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Optimization-Based Design of Reinforced Concrete Cantilever Retaining Walls Considering Embodied Energy, Carbon Emissions, and Cost
https://orcid.org/http://orcid.org/0000-0002-2102-9748
Sustainable design has become the top agenda among civil engineers to combat the rise of climate change. While computational advancements have enabled objective-based designs, sustainability requires a balanced optimization of a combination of cost, environmental, and safety factors. While metaheuristic algorithms have proven effective for multi-objective optimization, researchers are uncertain which objectives should be considered for sustainable design. Thus, this study conducts a comparative evaluation of six objective functions (three single-objective and three multi-objective) using the genetic algorithm to enhance the sustainability of design for a reinforced concrete cantilever retaining wall. The study explores material cost, carbon emissions, and embodied energy functions, with the latter investigated for the first time for retaining walls. It is revealed through a graphical analysis that cost and energy are superior objectives for sustainability, both individually and in combination. Conversely, the carbon emission objective has relatively adverse effects on the overall sustainability of the retaining wall.
Optimization-Based Design of Reinforced Concrete Cantilever Retaining Walls Considering Embodied Energy, Carbon Emissions, and Cost
https://orcid.org/http://orcid.org/0000-0002-2102-9748
Sustainable design has become the top agenda among civil engineers to combat the rise of climate change. While computational advancements have enabled objective-based designs, sustainability requires a balanced optimization of a combination of cost, environmental, and safety factors. While metaheuristic algorithms have proven effective for multi-objective optimization, researchers are uncertain which objectives should be considered for sustainable design. Thus, this study conducts a comparative evaluation of six objective functions (three single-objective and three multi-objective) using the genetic algorithm to enhance the sustainability of design for a reinforced concrete cantilever retaining wall. The study explores material cost, carbon emissions, and embodied energy functions, with the latter investigated for the first time for retaining walls. It is revealed through a graphical analysis that cost and energy are superior objectives for sustainability, both individually and in combination. Conversely, the carbon emission objective has relatively adverse effects on the overall sustainability of the retaining wall.
Optimization-Based Design of Reinforced Concrete Cantilever Retaining Walls Considering Embodied Energy, Carbon Emissions, and Cost
https://orcid.org/http://orcid.org/0000-0002-2102-9748
Sustainable design has become the top agenda among civil engineers to combat the rise of climate change. While computational advancements have enabled objective-based designs, sustainability requires a balanced optimization of a combination of cost, environmental, and safety factors. While metaheuristic algorithms have proven effective for multi-objective optimization, researchers are uncertain which objectives should be considered for sustainable design. Thus, this study conducts a comparative evaluation of six objective functions (three single-objective and three multi-objective) using the genetic algorithm to enhance the sustainability of design for a reinforced concrete cantilever retaining wall. The study explores material cost, carbon emissions, and embodied energy functions, with the latter investigated for the first time for retaining walls. It is revealed through a graphical analysis that cost and energy are superior objectives for sustainability, both individually and in combination. Conversely, the carbon emission objective has relatively adverse effects on the overall sustainability of the retaining wall.
Optimization-Based Design of Reinforced Concrete Cantilever Retaining Walls Considering Embodied Energy, Carbon Emissions, and Cost
J. Inst. Eng. India Ser. A
Shakeel, Mansoor (Autor:in) / Azam, Rizwan (Autor:in) / Riaz, Muhammad Rizwan (Autor:in) / Shihata, Ayman (Autor:in)
Journal of The Institution of Engineers (India): Series A ; 105 ; 629-639
01.09.2024
11 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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