Detonations and vapor cloud explosions: Why it matters

Johnson, M. M.; Tomlin, GB; Walker, D

doi:10.1016/j.jlp.2015.03.017

Cited by 18 publications

(12 citation statements)

References 2 publications

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“…This is a post Buncefield experiment (Tree test 2) performed by DNV GL and described in New Scientist (2012) and Johnson et al (2014) in which a 50 m Â 4 m Â 3 m polythene covered enclosure is filled with a near stoichiometric propane-air mixture. The first half of the enclosure (27 m) has been filled with a dense array of trees and branches while the second half is empty.…”

Section: Approach To Model Ddt With Flacsmentioning

confidence: 99%

“…While this method may be appropriate for single free-field blast predictions it will not be applicable for pressures reflected at buildings or for general correction of 3D pressure field, and the approach is thus of limited value. Hydrogen Fraunhofer ICT lane McGill detonation tubes DNV GL Merge A, B, D ethylene experiments (Mercx, 1994) BakerRisk ethylene and hydrogen experiments (Thomas et al, 2013) DNV GL Buncefield propane tree experiments (New Scientist, 2012;Johnson et al, 2014) NIOSH 73 m D ¼ 1.05 m pipe natural gas (97.5% methane) tests (Zipf, 2012;Gamezo et al, 2013), see Fig. 3.…”

Section: Introductionmentioning

confidence: 99%

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Improved far-field blast predictions from fast deflagrations, DDTs and detonations of vapour clouds using FLACS CFD

Hansen¹,

Johnson

2015

Journal of Loss Prevention in the Process Industries

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Section: Approach To Model Ddt With Flacsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improved far-field blast predictions from fast deflagrations, DDTs and detonations of vapour clouds using FLACS CFD

Hansen¹,

Johnson

2015

Journal of Loss Prevention in the Process Industries

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“…This fog then contained both water and fuel mist and vapor. Considerable measurements and modeling were done by [36,31,37,38,7]. Starting with this pancake shape, we look at four practical ignition scenarios of a pancake-shaped flammable cloud and congestion, such that the flammable cloud extends outside the congested region.…”

Section: Explosion Scenarios For Vcesmentioning

confidence: 99%

Mechanisms and Occurrence of Detonations in Vapor Cloud Explosions

Oran¹

2019

Preprint

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Not all accidental releases of ﬂammable gases and vapors create explosions. Most releases do not ﬁnd an ignition source, and of those that do ignite, most of them result in deﬂagrations that generate low or moderate overpressures. Under some circumstances, however, it is possible for deﬂagration-to-detonation transition (DDT) to occur, and this can be followed by a propagating detonation that quickly consumes the remaining detonable cloud. In a detonable cloud, a detonation creates the worst accident that can happen. Because detonation overpressures are much higher than those in a deﬂagration and continue through the entire detonable cloud, the damage from a DDT event is more severe.This paper ﬁrst provides a brief summary of our knowledge to date of the fundamental mechanisms of ﬂame acceleration and DDT. This information is then contrasted to and combined with evidence of detonations (detonation markers) obtained from large-scale tests and actual large vapor cloud explosions (VCEs), including events at Bunceﬁeld (UK), Jaipur (India), CAPECO (Puerto Rico), and Port Hudson (US). The major conclusion from this review is that detonations did occur in prior VCEs in at least part of the VCE accidents. Finally, actions are suggested that could be taken to minimize detonation hazards.

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“…In this paper, we study the domino effect of VCEs, where both the main triggering event and the subsequent events are VCEs [16]. VCEs occur when a large amount of flammable material is released into partially congested atmospheres and such material does not ignite immediately [14].…”

Section: Introductionmentioning

confidence: 99%

Stochastic modeling and analysis of vapor cloud explosions domino effects in chemical plants

Sierra¹,

Montecchi

Mura

2019

J Braz Comput Soc

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Because of the substances they process and the conditions of operation, chemical plants are systems prone to the occurrence of undesirable and potentially dangerous events. Major accidents may occur when a triggering event produces a cascading accident that propagates to other units, a scenario known as domino effect. Assessing the probability of experiencing a domino effect and estimating the magnitude of its consequences is a complex task, as it depends on the nature of the substances being processed, the operating conditions, the failure proneness of equipment units, the execution of preventive maintenance activities, and of course the plant layout. In this work, we propose a stochastic modeling methodology to perform a probabilistic analysis of the likelihood of domino effects caused by propagating vapor cloud explosions. Our methodology combines mathematical models of the physical characteristics of the explosion, with stochastic state-based models representing the actual propagation among equipment units and the effect of maintenance activities. Altogether, the models allow predicting the likelihood of major events occurrence and the associated costs. A case study is analyzed, where various layouts of atmospheric gasoline tanks are assessed in terms of the predicted consequences of domino effects occurrence. The results of the analyses show that our approach can provide precious insights to support decision-making for safety and cost management.

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Detonations and vapor cloud explosions: Why it matters

Cited by 18 publications

References 2 publications

Improved far-field blast predictions from fast deflagrations, DDTs and detonations of vapour clouds using FLACS CFD

Improved far-field blast predictions from fast deflagrations, DDTs and detonations of vapour clouds using FLACS CFD

Mechanisms and Occurrence of Detonations in Vapor Cloud Explosions

Stochastic modeling and analysis of vapor cloud explosions domino effects in chemical plants

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