A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
The initial planning and designing stage of a project is very crucial for deciding the most efficient and effective design solution from various available options that directly impact sustainability. The optimal solution for reinforced concrete structures can include a lot of repetitive calculations for finding the most optimized and feasible solution, which is impractical manually and semi-automatically using structural analysis software. Therefore, the aim of the research is the automation of the design process which may well be the answer for solving repetitive problems efficiently and reliably by providing optimal solutions in terms of time, cost and embodied carbon emissions leading to an optimized design of a structure and contributing to sustainability in construction and real estate industry. One such method of automation is optimizing using a genetic algorithm in MATLAB which is a metaheuristic method and has proved to provide optimal and robust results in past research. To understand the results of the genetic algorithm, it is compared with the manual calculations for various elements such as beam, column, slabs and building frame. The building information modelling tools such as Revit and Tekla are used for visualizing the results. The automation of the design process by incorporating Eurocode principles and constraints indicate that the cost saving is in the range of 7-40% and embodied carbon emission saving is between 5-52% depending on the elements. The use of a genetic algorithm indicates the saving of costs and embodied carbon emissions in all the analysed elements and frames demonstrating it to be a robust, cost-effective and time-efficient solution to achieve optimization of structural designing in the early design phase.
The initial planning and designing stage of a project is very crucial for deciding the most efficient and effective design solution from various available options that directly impact sustainability. The optimal solution for reinforced concrete structures can include a lot of repetitive calculations for finding the most optimized and feasible solution, which is impractical manually and semi-automatically using structural analysis software. Therefore, the aim of the research is the automation of the design process which may well be the answer for solving repetitive problems efficiently and reliably by providing optimal solutions in terms of time, cost and embodied carbon emissions leading to an optimized design of a structure and contributing to sustainability in construction and real estate industry. One such method of automation is optimizing using a genetic algorithm in MATLAB which is a metaheuristic method and has proved to provide optimal and robust results in past research. To understand the results of the genetic algorithm, it is compared with the manual calculations for various elements such as beam, column, slabs and building frame. The building information modelling tools such as Revit and Tekla are used for visualizing the results. The automation of the design process by incorporating Eurocode principles and constraints indicate that the cost saving is in the range of 7-40% and embodied carbon emission saving is between 5-52% depending on the elements. The use of a genetic algorithm indicates the saving of costs and embodied carbon emissions in all the analysed elements and frames demonstrating it to be a robust, cost-effective and time-efficient solution to achieve optimization of structural designing in the early design phase.
Automation in Structural Engineering
Singh, Udham (author)
2021-01-01
Miscellaneous
Electronic Resource
English
DDC:
690
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