Research Information System
4th International Conference on Sustainable Construction Materials and Technologies, SCMT 2016, Nevada, United States Of America, 7 - 11 August 2016, (Full Text)
The building construction industry consumes large amounts of energy and creates substantial pollution by producing a large portion of CO2 emissions. In addition to the energy consumed from the operation of the building, the energy consumed from both materials in the construction phase must be reduced to minimize the life-cycle energy use of a building. In this study, an optimal design method for RC columns in buildings using Social-Spider Optimization (SSO) algorithm is proposed to reduce the cost and CO2 emissions from the structural materials in the construction phase. Objective functions of the optimization problem are defined as the minimized cost, the CO2 emission, and the weighted aggregate of the cost and CO2. In the formulation of the objective functions, unit costs are based on the materials and labor required for the construction of RC columns and CO2 emissions are associated with the transportation, processing, manufacturing, and fabrication of materials and the emissions of the equipment involved in the construction process. In the formulation of the optimum design problem, the sectional properties of RC columns with rectangular cross section that are subjected to axial force and bi-axial bending moment such as the dimensions of the rectangular cross section along x and y direction, the diameters of bars and their total number along x and y directions are taken as design variables. The design constraints are implemented from ACI 318-14 which consist of columns strength check under axial compression and biaxial bending, the minimum and maximum steel ratio, the minimum and maximum bar spacing and the minimum column width restrictions. The proposed SSO based optimal design method is applied to two numerical design examples to investigate the effective use of structural materials for the sustainable design of RC columns and to demonstrate the efficiency and robustness of the presented algorithm. © 2016 International Committee of the SCMT conferences.