BOOK-CHAPTER

Optimum Design of Reinforced Concrete Retaining Walls

Rasim TemürGebrai̇l Bekdaş

Year: 2018 Advances in computational intelligence and robotics book series Pages: 360-378   Publisher: IGI Global

Abstract

Methodologies based on metaheuristic algorithms such as particle swarm optimization, harmony search algorithm, and teaching-learning-based optimization are proposed for optimum design of reinforced concrete cantilever retaining walls. The objective function of optimization is to find a design providing minimum cost, including material and construction costs. For this purpose, the best combination of 11 design variables (heel and toe projections, stem thickness at the top and bottom of a wall, slab thickness and rebar diameters, and spacing between the bars) that satisfy 29 design constraints including stability (overturning, sliding, and bearing) and reinforced concrete design of the wall are searched during the optimization process. The rules of ACI 318 14 (building code requirements for structural concrete) are used for the reinforced concrete design. In order to determine the strengths and weaknesses of algorithms, several different cases are investigated. As conclusions, some suggestions have been obtained that will lead to future work in this field.

Keywords:
Rebar Structural engineering Harmony search Slab Particle swarm optimization Retaining wall Computer science Reinforced concrete Metaheuristic Engineering Algorithm Artificial intelligence

Metrics

5
Cited By
0.00
FWCI (Field Weighted Citation Impact)
18
Refs
0.14
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Topology Optimization in Engineering
Physical Sciences →  Engineering →  Civil and Structural Engineering
Geotechnical Engineering and Analysis
Physical Sciences →  Engineering →  Safety, Risk, Reliability and Quality
Infrastructure Maintenance and Monitoring
Physical Sciences →  Engineering →  Civil and Structural Engineering

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