Optimizing Reinforced Concrete Cantilever Retaining Walls Using Gases Brownian Motion Algorithm (GBMOA)

Document Type : Regular Article

Authors

1 Engineer, Department of Civil Engineering Faculty of Central Tehran Branch, Islamic Azad University, Tehran, Iran

2 Professor, Faculty of Civil Engineering KN Toosi University of Technology, Tehran, Iran

3 Engineer, Department of Civil Engineering, University of Science and Culture, Tehran, Iran

Abstract

In this paper, the cost and weight of the reinforcement concrete cantilever retaining wall are optimized using Gases Brownian Motion Optimization Algorithm (GBMOA) which is based on the gas molecules motion. To investigate the optimization capability of the GBMOA, two objective functions of cost and weight are considered and verification is made using two available solutions for retaining wall design. Furthermore, the effect of wall geometries of retaining walls on their cost and weight is investigated using four different T-shape walls. Besides, sensitivity analyses for effects of backfill slope, stem height, surcharge, and backfill unit weight are carried out and of soil. Moreover, Rankine and Coulomb methods for lateral earth pressure calculation are used and results are compared. The GBMOA predictions are compared with those available in the literature. It has been shown that the use of GBMOA results in reducing significantly the cost and weight of retaining walls. In addition, the Coulomb lateral earth pressure can reduce the cost and weight of retaining walls.

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[1]     Sarıbaş A, Erbatur F. Optimization and Sensitivity of Retaining Structures. J Geotech Eng 1996;122:649–56. doi:10.1061/(ASCE)0733-9410(1996)122:8(649).
[2]     Sivakumar Babu GL, Basha BM. Optimum Design of Cantilever Retaining Walls Using Target Reliability Approach. Int J Geomech 2008;8:240–52. doi:10.1061/(ASCE)1532-3641(2008)8:4(240).
[3]     Yepes V, Alcala J, Perea C, González-Vidosa F. A parametric study of optimum earth-retaining walls by simulated annealing. Eng Struct 2008;30:821–30. doi:10.1016/j.engstruct.2007.05.023.
[4]     Ceranic B, Fryer C, Baines RW. An application of simulated annealing to the optimum design of reinforced concrete retaining structures. Comput Struct 2001;79:1569–81. doi:10.1016/S0045-7949(01)00037-2.
[5]     Ghazavi M, Bazzazian Bonab S. Learning from ant society in optimizing concrete retaining walls. J Technol Educ 2011;5:205–12.
[6]     Ghazavi M, Salavaty V. Sensitivity analysis and design and of reinforced concrete cantilever retaining walls using bacterial foraging optimization algorithm. Geotech Saf Risk ISGSR 2011 2011:307–14.
[7]     Kaveh A, Behnam AF. Charged System Search Algorithm for the Optimum Cost Design of Reinforced Concrete Cantilever Retaining Walls. Arab J Sci Eng 2013;38:563–70. doi:10.1007/s13369-012-0332-0.
[8]     Abdechiri M, Meybodi MR, Bahrami H. Gases Brownian Motion Optimization: an Algorithm for Optimization (GBMO). Appl Soft Comput 2013;13:2932–46. doi:10.1016/j.asoc.2012.03.068.
[9]     Bowles LE. Foundation analysis and design. McGraw-hill; 1982.
[10]    Committee ACI, Standardization IO for. Building code requirements for structural concrete (ACI 318-08) and commentary, American Concrete Institute; 2008.