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Intelligent Design Concept of Rural Light Steel Frame Structure Based on BIM Technology and Genetic Algorithm

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Abstract

The traditional structural design process of rural buildings requires a lot of trial calculations and iterations of modelling work. However, rural buildings are subject to construction costs and cannot be professionally designed and checked by designers like urban buildings. Their safety and economy are difficult to meet the requirements. Therefore, an intelligent design concept of rural light steel frame structure was proposed, including intelligent modeling and intelligent optimization. Based on the automatic layer recognition method and optical character recognition technology, the BIM intelligent modeling method of rural light steel frame structure corresponding to the standard atlas of rural buildings was proposed, including layer recognition, axis text data extraction, primary selection and automatic arrangement of components. The intelligent modeling results basically met the requirements of practical application. Based on the proposed two-stage genetic algorithm, an intelligent optimization method of rural light steel frame structure was given. The optimization speed was fast and the optimization effect was good. The proposed intelligent design method was verified by practical case. The results showed that the proposed intelligent design concept of rural light steel frame structure was feasible. Compared with the traditional manual design method, the design period could be shortened by more than 80%, and the structural design indexes were comparable.

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Acknowledgements

This research was supported by the Opening Funds of State Key Laboratory of Building Safety and Built Environment & National Engineering Research Center of Building Technology (No. BSBE2022-13).

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Correspondence to Ting Zhou.

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Sun, K., Zhou, T., Chen, Z. et al. Intelligent Design Concept of Rural Light Steel Frame Structure Based on BIM Technology and Genetic Algorithm. Int J Steel Struct 23, 1343–1356 (2023). https://doi.org/10.1007/s13296-023-00772-w

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  • DOI: https://doi.org/10.1007/s13296-023-00772-w

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