Open AccessFactors in the Relationship Between Optimal CO2 Emission and Optimal Cost of the RC Frames
Author(s) -
L. Mottaghi,
Ramezan Ali Izadifard,
A. Kaveh
Publication year - 2020
Publication title -
periodica polytechnica. civil engineering/periodica polytechnica. civil engineering (online)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.406
H-Index - 19
eISSN - 1587-3773
pISSN - 0553-6626
DOI - 10.3311/ppci.16790
Subject(s) - ductility (earth science) , greenhouse gas , structural engineering , frame (networking) , class (philosophy) , optimal design , reinforced concrete , environmental science , computer science , engineering , materials science , geology , telecommunications , composite material , creep , oceanography , artificial intelligence , machine learning
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.