Predicting the ejection velocities of fragments from explosions cylindrical pressure vessels: Uncertainty and sensitivity analysis

Vaidogas, Egidijus Rytas

doi:10.1016/j.jlp.2021.104450

Cited by 9 publications

(5 citation statements)

References 31 publications

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“…1 The three fragmentation events N n = ( n = 2, 3, 4) must be ranked in terms of the hazard of fragment impacts on potential targets. A stochastic simulation of fragment ejection and projection can be used for this ranking [34,41].…”

Section: Discussionmentioning

confidence: 99%

“…In terms of safety engineering, the number of fragments is the essential information necessary for a probabilistic prediction of aerodynamic properties, trajectories and impact of fragments on vulnerable objects [34,41,45]. Eventually this information will be important to a design of protective structures intended for a defence against moderate-velocity and high-mass non-rigid projectiles from such events as BLEVEs.…”

Section: Review Of Related Work and Available Datamentioning

confidence: 99%

“…The safety problem arises only when at least two fragments are ejected, that is, the random event 2 N ≥ occurs (Figure 1). The event 1 N = represents neg- (c) generation of five or more small fragments prediction of aerodynamic properties, trajectories and impact of fragments on vulnerable objects [34,41,45]. Eventually this information will be important to a design of protective structures intended for a defence against moderate-velocity and high-mass non-rigid projectiles from such events as BLEVEs.…”

Section: Mathematical Problem Under Studymentioning

confidence: 99%

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Bayesian Processing of Data on Bursts of Pressure Vessels

Vaidogas

2021

ITC

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Two alternative Bayesian approaches are proposed for the prediction of fragmentation of pressure vessels triggered off by accidental explosions (bursts) of these containment structures. It is shown how to carry out this prediction with post-mortem data on fragment numbers counted after past explosion accidents. Results of the prediction are estimates of probabilities of individual fragment numbers. These estimates are expressed by means of Bayesian prior or posterior distributions. It is demonstrated how to elicit the prior distributions from relatively scarce post-mortem data on vessel fragmentations. Specifically, it is suggested to develop priors with two Bayesian models known as compound Poisson-gamma and multinomial-Dirichlet probability distributions. The available data is used to specify non-informative prior for Poisson parameter that is subsequently transformed into priors of individual fragment number probabilities. Alternatively, the data is applied to a specification of Dirichlet concentration parameters. The latter priors directly express epistemic uncertainty in the fragment number probabilities. Example calculations presented in the study demonstrate that the suggested non-informative prior distributions are responsive to updates with scarce data on vessel explosions. It is shown that priors specified with Poisson-gamma and multinomial-Dirichlet models differ tangibly; however, this difference decreases with increasing amount of new data. For the sake of brevity and concreteness, the study was limited to fire induced vessel bursts known as boiling liquid expanding vapour explosions (BLEVEs).

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Section: Discussionmentioning

confidence: 99%

Section: Review Of Related Work and Available Datamentioning

confidence: 99%

Section: Mathematical Problem Under Studymentioning

confidence: 99%

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Bayesian Processing of Data on Bursts of Pressure Vessels

Vaidogas

2021

ITC

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“…Most information about these events is related to residual damage of damaged buildings. Despite this scenario, Stawczyk [21] and Tschirschwitz et al [22] carried out experiments with exploding gas tanks, and a study about high-speed fragments from pressure vessel explosions was presented by Vaidogas [23].…”

Section: Introductionmentioning

confidence: 99%

Numerical analysis of the explosion of gas tanks using computational fluid dynamics

Moura

Neto

Doz

2023

Rev. IBRACON Estrut. Mater.

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Buildings are composed of several systems, each with specific designs and regulations to ensure that constructions are safe and viable. Many residential, commercial, and industrial buildings have systems with gas central storage, which must be subjected to strict safety criteria to avoid accidents. In addition to the safety mechanisms provided by manufacturers, designers of these gas central storage must consider other devices to reduce explosion risk and mitigate the damaging blast effects. Explosions are physical-chemical phenomena that are characterized by the sudden expansion of a material and, consequently, energy release. When an accidental explosion occurs, much damage is caused by the shock wave and fragments. In the case of pressure vessels, a mechanical explosion can occur. Studying this explosion is essential to developing a more reliable, safe design for surrounding buildings and its users. This work aims to study the effects of gas tank explosions. In this study, the Autodyn computational tool based on fluid dynamics (CFD) is used. This software allows the modeling of complex explosion scenarios and the evaluation of blast wave parameters. For each numerical model, the overpressure levels outdoors and indoors are evaluated. The results indicated how the wave overpressures are distributed in different scenarios, and from them, it was possible to analyze the damaging levels.

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“…Hazards and consequences of BLEVEs and vessel explosions of other types are natural subjects of PRA. Unlike the classical, deterministic mechanical analysis, PRA is focussed on quantifying uncertainties, related to fragment numbers, fragmentation patterns, ejection and projection of fragments [11,12]. The first step in assessing the event sequence starting with vessel fragmentation and ending with fragment impact on a target is a prediction of the number of fragments and a closely related prediction of fragmentation pattern.…”

Section: Introductionmentioning

confidence: 99%

Explosions of Cylindrical Pressure Vessels Subjected to Fire: Probabilistic Prediction of a Number of Fragments

Vaidogas

2021

mech

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The aim of this study was to propose a procedure for a prediction of the number of fragments generated by fire induced explosions of cylindrical pressure vessels. The prediction is carried out in terms of probabilities of individual fragment numbers. The prevailing numbers of two to four fragments are considered. The fragment number probabilities are estimated by applying data on vessel fragmentations acquired in investigations of past explosion accidents. The pressure vessel explosions known as BLEVEs are considered. The Bayesian analysis is used for the estimation of the fragment number probabilities. This analysis is carried out on the basis of Poisson-gamma model. An approach to developing a gamma prior distribution for the average number of fragments per explosion accident is proposed. The assessment of the fragment number probabilities is carried out by propagating uncertainty related to the average number of fragments to uncertainty in the fragment number probabilities. The stochastic (Monte Carlo) simulation is used for this propagation. Findings of this study are viewed as a possibility to improve the assessment of risk posed by pressure vessel explosions.

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Predicting the ejection velocities of fragments from explosions cylindrical pressure vessels: Uncertainty and sensitivity analysis

Cited by 9 publications

References 31 publications

Bayesian Processing of Data on Bursts of Pressure Vessels

Bayesian Processing of Data on Bursts of Pressure Vessels

Numerical analysis of the explosion of gas tanks using computational fluid dynamics

Explosions of Cylindrical Pressure Vessels Subjected to Fire: Probabilistic Prediction of a Number of Fragments

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