Establishing a predictive method for blast induced masonry debris distribution using experimental and numerical methods
Establishing a predictive method for blast induced masonry debris distribution using experimental and numerical methods
When subjected to blast loading, fragments ejected by concrete or masonry structures present a number of potential
hazards. Airborne fragments pose a high risk of injury and secondary damage, with the resulting debris field causing
major obstructions. The capability to predict the spatial distribution of debris of any structure as a function of
parameterised blast loads will offer vital assistance to both emergency response and search and rescue operations
and aid improvement of preventative measures. This paper proposes a new method to predict the debris distribution
produced by masonry structures which are impacted by blast. It is proposed that describing structural geometry as an
array of simple modular panels, the overall debris distribution can be predicted based on the distribution of each
individual panel. Two experimental trials using 41kg TNT equivalent charges, which subjected a total of nine small
masonry structures to blast loading, were used to benchmark a computational modelling routine using the Applied
Element Method (AEM). The computational spatial distribution presented good agreement with the experimental trials,
closely matching breakage patterns, initial fragmentation and ground impact fragmentation. The collapse mechanisms
were unpredictable due to the relatively low transmitted impulse; however, the debris distributions produced by AEM
models with matching collapse mechanisms showed good agreement with the experimental trials.
Keys, Richard
8d6aeaf4-fd64-4d29-93a1-34ae9e3e592d
Clubley, Simon
d3217801-61eb-480d-a6a7-5873b5f6f0fd
Keys, Richard
8d6aeaf4-fd64-4d29-93a1-34ae9e3e592d
Clubley, Simon
d3217801-61eb-480d-a6a7-5873b5f6f0fd
Keys, Richard and Clubley, Simon
(2017)
Establishing a predictive method for blast induced masonry debris distribution using experimental and numerical methods.
Engineering Failure Analysis.
(doi:10.1016/j.engfailanal.2017.07.017).
Abstract
When subjected to blast loading, fragments ejected by concrete or masonry structures present a number of potential
hazards. Airborne fragments pose a high risk of injury and secondary damage, with the resulting debris field causing
major obstructions. The capability to predict the spatial distribution of debris of any structure as a function of
parameterised blast loads will offer vital assistance to both emergency response and search and rescue operations
and aid improvement of preventative measures. This paper proposes a new method to predict the debris distribution
produced by masonry structures which are impacted by blast. It is proposed that describing structural geometry as an
array of simple modular panels, the overall debris distribution can be predicted based on the distribution of each
individual panel. Two experimental trials using 41kg TNT equivalent charges, which subjected a total of nine small
masonry structures to blast loading, were used to benchmark a computational modelling routine using the Applied
Element Method (AEM). The computational spatial distribution presented good agreement with the experimental trials,
closely matching breakage patterns, initial fragmentation and ground impact fragmentation. The collapse mechanisms
were unpredictable due to the relatively low transmitted impulse; however, the debris distributions produced by AEM
models with matching collapse mechanisms showed good agreement with the experimental trials.
Text
EFA_2016_798_Revision 1_V0
- Accepted Manuscript
More information
Submitted date: 24 October 2016
Accepted/In Press date: 5 July 2017
e-pub ahead of print date: 19 July 2017
Organisations:
Infrastructure Group
Identifiers
Local EPrints ID: 401955
URI: http://eprints.soton.ac.uk/id/eprint/401955
ISSN: 1350-6307
PURE UUID: bea0dfb1-8715-4f61-b610-0e5ca2e9ba32
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Date deposited: 25 Oct 2016 13:21
Last modified: 15 Mar 2024 06:00
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Contributors
Author:
Richard Keys
Author:
Simon Clubley
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