Multi-objective sustainable design of reinforced concrete cylindrical tall structures by using metaheuristic algorithms

Abstract

While creating structural model, it is required that evaluation different and various alternative scenarios to provide sustainable conditions for the environment, and nature besides that structures have characteristics as strength and serviceability. However, this process needs extremely long times together with much effort to find out the desired properties. Concordantly, optimization technologies can be evaluated to use in overcoming the mentioned disadvantages. Regarding this, in this study, reinforced concrete cylindrical wall was dealt for generating an optimum structure by providing cost-minimization besides making possible eco-friendly design conditions. The best structural models were also evaluated according to variable concrete strengths and wall heights in separate cases as single and multi-objective ones. Meanwhile, a metaheuristic method as flower pollination algorithm was handled to detect the best values of structural parameters including total reinforcement and concrete amount, appropriate spacing between reinforcements, etc. Also, a different optimization methodology was applied for reinforced concrete structures in order to evaluate different aims, like both sustainability and economic conditions, besides independent objectives. In this respect, the minimum cost, and CO₂ can be determined together for different structural parameters like concrete compressive strength, wall height, etc. By this regard, multi-objective optimization processes can be utilized to investigate different structural models in order to focus on fundamental purposes like minimum cost, and emission values besides maximum seismic safety of structures.

Graphical abstract

Keywords

reinforced concrete / CO₂ emission / multi-objective optimization / cost minimization / eco-friendly design

References

[1] Ganzerli S, Pantelides C P, Reaveley L D. Performance-based design using structural optimization. Earthquake Engineering and Structural Dynamics, 2000, 29(11): 1677–1690

[2] Aktas E, Moses F, Ghosn M. Cost and safety optimization of structural design specifications. Reliability Engineering and System Safety, 2001, 73(3): 205–212

[3] Sirca G F Jr, Adeli H. Cost optimization of prestressed concrete bridges. Journal of Structural Engineering, 2005, 131(3): 380–388

[4] Wall W A, Frenzel M A, Cyron C. Isogeometric structural shape optimization. Computer Methods in Applied Mechanics and Engineering, 2008, 197(33–40): 2976–2988

[5] Zordan T, Briseghella B, Mazzarolo E. Bridge structural optimization through step-by-step evolutionary process. Structural Engineering International, 2010, 20(1): 72–78

[6] Ghasemi H, Rafiee R, Zhuang X, Muthu J, Rabczuk T. Uncertainties propagation in metamodel-based probabilistic optimization of CNT/polymer composite structure using stochastic multi-scale modeling. Computational Materials Science, 2014, 85: 295–305

[7] Ghasemi H, Brighenti R, Zhuang X, Muthu J, Rabczuk T. Optimal fiber content and distribution in fiber-reinforced solids using a reliability and NURBS based sequential optimization approach. Structural and Multidisciplinary Optimization, 2015, 51(1): 99–112

[8] YucelMNigdeli S MBekdaşG. Optimum design of tubular columns for different cases by using prediction model generated via artificial neural networks. In: IV. Eurasian Conference on Civil and Environmental Engineering (ECOCEE). İstanbul, 2019, 17–18

[9] Shaqfa M, Orbán Z. Modified parameter-setting-free harmony search (PSFHS) algorithm for optimizing the design of reinforced concrete beams. Structural and Multidisciplinary Optimization, 2019, 60(3): 999–1019

[10] Georgioudakis M, Plevris V. A comparative study of differential evolution variants in constrained structural optimization. Frontiers in Built Environment, 2020, 6: 102

[11] Yücel M, Kayabekir A E, Bekdaş G, Nigdeli S M, Kim S, Geem Z W. Adaptive-hybrid harmony search algorithm for multi-constrained optimum eco-design of reinforced concrete retaining walls. Sustainability, 2021, 13(4): 1639

[12] Brandão F D S, de Almeida A K, Miguel L F F. Optimum design of single and multiple tuned mass dampers for vibration control in buildings under seismic excitation. International Journal of Structural Stability and Dynamics, 2022, 22(8): 2250078

[13] Ghaderi A, Nouri M, Hoseinzadeh L, Ferdousi A. Hybrid vibration control of tall tubular structures via combining base isolation and mass damper systems optimized by enhanced special relativity search algorithm. Iranian Journal of Science and Technology, Transactions of Civil Engineering, 2024, 48: 3373–3391

[14] Bekdaş G, Yücel M, Nigdeli S M. Estimation of optimum design of structural systems via machine learning. Frontiers of Structural and Civil Engineering, 2021, 15(6): 1441–1452

[15] Karimi Sharafshadeh B, Ketabdari M J, Azarsina F, Amiri M, Nehdi M L. New fuzzy-heuristic methodology for analyzing compression load capacity of composite columns. Buildings, 2023, 13(1): 125

[16] Yucel M, Bekdaş G, Nigdeli S M. Machine learning-based model for prediction of optimum TMD parameters in time-domain history. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2024, 46(4): 192

[17] Lee M G, An J H, Bae S G, Oh H S, Choi J, Yun D Y, Hong T, Lee D E, Park H S. Multi-objective sustainable design model for integrating CO₂ emissions and costs for slabs in office buildings. Structure and Infrastructure Engineering, 2020, 16(8): 1096–1105

[18] Kaveh A, Izadifard R A, Mottaghi L. Optimal design of planar RC frames considering CO₂ emissions using ECBO, EVPS and PSO metaheuristic algorithms. Journal of Building Engineering, 2020, 28: 101014

[19] Yepes V, Martí J V, García J. Black hole algorithm for sustainable design of counterfort retaining walls. Sustainability (Basel), 2020, 12(7): 2767

[20] Yücel M, Nigdeli S M, Bekdaş G. Generation of sustainable models with multi-objective optimum design of reinforced concrete (RC) structures. Structures, 2022, 40: 223–236

[21] Negrin I A, Chagoyén E L. Economic and environmental design optimisation of reinforced concrete frame buildings: A comparative study. Structures, 2022, 38: 64–75

[22] Tres Junior F L, Yepes V, de Medeiros G F, Kripka M. Multi-objective optimization applied to the design of sustainable pedestrian bridges. International Journal of Environmental Research and Public Health, 2023, 20(4): 3190

[23] dos Santos N R, Alves E C, Kripka M. Towards sustainable reinforced concrete beams: multi-objective optimization for cost, CO₂ emission, and crack prevention. Asian Journal of Civil Engineering, 2024, 25(1): 575–582

[24] YangX S. Flower pollination algorithm for global optimization. In: Proceedings of Unconventional Computation and Natural Computation (UCNC 2012). Berlin-Heidelberg: Springer-Verlag, 2012, 240–249

[25] TS500. Turkish Standard Requirements for Design and Construction of Reinforced Concrete Structures. Ankara-Turkey, 2000

[26] Paya-Zaforteza I, Yepes V, Hospitaler A, Gonzalez-Vidosa F. CO₂-optimization of reinforced concrete frames by simulated annealing. Engineering Structures, 2009, 31(7): 1501–1508

[27] Yepes V, Gonzalez-Vidosa F, Alcala J, Villalba P. CO₂-optimization design of reinforced concrete retaining walls based on a VNS-threshold acceptance strategy. Journal of Computing in Civil Engineering, 2012, 26(3): 378–386

[28] Republic of Turkey Ministry of Environment and Urbanization, Directorate of Higher Technical Board. Construction and Installation Unit Prices, 2022

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11709-025-1171-x and is accessible for authorized users.

Funding note

Open access funding provided by the Scientific and Technological Research Council of Türkiye (TÜBİTAK).

Open Access

This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Competing interests

The authors declare that they have no competing interests.

RIGHTS & PERMISSIONS

2025 The Author(s). This article is published with open access at link.springer.com and journal.hep.com.cn