Load-Bearing Capacity Analysis and Optimization of Beams, Slabs, and Columns

Abstract

This study investigates the load-bearing capacity and optimization of structural elements—beams, slabs, and columns—using quantitative modeling and analysis based on material type, geometric dimensions, applied load, and safety factors. A dataset comprising ten structural elements was analyzed, with load-bearing capacities ranging from 7,130.9 kN to 113,169.6 kN and utilization ratios between 0.01 and 0.06 in the original configurations. Correlation analysis revealed that volume (r = 0.98), length (r = 0.59), and width (r = 0.37) had strong to moderate positive relationships with load-bearing capacity, while utilization ratio showed a strong inverse correlation (r = -0.52). A linear regression model demonstrated that width (β = 72,951.73), depth (β = 58,328.83), and strength (β = 989.31) had the most significant positive contributions to capacity, while safety factor (β = -10,689.44) had a substantial negative effect. Optimization results showed that structural elements designed with composite and steel materials, and optimized dimensions (e.g., 1.20 m width, 1.10 m depth for composite beams), achieved load-bearing capacities up to 30,500 kN with utilization ratios increased to as high as 0.90, and safety factors maintained within the range of 1.40 to 2.00. The study concludes that data-driven optimization significantly improves structural efficiency, capacity utilization, and material performance.