Non-dimensional pressure–impulse diagrams for blast-loaded reinforced concrete beam columns referred to different failure modes
The pressure–impulse diagram is commonly used to assess the damage level of structural components under explosion. Non-dimensional pressure–impulse diagrams referred to different failure modes was obtained using a new methodology in this article. Nine non-dimensional key parameters were first propos...
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Published in | Advances in structural engineering Vol. 21; no. 14; pp. 2114 - 2129 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
London, England
SAGE Publications
01.10.2018
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Subjects | |
Online Access | Get full text |
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Summary: | The pressure–impulse diagram is commonly used to assess the damage level of structural components under explosion. Non-dimensional pressure–impulse diagrams referred to different failure modes was obtained using a new methodology in this article. Nine non-dimensional key parameters were first proposed on basis of the Euler beam theory. Considering the shear failure, an elastic–plastic method to calculate the dynamic response of reinforced concrete beam columns was then proposed for different failure modes. Three failure categories, for example, bending failure, shear failure, and combined shear and bending failure, were considered. The threshold between the three failure modes was determined using non-dimensional pressure–impulse curves. A systematic parametric study was conducted to investigate the effects of different non-dimensional parameters on the dynamic response and the failure modes of reinforced concrete beam column. Parametric study shows that the nine non-dimensional key parameters are sufficient to calculate the dynamic response of reinforced concrete beam columns. Moreover, present study shows that the tangent modulus of direct shear stress–slip relation has a great influence on the failure modes. Beam columns with a smaller tangent modulus are more likely to generate combined shear and bending failure mode. |
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ISSN: | 1369-4332 2048-4011 |
DOI: | 10.1177/1369433218768085 |