Evaluating long-duration blast loads on steel columns using computational fluid dynamics
Evaluating long-duration blast loads on steel columns using computational fluid dynamics
Long-duration blasts are typically defined by positive pressure durations exceeding 100ms. Such blasts can generate dynamic pressures (blast winds) capable of exerting damaging drag loads on comparatively slender structural components such as columns. With limited drag coefficient availability for specific structural geometries, Computational Fluid Dynamics (CFD) can be the only satisfactory approach for analysing blast loading on user-specified, finite geometries. The ability to analyse long-duration blasts with commercially available CFD programs is still not confidently offered, with no prior studies examining the accuracy of modelling interaction with relatively much smaller, finite geometries. This paper presents a comparative investigation between numerical and experimental results to assess the predictive capacity of inviscid Eulerian CFD as a method for calculating long-duration blast drag loading on finite cross-section geometries. Full-scale long-duration blast experiments successfully measured surface pressure-time histories on a steel I-section column aligned at four orientations. Calculated pressure-time histories on exposed geometry surfaces demonstrated good agreement although reduced accuracy and under-prediction occurred on shielded surfaces manifesting as overestimated net loading. This study provides new understanding and awareness of the numerical capability and limitations of using CFD to calculate long-duration blast loads on intricate geometries.
Long-duration, Blast Loading, Multi-axis, Eulerian CFD, Finite Sections, Computational fluid dynamics
Denny, Jack
7bd3e650-6c4e-4149-b408-2166e377b216
Clubley, Simon
a18bf075-cd85-4da4-9655-6fd27354f773
Denny, Jack
7bd3e650-6c4e-4149-b408-2166e377b216
Clubley, Simon
a18bf075-cd85-4da4-9655-6fd27354f773
Denny, Jack and Clubley, Simon
(2019)
Evaluating long-duration blast loads on steel columns using computational fluid dynamics.
Structure and Infrastructure Engineering.
(doi:10.1080/15732479.2019.1599966).
Abstract
Long-duration blasts are typically defined by positive pressure durations exceeding 100ms. Such blasts can generate dynamic pressures (blast winds) capable of exerting damaging drag loads on comparatively slender structural components such as columns. With limited drag coefficient availability for specific structural geometries, Computational Fluid Dynamics (CFD) can be the only satisfactory approach for analysing blast loading on user-specified, finite geometries. The ability to analyse long-duration blasts with commercially available CFD programs is still not confidently offered, with no prior studies examining the accuracy of modelling interaction with relatively much smaller, finite geometries. This paper presents a comparative investigation between numerical and experimental results to assess the predictive capacity of inviscid Eulerian CFD as a method for calculating long-duration blast drag loading on finite cross-section geometries. Full-scale long-duration blast experiments successfully measured surface pressure-time histories on a steel I-section column aligned at four orientations. Calculated pressure-time histories on exposed geometry surfaces demonstrated good agreement although reduced accuracy and under-prediction occurred on shielded surfaces manifesting as overestimated net loading. This study provides new understanding and awareness of the numerical capability and limitations of using CFD to calculate long-duration blast loads on intricate geometries.
Text
Denny, J.W. (2019) 'Evaluating long duration blast loads on steel columns using computational fluid dynamics'
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More information
Accepted/In Press date: 10 February 2019
e-pub ahead of print date: 5 July 2019
Keywords:
Long-duration, Blast Loading, Multi-axis, Eulerian CFD, Finite Sections, Computational fluid dynamics
Identifiers
Local EPrints ID: 432743
URI: http://eprints.soton.ac.uk/id/eprint/432743
ISSN: 1573-2479
PURE UUID: 8d516fdd-4109-4dbd-b0e8-2af1f9fe5e9c
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Date deposited: 25 Jul 2019 16:30
Last modified: 16 Mar 2024 04:36
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Author:
Simon Clubley
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