Optimization of the Infrastructure of Reinforced Concrete Reservoirs by a Particle Swarm Algorithm

Optimization techniques may be effective in finding the best modeling and shapes for reinforced concrete reservoirs (RCR) to improve their durability and mechanical behavior, particularly for avoiding or reducing the bending moments in these structures. RCRs are one of the major structures applied f...

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Main Authors: Kia Saeed, Sebt Mohammad Hassan, Shahhosseini Vahid
Format: Article
Language:English
Published: Sciendo 2015-03-01
Series:Slovak Journal of Civil Engineering
Subjects:
Online Access:http://www.degruyter.com/view/j/sjce.2015.23.issue-1/sjce-2015-0003/sjce-2015-0003.xml?format=INT
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spelling doaj-6b8d66aeaba44ff481ad0fa3daa4eb8b2020-11-24T23:10:33ZengSciendoSlovak Journal of Civil Engineering1210-38961338-39732015-03-01231142210.1515/sjce-2015-0003sjce-2015-0003Optimization of the Infrastructure of Reinforced Concrete Reservoirs by a Particle Swarm AlgorithmKia Saeed0Sebt Mohammad Hassan1Shahhosseini Vahid2Amirkabir University of Technology , Tehran Polytechnic, IranDepartment of Civil & Environmental Engineering, Amirkabir University of Technology, Tehran Polytechnic, IranDepartment of Civil & Environmental Engineering, Amirkabir University of Technology, Tehran Polytechnic, IranOptimization techniques may be effective in finding the best modeling and shapes for reinforced concrete reservoirs (RCR) to improve their durability and mechanical behavior, particularly for avoiding or reducing the bending moments in these structures. RCRs are one of the major structures applied for reserving fluids to be used in drinking water networks. Usually, these structures have fixed shapes which are designed and calculated based on input discharges, the conditions of the structure's topology, and geotechnical locations with various combinations of static and dynamic loads. In this research, the elements of reservoir walls are first typed according to the performance analyzed; then the range of the membrane based on the thickness and the minimum and maximum cross sections of the bar used are determined in each element. This is done by considering the variable constraints, which are estimated by the maximum stress capacity. In the next phase, based on the reservoir analysis and using the algorithm of the PARIS connector, the related information is combined with the code for the PSO algorithm, i.e., an algorithm for a swarming search, to determine the optimum thickness of the cross sections for the reservoir membrane’s elements and the optimum cross section of the bar used. Based on very complex mathematical linear models for the correct embedding and angles related to achain of peripheral strengthening membranes, which optimize the vibration of the structure, a mutual relation is selected between the modeling software and the code for a particle swarm optimization algorithm. Finally, the comparative weight of the concrete reservoir optimized by the peripheral strengthening membrane is analyzed using common methods. This analysis shows a 19% decrease in the bar’s weight, a 20% decrease in the concrete’s weight, and a minimum 13% saving in construction costs according to the items of a checklist for a concrete reservoir at 10,000 m3.http://www.degruyter.com/view/j/sjce.2015.23.issue-1/sjce-2015-0003/sjce-2015-0003.xml?format=INTConcrete Reservoirsinfrastructurehealth monitoringoptimizationParticle Swarm Algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Kia Saeed
Sebt Mohammad Hassan
Shahhosseini Vahid
spellingShingle Kia Saeed
Sebt Mohammad Hassan
Shahhosseini Vahid
Optimization of the Infrastructure of Reinforced Concrete Reservoirs by a Particle Swarm Algorithm
Slovak Journal of Civil Engineering
Concrete Reservoirs
infrastructure
health monitoring
optimization
Particle Swarm Algorithm
author_facet Kia Saeed
Sebt Mohammad Hassan
Shahhosseini Vahid
author_sort Kia Saeed
title Optimization of the Infrastructure of Reinforced Concrete Reservoirs by a Particle Swarm Algorithm
title_short Optimization of the Infrastructure of Reinforced Concrete Reservoirs by a Particle Swarm Algorithm
title_full Optimization of the Infrastructure of Reinforced Concrete Reservoirs by a Particle Swarm Algorithm
title_fullStr Optimization of the Infrastructure of Reinforced Concrete Reservoirs by a Particle Swarm Algorithm
title_full_unstemmed Optimization of the Infrastructure of Reinforced Concrete Reservoirs by a Particle Swarm Algorithm
title_sort optimization of the infrastructure of reinforced concrete reservoirs by a particle swarm algorithm
publisher Sciendo
series Slovak Journal of Civil Engineering
issn 1210-3896
1338-3973
publishDate 2015-03-01
description Optimization techniques may be effective in finding the best modeling and shapes for reinforced concrete reservoirs (RCR) to improve their durability and mechanical behavior, particularly for avoiding or reducing the bending moments in these structures. RCRs are one of the major structures applied for reserving fluids to be used in drinking water networks. Usually, these structures have fixed shapes which are designed and calculated based on input discharges, the conditions of the structure's topology, and geotechnical locations with various combinations of static and dynamic loads. In this research, the elements of reservoir walls are first typed according to the performance analyzed; then the range of the membrane based on the thickness and the minimum and maximum cross sections of the bar used are determined in each element. This is done by considering the variable constraints, which are estimated by the maximum stress capacity. In the next phase, based on the reservoir analysis and using the algorithm of the PARIS connector, the related information is combined with the code for the PSO algorithm, i.e., an algorithm for a swarming search, to determine the optimum thickness of the cross sections for the reservoir membrane’s elements and the optimum cross section of the bar used. Based on very complex mathematical linear models for the correct embedding and angles related to achain of peripheral strengthening membranes, which optimize the vibration of the structure, a mutual relation is selected between the modeling software and the code for a particle swarm optimization algorithm. Finally, the comparative weight of the concrete reservoir optimized by the peripheral strengthening membrane is analyzed using common methods. This analysis shows a 19% decrease in the bar’s weight, a 20% decrease in the concrete’s weight, and a minimum 13% saving in construction costs according to the items of a checklist for a concrete reservoir at 10,000 m3.
topic Concrete Reservoirs
infrastructure
health monitoring
optimization
Particle Swarm Algorithm
url http://www.degruyter.com/view/j/sjce.2015.23.issue-1/sjce-2015-0003/sjce-2015-0003.xml?format=INT
work_keys_str_mv AT kiasaeed optimizationoftheinfrastructureofreinforcedconcretereservoirsbyaparticleswarmalgorithm
AT sebtmohammadhassan optimizationoftheinfrastructureofreinforcedconcretereservoirsbyaparticleswarmalgorithm
AT shahhosseinivahid optimizationoftheinfrastructureofreinforcedconcretereservoirsbyaparticleswarmalgorithm
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