Reliability-based design methods for protective structures

Twisdale, Lawrence A.; Sues, Robert H.; Lavelle, Francis M.

doi:10.1016/0167-4730(94)90050-7

Cited by 41 publications

(34 citation statements)

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“…The substantial variability of the blast parameters has been noted by various researchers even for identical field experiments. In their work, Netherton and Stewart (2010), Bogosian et al 2002, Campidelli et al (2015), and Twisdale et al (1993) showed that in some cases, the peak overpressure and positive impulse can differ by more than 40% (and the positive duration by more than 60%) in relation to the proposed values by Kingery and Bulmash (1984). Their analyses utilized results Table 3.…”

Section: Sensitivity Analysis and Trendsmentioning

confidence: 88%

“…The available information about the randomness of each blast parameter is limited. In Borenstein and Benaroya (2009), they have been assumed to be uniformly distributed, while other researchers (Twisdale et al, 1993), based on a number of experimental recordings made from surface detonations of general-purpose bombs, have showed that the probability of these parameters follows a log-normal distribution. At this study, the random variable parameters are considered to follow uniform distributions (the procedure would not change if a normal or log-normal distribution were considered).…”

Section: Sensitivity Analysis and Trendsmentioning

confidence: 99%

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Analysis of the blast wave decay coefficient using the Kingery–Bulmash data

Karlos

Solomos

Larcher

2016

International Journal of Protective Structures

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A growing interest for the design of structures to sustain blast-induced loads has been observed in recent years as a result of the worldwide rise of terrorist bombing attacks. The blast loading is usually characterized by a sudden increase in the pressure followed by an exponential decay. The parameters of this pressure pulse are essential for design and can be found in various blast design manuals available in the open literature. One of the most widely used sources is a technical report by Kingery-Bulmash, which provides values for many blast parameters in diagrams and polynomial form. However, it does not include an equation for calculating the blast wave decay coefficient, necessary for constructing the pressure-time history of an explosion at a certain point. In this study, a review of the technical literature that contains expressions for the blast pressure decay coefficient is performed, and relevant comparisons have been made. New equations describing the decay coefficient of the Friedlander equation for both incident and reflected cases for free-air and surface bursts are proposed. These equations express the decay coefficient in terms of the scaled distance and are not valid for close-in detonations. They are entirely based on the Kingery-Bulmash data, and their accuracy is satisfactorily checked against new experimental results and their trends assessed through a sensitivity analysis. Accordingly, the positive phase of the pressure-time curve at a point can be reliably and efficiently generated.

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Section: Sensitivity Analysis and Trendsmentioning

confidence: 88%

Section: Sensitivity Analysis and Trendsmentioning

confidence: 99%

Analysis of the blast wave decay coefficient using the Kingery–Bulmash data

Karlos

Solomos

Larcher

2016

International Journal of Protective Structures

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“…Bogosian et al, 2014; Formby and Wharton, 1996; Maserjian and Fisher, 1951; Petes and Tempo, 1984; Rigby and Sielicki, 2014; Rigby et al, 2014a). Twisdale et al (1994) conducted a statistical analysis of blasts from 325 Mark-83 GP conventional bombs, which found a coefficient of variation (COV) of 0.30 for peak pressure and 0.25 for impulse. Low and Hao (2002) found a similar variability of peak reflected pressure (COV = 0.32) at various scaled distances in their review of available data.…”

Section: Introductionmentioning

confidence: 99%

Observed airblast variability and model error from repeatable explosive field trials

Stewart

Netherton

Baldacchino³

2019

International Journal of Protective Structures

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Explosive field trials have been conducted to measure the peak incident pressure, impulse and time of positive phase duration following the detonation of 15 different masses of the Plastic Explosive No #4. A novel aspect of these field trials was the repeatability of tests. Eight pressure gauges collected data during each blast, and at each scaled distance. In all, 4 blasts were conducted for each scaled distance (i.e. up to 32 measurements recorded for each scaled distance) – 60 blasts were fired in total. Consequently, this repeatability of testing allowed the mean and variance of blast pressure–time histories to be quantified, with a view to better characterise the variability of a blast itself and model error variability. This article describes the explosive field trials, and the statistical analysis of blast load variability and model error for peak incident pressure, impulse and time of positive phase duration. It was found that the mean model error is close to unity with a coefficient of variation of up to 0.15 for pressure and 0.21 for impulse. The lognormal probability distribution best fits the model error data. The probabilistic models derived from these tests can be used for a variety of structural engineering applications, such as calculating reliability-based design load or partial safety factors for explosive blast loading, and estimating the probability of damage and casualties for infrastructure subject to explosive blast loading. This is illustrated for a terrorist explosive scenario involving a spherical free-air burst, where the damage modes of interest are breaching and spalling of a concrete slab. It was found that the variability of charge mass, range and model error have a significant effect on reliability-based design.

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“…To do so requires the quantification of threat probabilities, risk reductions, losses, and costs of the security measures. This task is challenging, but it is necessary for any risk assessment, and the quantification of security risks and cost‐benefit assessment is increasingly being addressed, as are life‐cycle and cost‐benefit analyses for infrastructure protective measures . Much of this work can be categorized as “probabilistic terrorism risk assessment …”

Section: Introductionmentioning

confidence: 99%

Terrorism Risks and Cost‐Benefit Analysis of Aviation Security

Stewart

Mueller

2012

Risk Analysis

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We evaluate, for the U.S. case, the costs and benefits of three security measures designed to reduce the likelihood of a direct replication of the 9/11 terrorist attacks. To do so, we assess risk reduction, losses, and security costs in the context of the full set of security layers. The three measures evaluated are installed physical secondary barriers (IPSB) to restrict access to the hardened cockpit door during door transitions, the Federal Air Marshal Service (FAMS), and the Federal Flight Deck Officer (FFDO) Program. In the process, we examine an alternate policy measure: doubling the budget of the FFDO program to $44 million per year, installing IPSBs in all U.S. aircraft at a cost of $13.5 million per year, and reducing funding for FAMS by 75% to $300 million per year. A break-even cost-benefit analysis then finds the minimum probability of an otherwise successful attack required for the benefit of each security measures to equal its cost. We find that the IPSB is costeffective if the annual attack probability of an otherwise successful attack exceeds 0.5% or one attack every 200 years. The FFDO program is costeffective if the annual attack probability exceeds 2%. On the other hand, more than two otherwise successful attacks per year are required for FAMS to be costeffective. A policy that includes IPSBs, an increased budget for FFDOs, and a reduced budget for FAMS may be a viable policy alternative, potentially saving hundreds of millions of dollars per year with consequences for security that are, at most, negligible.

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Reliability-based design methods for protective structures

Cited by 41 publications

References 1 publication

Analysis of the blast wave decay coefficient using the Kingery–Bulmash data

Analysis of the blast wave decay coefficient using the Kingery–Bulmash data

Observed airblast variability and model error from repeatable explosive field trials

Terrorism Risks and Cost‐Benefit Analysis of Aviation Security

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