019-01-01

Abstract

This paper summarises the results from a blind-prediction study for consequence models used for estimating the reduced explosion pressure and structural response in vented hydrogen deflagrations. The work is part of the project Improving hydrogen safety for energy applications through pre-normative research on vented deflagrations (HySEA). The scenarios selected for the blind-prediction entailed vented explosions with homogeneous hydrogen-air mixtures in a 20-foot ISO (International Organization for Standardization) container. The test program included two configurations and six experiments, i.e. three repeated tests for each scenario. The comparison between experimental results and model predictions reveals reasonable agreement for some of the models, and significant discrepancies for others. The results from the first blind-prediction study in the HySEA project should motivate developers to improve and validate their models, as well as to update documentation and guidelines for users of the models.
2019
Skjold, T.; Hisken, H.; Lakshmipathy, S.; Atanga, G.; Carcassi, M.; Schiavetti, M.; Stewart, J. R.; Newton, A.; Hoyes, J. R.; Tolias, I. C.; Venetsanos, A. G.; Hansen, O. R.; Geng, J.; Huser, A.; Helland, S.; Jambut, R.; Ren, K.; Kotchourko, A.; Jordan, T.; Daubech, J.; Lecocq, G.; Hanssen, A. G.; Kumar, C.; Krumenacker, L.; Jallais, S.; Miller, D.; Bauwens, C. R.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/997579
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 20
  • ???jsp.display-item.citation.isi??? 18
social impact