Optimization of Reinforced Concrete Deep Beams Using Data-Driven Parametric Performance Indicators
Abstract
The present study proposes a multi-objective optimization model for reinforced concrete deep beams based on the study and improvement of structural performance using multi objective optimization. In traditional design methodologies, the complex relationships between various parameters are generally ignored. The present study was based on the formulation of four objectives: (Cross-sectional Efficiency), (Reinforcement Contribution Ratio), (Tensile Mechanism), and (Structural Gradient). The objectives , , , and were combined with various parameters and material characteristics to obtain optimal design findings. and are related to efficient cross-sectional design and uniform stress. and are related to tensile and compressive effects of vertical and horizontal bars. The conclusions revealed efficient design and proportions of reinforced materials for capacities to bear loads and minimal use of materials. The importance of multi-objective optimization is emphasized in the discussion, which states that it gives a more precise view of structural behavior than the conventional single-parameter design. In general, the paper has established a generalized design approach for reinforced concrete deep beams that incorporate efficiency, safety, and practicability. The results of this research provide valuable information for engineers and pave the way for further experimental verification and parametric studies.
References
- P. Salehi, R. Aghayari, and M. Fazelikelareh, “Behavioral Analysis of Reinforced Concrete Deep Beams under Dynamic Loading with Varying Strain Rates Using the Strut-and-Tie Model Framework,” Civil Engineering Infrastructures Journal, Nov. 2025, doi: 10.22059/CEIJ.2025.398909.2350.
- M. R. Kaloop et al., “Shear Strength Estimation of Reinforced Concrete Deep Beams Using a Novel Hybrid Metaheuristic Optimized SVR Models,” Sustainability (Switzerland), vol. 14, no. 9, May 2022, doi: 10.3390/su14095238.
- F. Cakir and M. A. Ozdemir, “Strut-and-Tie Modeling of Intraply Hybrid Composite-Strengthened Deep RC Beams,” Buildings 2025, Vol. 15, Page 3810, vol. 15, no. 21, p. 3810, Oct. 2025, doi: 10.3390/buildings15213810.
- H. Chen, Y. Sun, and M. Deng, “Research on the Reinforcement Design of Concrete Deep Beams with Openings Based on the Strut-and-Tie Model,” Buildings 2025, Vol. 15, Page 1382, vol. 15, no. 8, p. 1382, Apr. 2025, doi: 10.3390/buildings15081382.
- W. A. Jasim, A. A. Allawi, and N. K. Oukaili, “Strength and Serviceability of Reinforced Concrete Deep Beams with Large Web Openings Created in Shear Spans,” Civil Engineering Journal, vol. 4, no. 11, pp. 2560–2574, Nov. 2018, doi: 10.28991/cej-03091181.
- M. Mansour and T. El-Maaddawy, “Testing and modeling of deep beams strengthened with NSM-CFRP reinforcement around cutouts,” Case Studies in Construction Materials, vol. 15, no. 3, pp. 145–152, Dec. 2021, doi: 10.1016/j.cscm.2021.e00670.
- A. Al-khreisat, M. Abdel-Jaber, and A. Ashteyat, “Shear Strengthening and Repairing of Reinforced Concrete Deep Beams Damaged by Heat Using NSM–CFRP Ropes,” Fibers, vol. 11, no. 4, Apr. 2023, doi: 10.3390/fib11040035.
- A. Al Ismaeel, F. Amin, and A. Husnain, “Predicting the shear strength of RC deep beams with wide openings using FEM and machine learning-based Ni-Ti SMA retrofitting,” Results in Engineering, vol. 29, no. 6, p. 109320, Mar. 2026, doi: 10.1016/j.rineng.2026.109320.
- Q. Hussain and A. Pimanmas, “Shear strengthening of RC deep beams with openings using Sprayed Glass Fiber Reinforced Polymer Composites (SGFRP) : Part 1. Experimental study,” KSCE Journal of Civil Engineering, vol. 19, no. 7, pp. 2121–2133, Feb. 2015, doi: 10.1007/s12205-015-0243-1.
- J. M. Mhalhal, T. S. Al-Gasham, and S. R. Abid, “Tests on reinforced concrete deep beams with different web reinforcement types,” IOP Conf. Ser. Mater. Sci. Eng., vol. 988, no. 1, Dec. 2020, doi: 10.1088/1757-899X/988/1/012032.
- C. Ma, S. Wang, J. Zhao, X. Xiao, C. Xie, and X. Feng, “Prediction of shear strength of RC deep beams based on interpretable machine learning,” Constr. Build. Mater., vol. 387, Jul. 2023, doi: 10.1016/j.conbuildmat.2023.131640.
- A. Tiwari, A. K. Gupta, and T. Gupta, “A robust approach to shear strength prediction of reinforced concrete deep beams using ensemble learning with SHAP interpretability,” Soft Comput., vol. 28, no. 7–8, pp. 6343–6365, Apr. 2023, doi: 10.1007/s00500-023-09495-w.
- K. Le Nguyen, H. Thi Trinh, T. T. Nguyen, and H. D. Nguyen, “Comparative study on the performance of different machine learning techniques to predict the shear strength of RC deep beams: Model selection and industry implications,” Expert Syst. Appl., vol. 230, Nov. 2023, doi: 10.1016/j.eswa.2023.120649.
- D. C. Feng, W. J. Wang, S. Mangalathu, G. Hu, and T. Wu, “Implementing ensemble learning methods to predict the shear strength of RC deep beams with/without web reinforcements,” Eng. Struct., vol. 235, May 2021, doi: 10.1016/j.engstruct.2021.111979.
- H. Chen, W. J. Yi, and H. J. Hwang, “Cracking strut-and-tie model for shear strength evaluation of reinforced concrete deep beams,” Eng. Struct., vol. 163, pp. 396–408, May 2018, doi: 10.1016/j.engstruct.2018.02.077.
- M. M. Hameed, F. Khaleel, M. K. AlOmar, S. F. Mohd Razali, and M. A. Alsaadi, “Optimising the selection of input variables to increase the predicting accuracy of shear strength for deep beams,” Complexity, vol. 2022, 2022, doi: 10.1155/2022/6532763.
- M. Shahnewaz, A. Rteil, and M. S. Alam, “Shear strength of reinforced concrete deep beams—A review with improved model by genetic algorithm and reliability analysis,” Structures, vol. 23, pp. 494–508, Feb. 2020, doi: 10.1016/j.istruc.2019.09.006.
- A. F. Ashour, L. F. Alvarez, and V. V. Toropov, “Empirical modelling of shear strength of RC deep beams by genetic programming,” Comput. Struct., vol. 81, no. 5, pp. 331–338, Mar. 2003, doi: 10.1016/S0045-7949(02)00437-6.
- M. V. G. Silveira, L. A. G. Bitencourt, and S. Das, “Generative design framework for RC deep beams using topology optimization and generative tie method: Experimental and numerical investigation,” Eng. Struct., vol. 316, p. 118490, Oct. 2024, doi: 10.1016/j.engstruct.2024.118490.
- “(PDF) APPLICATION OF TOPOLOGY OPTIMIZATION ON DEEP BEAMS.” Accessed: Feb. 05, 2026. [Online]. Available: https://www.researchgate.net/publication/360943746_APPLICATION_OF_TOPOLOGY_OPTIMIZATION_ON_DEEP_BEAMS
- Q. F. Hasan, D. A. Al-Mamany, and O. K. Fayadh, “Design of Reinforced Concrete Deep Beams using Particle Swarm Optimization Technique,” Karbala International Journal of Modern Science, vol. 5, no. 4, pp. 254–265, 2019, doi: 10.33640/2405-609X.1180.
- H.-Z. Zhang, Z.-S. Wu, X.-X. Yuan, and W.-T. Xu, “Performance of Deep Beams with Topologically Optimized Reinforcements: Experimental Verification and Comparison,” Journal of Structural Engineering, vol. 151, no. 4, p. 04025019, Apr. 2025, doi: 10.1061/jsendh.steng-13495.
- H. Wang, C. Zhang, and H. Wu, “Shear Capacity Prediction Model of Deep Beam Based on New Hybrid Intelligent Algorithm,” Buildings 2023, Vol. 13, Page 1395, vol. 13, no. 6, p. 1395, May 2023, doi: 10.3390/buildings13061395.
- E. H. Houssein, M. Hossam Abdel Gafar, N. Fawzy, and A. Y. Sayed, “Recent metaheuristic algorithms for solving some civil engineering optimization problems,” Scientific Reports 2025 15:1, vol. 15, no. 1, pp. 7929-, Mar. 2025, doi: 10.1038/s41598-025-90000-8.
Downloads
Similar Articles
- Nada Salih , A field study compares the use of glass with traditional materials in the context of Dubai. A field study compares the use of glass with traditional materials in the context of Dubai , Emirati Journal of Civil Engineering and Applications: Vol. 3 No. 2 (2025): Emirati Journal of Civil Engineering and Applications
- Nada Salih , The thermal efficacy of double, triple, and quadruple glazing under the extreme heat conditions prevalent in Dubai's climate (A field-based investigation). , Emirati Journal of Civil Engineering and Applications: Vol. 3 No. 2 (2025): Emirati Journal of Civil Engineering and Applications
- Imad Chobaki, Hamza Yakub, Sokrates Ioannou, Small scale testing of shear-bond behavior in composite deck slabs with profiled steel sheeting , Emirati Journal of Civil Engineering and Applications: Vol. 3 No. 2 (2025): Emirati Journal of Civil Engineering and Applications
- Mohamed Wehbi, Marwan Alzaylaie, Otso Lahtinen, Reducing the effect of rising water table on the shallow foundation settlement using geopolymer resin injections , Emirati Journal of Civil Engineering and Applications: Vol. 3 No. 1 (2025): Emirati Journal of Civil Engineering and Applications
- Seyed Amir Hossein, Adil Al Tamimi, Ghanim Kashwani, Application of JIT on Materials and Labor Management of Construction Site , Emirati Journal of Civil Engineering and Applications: Vol. 2 No. 1 (2024): Emirati Journal of Civil Engineering and Applications
- Morsaleen S Chowdhury, Abdullah M S Al-Hadhrami, Mohammed Abdelfattah, Nasra S S Al Sharji, Sokrates Ioannou, Potential of coastal armour units as energy dissipators to enhance the characteristics of hydraulic jumps , Emirati Journal of Civil Engineering and Applications: Vol. 2 No. 2 (2024): Emirati Journal of Civil Engineering and Applications
- Yasir Zaman, Fayiz Amin, Muhammad Asif, Khan Abdul Majid, Niazi Ehsanullah, Investigating the Compressive Response of Hand-Laminated GFRP Pipes in the Hoop Direction through Experiment and FEM Modeling , Emirati Journal of Civil Engineering and Applications: Vol. 2 No. 2 (2024): Emirati Journal of Civil Engineering and Applications
- Mohamed Abdalla Lootah, In Ju Kim, Zafar Said, Fire Safety and Resilience in UAE High-Rise Buildings (Integrating Materials, Codes, and Management Systems under Extreme Climatic Conditions) , Emirati Journal of Civil Engineering and Applications: Vol. 4 No. 1 (2026): Emirati Journal of Civil Engineering and Applications
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Tufail Mabood, Prediction of Beam-Column Joint Shear Strength Using Machine Learning and a Proposed Design Equation , Emirati Journal of Civil Engineering and Applications: Vol. 4 No. 1 (2026): Emirati Journal of Civil Engineering and Applications
- Tufail Mabood, Development of a Standalone Application for Accurate and User-Friendly Prediction of Concrete Compressive Strength Using Ensemble Machine Learning , Emirati Journal of Civil Engineering and Applications: Vol. 4 No. 1 (2026): Emirati Journal of Civil Engineering and Applications