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Optimum design of steel columns filled with concrete via genetic algorithm: environmental impact and cost analysis
Abstract The use of concrete-filled tubular columns as part of structural systems has steadily increased throughout the years. The growing demand for structural elements of this nature is a direct result of the possibility to use various cross-section shapes that have increased strength, along with resistance to fire and other corrosive agents. The main objective of this article is to present the formulation for optimizing the design of composite columns in accordance with prescriptions from ABNT NBR 16239: 2013, considering financial cost and CO2 emission during manufacturing as objective functions. A Genetic Algorithm was used to solve three examples of composite tubular columns subjected to combined bending and compression, considering major axis and unsymmetrical bending. The financial cost in Brazilian currency and the CO2 emission in kilograms attributed to manufacturing concrete-filled composite columns were calculated and the optimization procedure was implemented on composite columns featuring CHS, RHS and SHS steel members. This study also considers the different concrete strengths and the optional inclusion of longitudinal rebar. For the cases analyzed, the financially and environmentally optimum design corresponds to a CHS composite column with no longitudinal rebar and the highest concrete strength tested, except when unsymmetrical bending is applied, in which case the optimum solution includes longitudinal rebar. Furthermore, results indicate that structural steel has the highest impact on the CO2 emission of the optimal designs. For the column with longitudinal rebar, the reinforcement steel presents the second highest financial impact, while concrete is responsible for the highest influence on CO2 emission.
Optimum design of steel columns filled with concrete via genetic algorithm: environmental impact and cost analysis
Abstract The use of concrete-filled tubular columns as part of structural systems has steadily increased throughout the years. The growing demand for structural elements of this nature is a direct result of the possibility to use various cross-section shapes that have increased strength, along with resistance to fire and other corrosive agents. The main objective of this article is to present the formulation for optimizing the design of composite columns in accordance with prescriptions from ABNT NBR 16239: 2013, considering financial cost and CO2 emission during manufacturing as objective functions. A Genetic Algorithm was used to solve three examples of composite tubular columns subjected to combined bending and compression, considering major axis and unsymmetrical bending. The financial cost in Brazilian currency and the CO2 emission in kilograms attributed to manufacturing concrete-filled composite columns were calculated and the optimization procedure was implemented on composite columns featuring CHS, RHS and SHS steel members. This study also considers the different concrete strengths and the optional inclusion of longitudinal rebar. For the cases analyzed, the financially and environmentally optimum design corresponds to a CHS composite column with no longitudinal rebar and the highest concrete strength tested, except when unsymmetrical bending is applied, in which case the optimum solution includes longitudinal rebar. Furthermore, results indicate that structural steel has the highest impact on the CO2 emission of the optimal designs. For the column with longitudinal rebar, the reinforcement steel presents the second highest financial impact, while concrete is responsible for the highest influence on CO2 emission.
Optimum design of steel columns filled with concrete via genetic algorithm: environmental impact and cost analysis
Sane Alves Guimarães (author) / Diego Klein (author) / Adenilcia Fernanda Grobério Calenzani (author) / Élcio Cassimiro Alves (author)
2022
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
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