Optimum Design of Reinforced Concrete Folded Plate Structures to ACI 318-11 Using Soft Computing Algorithm
In this paper, an optimum design algorithm is presented for reinforced concrete folded plate structures. The design provisions are implemented by ACI 318-11 and ACI 318.2-14, which are quite complex to apply. The design variables are divided into three classes. The first class refers to the variable...
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MDPI AG
2022-05-01
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author | Sayed Yousif Mehmet Polat Saka Sanghun Kim Zong Woo Geem |
author_facet | Sayed Yousif Mehmet Polat Saka Sanghun Kim Zong Woo Geem |
author_sort | Sayed Yousif |
collection | DOAJ |
description | In this paper, an optimum design algorithm is presented for reinforced concrete folded plate structures. The design provisions are implemented by ACI 318-11 and ACI 318.2-14, which are quite complex to apply. The design variables are divided into three classes. The first class refers to the variables involving the plates, which are the number of supports, thicknesses of the plates, configurations of longitudinal and transverse reinforcement, span length of each plate, and angle of inclination of the inclined plates. The second class consists of the variables involving the auxiliary members’ (beams and diaphragms) depth and breadth and the configurations of longitudinal and shear reinforcement. The third class of variables can be the supporting columns, which involve the dimensions of the column along each axis and the configurations of longitudinal and shear reinforcement. The objective function is considered as the total cost of the folded plate structure, which consists of the cost of concrete, reinforcement, and formwork that is required to construct the building. With such formulation, the design problem becomes a discrete nonlinear programming problem. Its solution is obtained by using three different soft computing techniques, which are artificial bee colony, differential evolution, and enhanced beetle antennae search. The enhancement suggested makes use of the population of beetles instead of one, as is the case in the standard algorithm. With this novel improvement, the beetle antennae search algorithm became very efficient. Two folded plate structures are designed by the proposed optimum design algorithm. It is observed that the differential evolution algorithm performed better than the other two metaheuristics and achieved the cheapest solution. |
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spelling | doaj.art-e8571fc0aeac4d8a9548ab3851bb13802023-11-23T12:00:40ZengMDPI AGMathematics2227-73902022-05-011010166810.3390/math10101668Optimum Design of Reinforced Concrete Folded Plate Structures to ACI 318-11 Using Soft Computing AlgorithmSayed Yousif0Mehmet Polat Saka1Sanghun Kim2Zong Woo Geem3Department of Civil Engineering, University of Bahrain, Manama 32038, BahrainDepartment of Civil Engineering, University of Bahrain, Manama 32038, BahrainDepartment of Civil and Environmental Engineering, Temple University, Philadelphia, PA 19122, USADepartment of Smart City & Energy, Gachon University, Seongnam 13120, KoreaIn this paper, an optimum design algorithm is presented for reinforced concrete folded plate structures. The design provisions are implemented by ACI 318-11 and ACI 318.2-14, which are quite complex to apply. The design variables are divided into three classes. The first class refers to the variables involving the plates, which are the number of supports, thicknesses of the plates, configurations of longitudinal and transverse reinforcement, span length of each plate, and angle of inclination of the inclined plates. The second class consists of the variables involving the auxiliary members’ (beams and diaphragms) depth and breadth and the configurations of longitudinal and shear reinforcement. The third class of variables can be the supporting columns, which involve the dimensions of the column along each axis and the configurations of longitudinal and shear reinforcement. The objective function is considered as the total cost of the folded plate structure, which consists of the cost of concrete, reinforcement, and formwork that is required to construct the building. With such formulation, the design problem becomes a discrete nonlinear programming problem. Its solution is obtained by using three different soft computing techniques, which are artificial bee colony, differential evolution, and enhanced beetle antennae search. The enhancement suggested makes use of the population of beetles instead of one, as is the case in the standard algorithm. With this novel improvement, the beetle antennae search algorithm became very efficient. Two folded plate structures are designed by the proposed optimum design algorithm. It is observed that the differential evolution algorithm performed better than the other two metaheuristics and achieved the cheapest solution.https://www.mdpi.com/2227-7390/10/10/1668folded platesupporting membersminimum cost designstructural optimizationmetaheuristic algorithmsbeetle antennae search algorithm |
spellingShingle | Sayed Yousif Mehmet Polat Saka Sanghun Kim Zong Woo Geem Optimum Design of Reinforced Concrete Folded Plate Structures to ACI 318-11 Using Soft Computing Algorithm Mathematics folded plate supporting members minimum cost design structural optimization metaheuristic algorithms beetle antennae search algorithm |
title | Optimum Design of Reinforced Concrete Folded Plate Structures to ACI 318-11 Using Soft Computing Algorithm |
title_full | Optimum Design of Reinforced Concrete Folded Plate Structures to ACI 318-11 Using Soft Computing Algorithm |
title_fullStr | Optimum Design of Reinforced Concrete Folded Plate Structures to ACI 318-11 Using Soft Computing Algorithm |
title_full_unstemmed | Optimum Design of Reinforced Concrete Folded Plate Structures to ACI 318-11 Using Soft Computing Algorithm |
title_short | Optimum Design of Reinforced Concrete Folded Plate Structures to ACI 318-11 Using Soft Computing Algorithm |
title_sort | optimum design of reinforced concrete folded plate structures to aci 318 11 using soft computing algorithm |
topic | folded plate supporting members minimum cost design structural optimization metaheuristic algorithms beetle antennae search algorithm |
url | https://www.mdpi.com/2227-7390/10/10/1668 |
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