Cost-Based Optimum Design of Reinforced Concrete Retaining Walls Considering Different Methods of Bearing Capacity Computation

Neda Moayyeri, Sadjad Gharehbaghi and Vagelis Plevris
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Neda Moayyeri: Department of Civil Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan P.O. Box 6361647189, Iran
Sadjad Gharehbaghi: Department of Civil Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan P.O. Box 6361647189, Iran
Vagelis Plevris: Department of Civil Engineering and Energy Technology, OsloMet—Oslo Metropolitan University, 0166 Oslo, Norway

Mathematics, 2019, vol. 7, issue 12, 1-21

Abstract: This paper investigates the effect of computing the bearing capacity through different methods on the optimum construction cost of reinforced concrete retaining walls (RCRWs). Three well-known methods of Meyerhof, Hansen, and Vesic are used for the computation of the bearing capacity. In order to model and design the RCRWs, a code is developed in MATLAB. To reach a design with minimum construction cost, the design procedure is structured in the framework of an optimization problem in which the initial construction cost of the RCRW is the objective function to be minimized. The design criteria (both geotechnical and structural limitations) are considered constraints of the optimization problem. The geometrical dimensions of the wall and the amount of steel reinforcement are used as the design variables. To find the optimum solution, the particle swarm optimization (PSO) algorithm is employed. Three numerical examples with different wall heights are used to capture the effect of using different methods of bearing capacity on the optimal construction cost of the RCRWs. The results demonstrate that, in most cases, the final design based on the Meyerhof method corresponds to a lower construction cost. The research findings also reveal that the difference among the optimum costs of the methods is decreased by increasing the wall height.

Keywords: reinforced concrete; retaining wall; optimization; bearing capacity; particle swarm optimization; PSO (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
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