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Damage evaluation of H-section steel columns under impulsive blast loads via gene expression programming

Authors :
Mohammad Momeni
Chiara Bedon
Abdolhossein Baghlani
Mohammad Ali Hadianfard
Momeni, Mohammad
Hadianfard, Mohammad Ali
Bedon, Chiara
Baghlani, Abdolhossein
Source :
Engineering Structures. 219:110909
Publication Year :
2020
Publisher :
Elsevier BV, 2020.

Abstract

Increasing terrorist attacks towards ordinary or strategic buildings and soft targets represent one of the major impetus to improve existing methods of design for blast-resistant structures. When a building undergoes an extreme dynamic event such as blast or impact, local damage of its key structural components (i.e., the columns) may lead to severe failure and even collapse of the entire building. Consequently, the availability of simplified, time efficient and reliable methods of analysis can be relevant for design. In this paper, H-section steel columns subjected to blast loads are numerically investigated, so as to derive practical formulations for damage evaluation assessment. The strategy is based on parametric Finite Element (FE) models (with up to 5600 configurations), validated towards experiments and, used as an extensive data bank, for further elaboration via Gene Expression Programming. Analytical formulations are in fact proposed for calculating some relevant parameters of design, such as (a) the initial and (b) the residual axial capacity of the examined columns. The collected results show that the proposed formulations can offer a good level of accuracy and high calculation efficiency for blast loaded H-section steel columns. In addition, an expression is proposed to relate the damage index (based residual axial capacity) to the conventional displacement/rotational index. Sensitivity analyses and some calculation examples are finally presented, to further investigate the potential of the approach for design purposes.

Details

ISSN :
01410296
Volume :
219
Database :
OpenAIRE
Journal :
Engineering Structures
Accession number :
edsair.doi.dedup.....ab68d7e0e22b09670b8794229c93f7e1
Full Text :
https://doi.org/10.1016/j.engstruct.2020.110909