CO2 Emission and Cost Optimization of Concrete-Filled Steel Tubular (CFST) Columns Using Metaheuristic Algorithms

Concrete-filled steel tubular columns have garnered wide interest among researchers due to their favorable structural characteristics. To attain the best possible performance from concrete-filled while reducing cost, use of optimization algorithms is indispensable. In this regard, metaheuristic are finding increasing application in engineering high efficiency. Various equations that predict ultimate axial load-carrying capacity (Nu) available design codes as well research literature. However, most these only applicable within certain parameter ranges. overcome limitation, present study adopts a recently developed set for prediction Nu broader ranges applicability. Furthermore, newly algorithm, called social spider introduced and applied optimizing cross-section circular columns. The improvement dimensioning under constraint demonstrated. objective underlying presented here minimize CO2 emission cost associated with fabrication stub context, relationships between cross-sectional emissions characterized visualized.