Volume 1, Issue 4 (12-2011)                   IJOCE 2011, 1(4): 507-520 | Back to browse issues page

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Kaveh A, Bakhshpoori T, Afshari E. AN OPTIMIZATION-BASED COMPARATIVE STUDY OF DOUBLE LAYER GRIDS WITH TWO DIFFERENT CONFIGURATIONS USING CUCKOO SEARCH ALGORITHM. IJOCE 2011; 1 (4) :507-520
URL: http://ijoce.iust.ac.ir/article-1-60-en.html
Abstract:   (28300 Views)
This paper is concerned with the economical comparison between two commonly used configurations for double layer grids and determining their optimum span-depth ratio. Two ranges of spans as small and big sizes with certain bays of equal length in two directions and various types of element grouping are considered for each type of square grids. In order to carry out a precise comparison between different systems, optimum design procedure based on the Cuckoo Search (CS) algorithm is developed. The CS is a meta-heuristic algorithm recently developed that is inspired by the behavior of some Cuckoo species in combination with the Lévy flight behavior of some birds and insects. The design algorithm obtains minimum weight grid through appropriate selection of tube sections available in AISC Load and Resistance Factor Design (LRFD). Strength constraints of AISC-LRFD specification and displacement constraints are imposed on grids. The comparison is aimed at finding the depth at which each of the different configurations shows its advantages. The results are graphically presented from which the optimum depth can easily be estimated for each type, while the influence of element grouping can also be realized at the same time.
Full-Text [PDF 267 kb]   (6216 Downloads)    
Type of Study: Research | Subject: Optimal design
Received: 2012/02/28 | Published: 2011/12/15

Add your comments about this article : Your username or Email:
CAPTCHA

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Iran University of Science & Technology

Designed & Developed by : Yektaweb