International Journal of Civil and Structural Engineering

Volume 2 Issue 4 2012          Pages: 1107 - 1121

Modeling and Shape Optimization of Reinforced Concrete Reservoirs Using Particle Swarm Algorithm

Author Information:

Saeed KIA M.Sc. in Structural Engineering, Department of Civil Engineering, College of Engineering, University of Sistan and Baluchestan, IRAN

Mohammad Reza Ghasemi Associate Professor, Department of Civil Engineering, College of Engineering, University of Sistan and Baluchestan, IRAN

ABSTRACT

Optimization techniques may be effective in finding best modeling and shape in reinforced concrete reservoirs to improve their durability, mechanical behavior, particularly avoiding or reducing the bending moments in these structures. RCR are one of the major structures applied for reserving fluids to be used in the networks of drinking water. Usually, these structures have fixed shapes which designed and calculated based on input discharge, conditions of structure topology and place geotechnical with various combinations of static and dynamic loads. In this research, first, the elements of reservoir walls are typed according to the performed analysis; then the range of membrane thickness and the minimum and maximum cross section of consumed bar are determined on the maximum stress. In next phase, based on reservoir analysis and using the algorithm of PARIS connector, the related information are combined with the code for PSO algorithm, an algorithm for swarming search, to determine the optimum thickness of cross sections for reservoir membrane elements and the optimum cross section of consumed bars. Based on very complex mathematical linear models for correct embedding and angles related to a chain of peripheral strengthening membranes, which optimize the structure vibrational, a mutual relation is selected between the modeling software and code for particle swarm optimization algorithm. Finally, the comparative weight of concrete reservoir optimized by peripheral strengthening membrane is analyzed by common methods. This analysis shows 19% decrease for bar weight, 20% decrease for concrete weight and minimum 13% saving for construction costs according to the items of checklist for a concrete reservoir at 10,000m3.

Keywords: Optimization, Reinforced Concrete Reservoirs, Particle Swarm Algorithm

doi:10.6088/ijcser.00202040009

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