OPTIMUM DESIGN OF BUTTRESS DAM USING GENETIC ALGORITHM

ALBayati, Noor Nazar; Arslan, Chelang A.

doi:10.37649/aengs.2023.142965.1061

	OPTIMUM DESIGN OF BUTTRESS DAM USING GENETIC ALGORITHM
Anbar Journal of Engineering Sciences
Volume 14, Issue 2, November 2023, Pages 40-52 PDF (1.02 M)
Document Type: Review Paper
DOI: 10.37649/aengs.2023.142965.1061
Authors
Noor Nazar ALBayati^* ; Chelang A. Arslan
University of Kirkuk
Abstract
Designing large structures like dams requires carefully selecting various geometric, hydraulic, and structural characteristics. The required structural design and performance criteria are considered when selecting these characteristics. In order to find the best solution, a variety of restrictions must simultaneously be carefully taken into account. This study presents an effective method for determining the optimal shape design for concrete buttress dams. The research was divided into two crucial phases. The dam's initial design and subsequent modeling were mostly done using DIANA FEA and traditional design and stability analysis. After that, a genetic algorithm was used on the MATLAB platform to control optimizing the dam's shape. Three design factors were used in this phase to alter the goal function and to reduce the amount of Concrete used, which decreased project costs. These variables covered three areas of the buttress's cross-section. Two important limitations were scrutinized during this optimization process: establishing a safety margin against overtopping and preventing sliding. The analysis included a detailed assessment of Shear friction stability to complete a thorough stability study. The optimization efforts had a spectacular result, resulting in a significant 52.365% reduction in the total volume of Concrete used, dropping from 19147.5 cubic meters to 9122.55 cubic meters. This decrease was made possible by reducing three distinct components (X1, X2, X3), with respective proportions of 37.5%, 13.33%, and 30%, including two segments related to the buttress and the final segment linked (slab) to the strip footing.
Keywords
Genetic Algorithm; Optimization; Buttress dam; FSO; FSS

References
Bersini and G. Seront, “In search of a good evolution optimization crossover,” in the 2nd Conference on Parallel Problem Solving from Nature, 1992, pp. 479–488. M. Silvoso, E. M. R. Fairbairn, M. Asce, R. D. T. Filho, N. F. F. Ebecken, and J. L. D. Alves, “Optimization of Dam Construction Costs Using,” in Concrete, 2003, pp. 154–161. S. Sun and F. Du, “Robust optimization for shape design of arch dams based on strain energy,” in Applied Mechanics and Materials, 2015, vol. 777, pp. 94–100. Pourbakhshian, M. Ghaemian, and A. Joghataie, “Shape optimization of concrete arch dams considering stage construction,” Sci. Iran., vol. 23, no. 1, pp. 21–35, 2016, doi: 10.24200/sci.2016.2094. Akbari, M. T. Ahmadi, and H. Moharrami, “Advances in concrete arch dams shape optimization,” Appl. Math. Model., vol. 35, no. 7, pp. 3316–3333, Jul. 2011, doi: 10.1016/j.apm.2011.01.020. A. H. S. and . N. W. awaid A., “Optimum Analysis and Design of Curved Concrete Dams,” Iraqi J. Civ. Eng., vol. 11, no. 3, pp. 32–51, 2017, doi: 10.37650/ijce.2017.172892. J. Araujo, A. Vieira, and D. Gutstein, “Optimization study for the cross-section of a concrete gravity dam: Genetic algorithm model and application,” Rev. Int. Metod. Numer. para Calc. y Disen. en Ing., 2019, doi: 10.23967/j.rimni.2019.06.002. Q. Wang, R. H. Zhao, Y. Liu, Y. Z. Chen, and X. Y. Ma, “Shape optimization of single-curvature arch dam based on sequential Kriging-genetic algorithm,” Appl. Sci., vol. 9, no. 20, p. 12, Oct. 2019, doi: 10.3390/app9204366. Gholizadeh and S. M. Seyedpoor, “Shape optimization of arch dams by metaheuristics and neural networks for frequency constraints,” Sci. Iran., vol. 18, no. 5, pp. 1020–1027, 2011. H. Kadoury, MEAN RAINFALL IN KHASA CHAI CATCHMENTS. 2005, p. 16. Zhou, A. Nekouie, C. A. Arslan, B. T. Pham, and M. Hasanipanah, “Novel approach for forecasting the blast-induced AOp using a hybrid fuzzy system and firefly algorithm,” Eng. Comput., vol. 36, no. 2, pp. 703–712, 2020, doi: 10.1007/s00366-019-00725-0. Zhou, C. Li, C. A. Arslan, M. Hasanipanah, and H. Bakhshandeh Amnieh, “Performance evaluation of hybrid FFA-ANFIS and GA-ANFIS models to predict particle size distribution of a muck-pile after blasting,” Springer London, 2021. doi: 10.1007/s00366-019-00822-0. Shashi Kumar Sharma, Irrigation Engineering and Hydraulic Structures, 4th ed. NEW DELHI: S Chand & Co Ltd, 2017. Darwin, ENGINEERING GUIDELINE FOR THE EVALUATION OF HYDROPOWER PROJECTS, vol. XXX. England, 1991. Chaoran Fu and Bjartmar Porri Haflidason, “Progressive failure analyses of concrete buttress dams,” 2015. [Online]. Available: https://www.diva-portal.org/smash/record.jsf?pid=diva2:824952 Bäck, Evolutionary Algorithms in Theory and Practice. Oxford University Press, 1996. doi: 10.1093/oso/9780195099713.001.0001. H. (John H. Holland and J. H, Adaptation in natural and artificial systems : an introductory analysis with applications to biology, control, and artificial intelligence. Ann Arbor SE -: University of Michigan Press Ann Arbor, 1992. doi: LK - https://worldcat.org/title/1531617. L. Torres and N. B. Linsangan, “Application of Genetic Algorithm for Optimization of Data in Surface Myoelectric Prosthesis for the Transradial Amputee,” Int. J. Inf. Educ. Technol., vol. 5, no. 2, pp. 113–118, 2015, doi: 10.7763/ijiet.2015.v5.486. N. Sivanandam and S. N. Deepa, “Genetic Algorithms BT - Introduction to Genetic Algorithms,” S. N. Sivanandam and S. N. Deepa, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008, pp. 15–37. doi: 10.1007/978-3-540-73190-0_2. Santosh Kumar Garg, Irrigation Engineering And Hydraulic Structures, vol. 20, no. 1. 1986. doi: 10.1201/b19987-15. Sachdeva, S. Chakraborty, and S. Ray-Chaudhuri, Seismic response control of a structure isolated by flat sliding bearing and nonlinear restoring spring: Experimental study for performance evaluation, vol. 159. 2018. doi: 10.1016/j.engstruct.2017.12.033.
Statistics Article View: 892 PDF Download: 43