AIstructure更新：剪力墙结构GNN梁智能设计功能试用 + 智能设计云平台更新

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内容提要

AIstructure-Copilot更新：增加了剪力墙结构GNN梁智能设计的试用版。

ai-structure.com更新：智能设计平台功能同步了GAN、GNN、Diffusion model同时开展设计的功能；此外，“规则自动解译”功能也在主页的“开发测试产品”中重新上线。

欢迎大家试用！

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AIstructure-Copilot更新

1.1 剪力墙结构GNN梁智能设计推出试用版

在使用AIstructure完成剪力墙结构布置设计之后，可进一步开展梁布置设计工作。AIstructure-Copilot此前开发了基于人工定义规则（Rule）进行梁设计的功能（详见：ai-structure.com剪力墙结构梁自动设计功能更新)。

本次更新提供了基于图神经网络（GNN）梁布置设计的试用功能。该方法基于剪力墙布置设计和建筑墙、门窗构件信息，利用训练完成的GNN模型进行梁构件布置的生成。

近期发表的新论文，对该方法进行了详细的原理介绍，传送门：新论文：剪力墙结构的GNN梁布置智能设计。

1.2 典型案例

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ai-structure.com更新

2.1 ai-structure.com的智能设计平台更新

目前，智能设计平台的信息和设计功能已经基本和AIstructure-Copilot同步，目前可有效实现两个功能。

（1）基于上传的建筑构件图、建筑空间图、JSON数据文件，创建新的设计项目，点击设计按钮，实现一次性完成剪力墙-梁的结构设计，并完成其对应的材料用量预测。

（2）云平台同步Copilot的设计结果

如下图所示，如果在Copilot中只进行了一个方案的梁设计，那么最后云平台同步得到的就只有一个梁设计结果，其他方案未设计则不显示。

2.2 “规则自动解译”功能重新上线

将“规则自动解译”模块放置于“开发测试中产品”模块，未来我们也会将部分测试功能放置于该模块。点击进入规则解译界面，便可开始测试规则自动解译。

详见：ai-structure.com：土木工程自然语言规则AI解译模块上线测试

下图则是典型案例规则的解译结果。

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结语

我们将最新发表的基于GNN梁布置设计方法集成到了AIstructure-Copilot中进行测试，未来我们将根据测试结果进一步改进该算法。

同时ai-structure.com也进行了对应的更新，进一步完善智能设计云平台与Copilot的同步程度，同时再次上线了规则自动解译模块，为工程师提供更好的服务。

后续，我们还将不断完善相关产品功能。欢迎大家持续关注我们的工作，多多支持！

温馨提示：为更好使用AI设计工具，请仔细阅读使用说明书。

ai-structure.com联系方式

QQ群，AI-structure-交流群：741840451

廖文杰：[email protected]

相关论文

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2. Lu XZ, Liao WJ, Zhang Y, Huang YL, Intelligent structural design of shear wall residence using physics-enhanced generative adversarial networks, Earthquake Engineering & Structural Dynamics, 2022, 51(7): 1657-1676. DOI: 10.1002/eqe.3632.
   

3. Zhao PJ, Liao WJ, Xue HJ, Lu XZ, Intelligent design method for beam and slab of shear wall structure based on deep learning, Journal of Building Engineering, 2022, 57: 104838. DOI: 10.1016/j.jobe.2022.104838.

4. Liao WJ, Huang YL, Zheng Z, Lu XZ, Intelligent generative structural design method for shear-wall building based on “fused-text-image-to-image” generative adversarial networks, Expert Systems with Applications, 2022, 118530, DOI: 10.1016/j.eswa.2022.118530.

5. Fei YF, Liao WJ, Zhang S, Yin PF, Han B, Zhao PJ, Chen XY, Lu XZ, Integrated schematic design method for shear wall structures: a practical application of generative adversarial networks, Buildings, 2022, 12(9): 1295. DOI: 10.3390/buildings1209129.

6. Fei YF, Liao WJ, Huang YL, Lu XZ, Knowledge-enhanced generative adversarial networks for schematic design of framed tube structures, Automation in Construction, 2022, 144: 104619. DOI: 10.1016/j.autcon.2022.104619.

7. Zhao PJ, Liao WJ, Huang YL, Lu XZ, Intelligent design of shear wall layout based on attention-enhanced generative adversarial network, Engineering Structures, 2023, 274, 115170. DOI: 10.1016/j.engstruct.2022.115170.

8. Zhao PJ, Liao WJ, Huang YL, Lu XZ, Intelligent beam layout design for frame structure based on graph neural networks, Journal of Building Engineering, 2023, 63, Part A: 105499. DOI: 10.1016/j.jobe.2022.105499.

9.  Zhao PJ, Liao WJ, Huang YL, Lu XZ, Intelligent design of shear wall layout based on graph neural networks, Advanced Engineering Informatics, 2023, 55, 101886, DOI: 10.1016/j.aei.2023.101886

10. Liao WJ, Wang XY, Fei YF, Huang YL, Xie LL, Lu XZ*, Base-isolation design of shear wall structures using physics-rule-co-guided self-supervised generative adversarial networks, Earthquake Engineering & Structural Dynamics, 2023, DOI:10.1002/eqe.3862.

11. Feng YT, Fei YF, Lin YQ, Liao WJ, Lu XZ, Intelligent generative design for shear wall cross-sectional size using rule-Embedded generative adversarial network, Journal of Structural Engineering-ASCE, 2023, 149(11). 04023161. DOI:10.1061/JSENDH.STENG-12206.

12. Fei YF, Liao WJ, Lu XZ*, Guan H*, Knowledge-enhanced graph neural networks for construction material quantity estimation of reinforced concrete buildings, Computer-Aided Civil and Infrastructure Engineering, 2023, DOI: 10.1111/mice.13094.

13. Zhao PJ, Fei YF, Huang YL, Feng YT, Liao WJ, Lu XZ*, Design-condition-informed shear wall layout design based on graph neural networks, Advanced Engineering Informatics, 2023, 58: 102190. DOI: 10.1016/j.aei.2023.102190.

14. Fei YF, Liao WJ, Lu XZ*, Taciroglu E, Guan H, Semi-supervised learning method incorporating structural optimization for shear-wall structure design using small and long-tailed datasets, Journal of Building Engineering, 2023, DOI：10.1016/j.jobe.2023.107873

15. Liao WJ, Lu XZ*, Fei YF, Gu Y, Huang YL, Generative AI design for building structures, Automation in Construction, 2024, 157: 105187. DOI: 10.1016/j.autcon.2023.105187

16. Zhao PJ, Liao WJ, Huang YL, Lu XZ*, Beam layout design of shear wall structures based on graph neural networks, Automation in Construction, 2024, 158: 105223. DOI: 10.1016/j.autcon.2023.105223