2024, 16(3): 104-108. doi: 10.16670/j.cnki.cn11-5823/tu.2024.03.19
基于生成对抗网络的自动框架结构设计
1. | 西南交通大学 土木工程学院,成都 610031 |
2. | 中国建筑西南设计研究院有限公司,成都 610042 |
Intelligent Generation Method Of Concrete Frame Structures
1. | School of Civil engineering, Southwest Jiao tong University, Chengdu 610031, China |
2. | China Southwest Architecture, Chengdu 610042, China |
引用本文: 龙丹冰, 雷昕, 方长建, 康永君. 基于生成对抗网络的自动框架结构设计[J]. 土木建筑工程信息技术, 2024, 16(3): 104-108. doi: 10.16670/j.cnki.cn11-5823/tu.2024.03.19
Citation: Danbing Long, Xin Lei, Changjian Fang, Yongjun Kang. Intelligent Generation Method Of Concrete Frame Structures[J]. Journal of Information Technologyin Civil Engineering and Architecture, 2024, 16(3): 104-108. doi: 10.16670/j.cnki.cn11-5823/tu.2024.03.19
摘要:本文在结构设计中引入人工智能方法,通过提出建筑结构特征表达方法,构建以生成对抗网络为核心的框架结构自动设计方法。在数据前处理阶段,通过对建筑结构图纸分析,提出建筑特征表达方法与结构特征表达方法。在构建算法模型阶段,实现在有限的数据量下训练生成对抗算法学习框架结构布置,构建了依据建筑信息自动生成含有构件尺寸信息的框架结构自动布置模型,并提出了评价指标量化评价模型的结构设计能力。在案例中使用本文构建的框架结构自动布置模型完成一栋实际建筑的自动设计,验证了本文提出方法对结构设计效率的提高。
Abstract: This paper introduces artificial intelligence methods in structural design, and further proposes a method for expressing building structural features, and constructs an automatic design method for frame structures centered on generating adversarial networks. In the data preprocessing stage, this paper proposes building feature expression methods and structural feature expression methods by analyzing building structural drawings. During constructing algorithm models, the adversarial algorithm is trained and generated under limited data to learn framework structure layout. A framework structure automatic layout model containing component size information is constructed based on building information, and evaluation indicators are proposed to quantify the structural design ability of the model. In the case study in this paper, the framework structure automatic layout model constructed is used to complete the automatic design of an actual building, which verifies the improvement of the proposed method in structural design efficiency.
[1] |
刘晓群, 邹欣, 范虹. 基于并行云计算模式的建筑结构设计[J]. 电子技术应用, 2011, 37(10): 123-125.doi: 10.3969/j.issn.0258-7998.2011.10.043 |
[2] |
龙甘, 戚向明, 胡达敏, 等. 复杂超高层建筑结构数字化设计方法探索[J]. 建筑结构, 2022, 52(19): 74-80. |
[3] |
钟万勰, 裘春航, 秦晓霖, 等. 混凝土框架结构智能化CAD中的设计规范处理[J]. 计算结构力学及其应用, 1991(04): 439-444. |
[4] | |
[5] |
马臣杰, 张良平, 范重. 优化技术在深圳京基金融中心中的应用[J]. 建筑结构, 2009(S1): 195-197. |
[6] | |
[7] |
住房和城乡建设部等. 住房和城乡建设部等部门关于推动智能建造与建筑工业化协同发展的指导意见[EB/OL]. (2020-07-20)[2023-04-20]. |
[8] |
住房和城乡建设部. "十四五"建筑业发展规划[S]. 2022. |
[9] |
中华人民共和国国务院. 中华人民共和国国民经济和社会发展第十四个五年规划 |
[10] |
"十四五"规划和2035年远景目标纲要[S]. 2021. |
[11] |
Kim Y M. Development of automated structural design tool for horizontal members of Hanok[J]. Journal of the Architectural Institute of Korea Structure & Construction, 2017, 33(4): 21-28. |
[12] |
Jeong J H, Jo H. Deep reinforcement learning for automated design of reinforced concrete structures[J]. Computer‐Aided Civil and Infrastructure Engineering, 2021 |
[13] | |
[14] |
Liao W, Lu X, Huang Y, et al. Automated structural design of shear wall residential buildings using generative adversarial networks[J]. Automation in Construction, 2021, 132: 103931doi: 10.1016/j.autcon.2021.103931 |
[15] |
程国忠, 周绪红, 刘界鹏, 等. 基于深度强化学习的高层剪力墙结构智能设计方法[J]. 建筑结构学报, 2022, 43(9): 84-91. |
计量
- PDF下载量(9)
- 文章访问量(592)
- HTML全文浏览量(364)