Optimization of Reinforced Concrete Deep Beams Using Data-Driven Par-ametric Performance Indicators

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: F_1 (Cross-sectional Efficiency), F_2 (Reinforcement Contribution Ratio), F_3 (Tensile Mechanism), and F_4 (Structural Gradient). The objectives F_1, F_2, F_3, and F_4 were combined with various parameters and material characteristics to obtain optimal design findings. F_1 and F_4 are related to efficient cross-sectional design and uniform stress. F_2 and F_3 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