Factors in the Relationship Between Optimal CO2 Emission and Optimal Cost of the RC Frames

Abstract

Nowadays, reduction of greenhouse gases emissions from the construction industry is seriously under investigation. The aim of this study is to investigate the various effective factors on the relationship between optimal cost and optimal carbon dioxide emissions of the reinforced concrete structures with nonlinear structural behavior. A four-story reinforced concrete frame is designed for various peak ground accelerations (PGAs) and all ductility classes according to Iran’s seismic resistant design-2800 code, as well as for different concrete classes. The frames are optimally designed according to ACI 318-08 and FEMA codes. The results of optimal designs show that the design of structures with medium and high ductility class produces less cost and CO2 emissions than the low ductility class. On the other hand, the relationship between cost and CO2 emissions shows that in the low ductility class, increasing the percentage of the optimal cost can greatly reduce the amount of CO2 emissions. PGA design has a significant effect on reducing optimal cost and CO2 emissions. Especially in the low ductility class, reducing this parameter can greatly decrease the amount of the objective functions. Also, the use of concrete with low class can reduce the cost and CO2 emissions but the effect of this parameter in the objective is very small.

Optimization of Columns and Bent Caps of RC Bridges for Cost and CO2 Emission

“…Construction industry has a remarkable contribution on GHG, and carbon dioxide (CO 2 ) is a major part of it. Studies have employed the strategies to reduce the CO 2 emissions from the reinforced concrete (RC) structure, one of which is the use of optimization techniques during the design phase of RC frames [7][8][9][10][11][12]. Studies have been conducted to reduce CO 2 emissions on bridges.…”

Optimal Design of Mixed Structures under Time-history Loading Using Metaheuristic Algorithm

“…In the past decades, the optimal design of the structures has been investigated that the main goal of the optimization is to use minimum weight of the materials, optimum size of the large-scale steel structures, minimum cost of the reinforced concrete frames [23][24][25] and control the plastic behavior of reinforced concrete [26] by different metaheuristic algorithms for example genetic algorithm (GA) [27], simulated annealing optimization (SAO) [28], particle swarm optimization (PSO) [29], ant colony optimization (ACO) [30], enhanced colliding bodies optimization (ECBO) [31], vibrating particles system (VPS) [32], harmony search (HS) [33], big bang-big crunch (BB-BC [34], charged system search (CSS) [35], teachinglearning-based optimization (TLBO) [36], bi-directional evolutionary structural optimization (BESO) [37], plasma generation optimization (PGO) [38], and improved plasma generation optimization (IPGO) [39] but all of them the previous studies are about the optimum design of the steel structures and reinforced concrete (RC) frame structures.…”