Application of virtual ant algorithms in the optimization of CFRP shear strengthened precracked structures

18Citations
Citations of this article
14Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Many engineering applications often involve the minimization of objective functions. The optimization becomes very difficult when the objective functions are either unknown or do not have an explicit form. This is certainly the case in the strengthening of existing pre-cracked reinforced concrete structures using external carbon fibre reinforced polymer (CFRP) reinforcement. For a given concrete structure, the identification of the optimum strengthening system is very important and difficult, and depends on many parameters including the extent and distribution of existing cracks, loading capacity, materials and environment. The choice of these parameters essentially forms a coupled problem of finite element analysis and parameter optimization with the aim of increasing the serviceability of the structure concerned. In this paper, virtual ant algorithms combined with nonlinear FE analysis are used in the optimization of the strengthening parameters. Simulations show that the location and orientation of the CFRP reinforcement has a significant influence on the behaviour of the strengthened structure. The orientation of the reinforcement with a fixed location becomes optimal if the reinforcing material is placed perpendicular to the existing crack direction. The implication for strengthening will also be presented. © Springer-Verlag Berlin Heidelberg 2006.

Cite

CITATION STYLE

APA

Yang, X. S., Lees, J. M., & Morley, C. T. (2006). Application of virtual ant algorithms in the optimization of CFRP shear strengthened precracked structures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3991 LNCS-I, pp. 834–837). Springer Verlag. https://doi.org/10.1007/11758501_117

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free