Manta Ray Foraging and Jaya Hybrid Optimization of Concrete Filled Steel Tubular Stub Columns Based on CO2 Emission

Abstract

Concrete-filled steel tubular (CFST) columns exhibit favorable characteristics and have been studied extensively particularly through experiments. However, the CO2 emission in the production process of these structural members should be reduced to minimize the environmental impact. At the same time, the performance of these structures should be kept at a satisfactory level. This can be achieved using metaheuristic optimization algorithms. The most commonly used indicator of structural performance for CFST columns is the ultimate axial load carrying capacity (Nu). This quantity can be predicted using various equations available in design codes and the research literature. However, most of these equations are only applicable within certain parameter ranges. A recently developed set of equations from the CFST literature was applied for the prediction of Nu due to its improved ranges of applicability. Furthermore, novel metaheuristic algorithms called Manta Ray Foraging Optimization and, Jaya algorithm are applied to the cross-section optimization of rectangular CFST columns. The improvement of the structural dimensioning under Nu constraint was demonstrated. The objective of optimization was to minimize the CO2 emission associated with the fabrication of CFST stub columns. For different concrete classes and load capacities, the optimum cross-sectional dimensions have been obtained.