Volume 7, Issue 2 (3-2017)                   IJOCE 2017, 7(2): 241-255 | Back to browse issues page

XML Print


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

Markandeya Raju P, Rama Rao G V, Himala Kumari G, Gowthami E. MATHEMATICAL MODEL FOR ESTIMATION OF SELF WEIGHT OF FLEXURAL STEEL MEMBERS. IJOCE 2017; 7 (2) :241-255
URL: http://ijoce.iust.ac.ir/article-1-296-en.html
Abstract:   (20113 Views)

The first step in the design of plate girder is to estimate the self-weight of it. Although empirical formulae for the same are available, the level of their accuracy (underestimate or overestimate) with respect to actual self-weight is not known. In this paper, optimized sections are obtained for different spans subjected to different live load carrying capacities and self-weights are estimated. EXCEL solver, which adopts Reduced Gradient Method (RGM) was applied for optimization. The objective function was chosen as Cross-sectional area with twelve constraints based on LRFD (IS 800: 2007) design specification for safety and serviceability. Simply supported (laterally restrained) plastic symmetric cross section without stiffeners is adopted for study. A mathematical model was developed based on best-fit curves between self-weight, span and live load carrying capacity and their trend line equations are obtained. The study revealed that, the ratio of self-weight to load carrying capacity was parabolic for a given span. The results from this equation are compared with the conventional formula and the standard deviation of the proposed model with respect to actual self-weight is in the range of -0.03 to 2.29 while that from the conventional model is in the range of -0.04 to 9.18.

Full-Text [PDF 726 kb]   (12534 Downloads)    
Type of Study: Research | Subject: Optimal design
Received: 2016/11/27 | Accepted: 2016/11/27 | Published: 2016/11/27

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