Integrated Schematic Design Method for Shear Wall Structures: A Practical Application of Generative Adversarial Networks
The intelligent design method based on generative adversarial networks (GANs) represents an emerging structural design paradigm where design rules are not artificially defined but are directly learned from existing design data. GAN-based methods have exhibited promising potential compared to convent...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/12/9/1295 |
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| author | Yifan Fei Wenjie Liao Shen Zhang Pengfei Yin Bo Han Pengju Zhao Xingyu Chen Xinzheng Lu |
| author_facet | Yifan Fei Wenjie Liao Shen Zhang Pengfei Yin Bo Han Pengju Zhao Xingyu Chen Xinzheng Lu |
| author_sort | Yifan Fei |
| collection | DOAJ |
| description | The intelligent design method based on generative adversarial networks (GANs) represents an emerging structural design paradigm where design rules are not artificially defined but are directly learned from existing design data. GAN-based methods have exhibited promising potential compared to conventional methods in the schematic design phase of reinforced concrete (RC) shear wall structures. However, for the following reasons, it is challenging to apply GAN-based approaches in the industry and to integrate them into the structural design process. (1) The data form of GAN-based methods is heterogeneous from that of the widely used computer-aided design (CAD) methods, and (2) GAN-based methods have high requirements on the hardware and software environment of the user’s computer. As a result, this study proposes an integrated schematic design method for RC shear wall structures, providing a workable GAN application strategy. Specifically, (1) a preprocessing method of architectural CAD drawings is proposed to connect the GAN with the upstream architectural design; (2) a user-friendly cloud design platform is built to reduce the requirements of the user’s local computer environment; and (3) a heterogeneous data transformation method and a parametric modeling procedure are proposed to automatically establish a structural analysis model based on GAN’s design, facilitating downstream detailed design tasks. The proposed method makes it possible for the entire schematic design phase of RC shear wall structures to be intelligent and automated. A case study reveals that the proposed method has a heterogeneous data transformation accuracy of 97.3% and is capable of generating shear wall layout designs similar to the designs of a competent engineer, with 225 times higher efficiency. |
| first_indexed | 2024-03-10T00:32:21Z |
| format | Article |
| id | doaj.art-47a92ba51a4949e0b948abd932cf95d6 |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-10T00:32:21Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-47a92ba51a4949e0b948abd932cf95d62023-11-23T15:22:07ZengMDPI AGBuildings2075-53092022-08-01129129510.3390/buildings12091295Integrated Schematic Design Method for Shear Wall Structures: A Practical Application of Generative Adversarial NetworksYifan Fei0Wenjie Liao1Shen Zhang2Pengfei Yin3Bo Han4Pengju Zhao5Xingyu Chen6Xinzheng Lu7Beijing Engineering Research Center of Steel and Concrete Composite Structures, Tsinghua University, Beijing 100084, ChinaKey Laboratory of Civil Engineering Safety and Durability of Ministry of Education, Tsinghua University, Beijing 100084, ChinaCentral-South Architectural Design Institute Co., Ltd., Wuhan 430071, ChinaCentral-South Architectural Design Institute Co., Ltd., Wuhan 430071, ChinaBeijing Institute of Architectural Design Co., Ltd., Beijing 100045, ChinaBeijing Engineering Research Center of Steel and Concrete Composite Structures, Tsinghua University, Beijing 100084, ChinaBeijing Engineering Research Center of Steel and Concrete Composite Structures, Tsinghua University, Beijing 100084, ChinaKey Laboratory of Civil Engineering Safety and Durability of Ministry of Education, Tsinghua University, Beijing 100084, ChinaThe intelligent design method based on generative adversarial networks (GANs) represents an emerging structural design paradigm where design rules are not artificially defined but are directly learned from existing design data. GAN-based methods have exhibited promising potential compared to conventional methods in the schematic design phase of reinforced concrete (RC) shear wall structures. However, for the following reasons, it is challenging to apply GAN-based approaches in the industry and to integrate them into the structural design process. (1) The data form of GAN-based methods is heterogeneous from that of the widely used computer-aided design (CAD) methods, and (2) GAN-based methods have high requirements on the hardware and software environment of the user’s computer. As a result, this study proposes an integrated schematic design method for RC shear wall structures, providing a workable GAN application strategy. Specifically, (1) a preprocessing method of architectural CAD drawings is proposed to connect the GAN with the upstream architectural design; (2) a user-friendly cloud design platform is built to reduce the requirements of the user’s local computer environment; and (3) a heterogeneous data transformation method and a parametric modeling procedure are proposed to automatically establish a structural analysis model based on GAN’s design, facilitating downstream detailed design tasks. The proposed method makes it possible for the entire schematic design phase of RC shear wall structures to be intelligent and automated. A case study reveals that the proposed method has a heterogeneous data transformation accuracy of 97.3% and is capable of generating shear wall layout designs similar to the designs of a competent engineer, with 225 times higher efficiency.https://www.mdpi.com/2075-5309/12/9/1295intelligent structural designgenerative adversarial networksparametric modelingreinforced concrete shear wall structuresschematic design |
| spellingShingle | Yifan Fei Wenjie Liao Shen Zhang Pengfei Yin Bo Han Pengju Zhao Xingyu Chen Xinzheng Lu Integrated Schematic Design Method for Shear Wall Structures: A Practical Application of Generative Adversarial Networks Buildings intelligent structural design generative adversarial networks parametric modeling reinforced concrete shear wall structures schematic design |
| title | Integrated Schematic Design Method for Shear Wall Structures: A Practical Application of Generative Adversarial Networks |
| title_full | Integrated Schematic Design Method for Shear Wall Structures: A Practical Application of Generative Adversarial Networks |
| title_fullStr | Integrated Schematic Design Method for Shear Wall Structures: A Practical Application of Generative Adversarial Networks |
| title_full_unstemmed | Integrated Schematic Design Method for Shear Wall Structures: A Practical Application of Generative Adversarial Networks |
| title_short | Integrated Schematic Design Method for Shear Wall Structures: A Practical Application of Generative Adversarial Networks |
| title_sort | integrated schematic design method for shear wall structures a practical application of generative adversarial networks |
| topic | intelligent structural design generative adversarial networks parametric modeling reinforced concrete shear wall structures schematic design |
| url | https://www.mdpi.com/2075-5309/12/9/1295 |
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