0
引言
随着研究的进展,AI设计的算法库越来越丰富,我们将多种算法相互融合,取长补短,在AIstructure-Copilot-V0.3.4版本实现了新的融合算法。同时,为了及时把最新最好的算法提供给用户,我们提供了新算法尝新功能。此外,我们也将前处理部分做了更加精细化的处理,可以使用户操作起来更加顺畅,欢迎大家试用。
1
新算法尝新功能
每次软件升级到新的版本,都可能会引入新的缺陷。特别是对于AI这类发展很快的领域,如何在“算法快速迭代升级”和“性能稳定”取得平衡往往是比较困难的。为了解决这一难题,我们决定同时将稳定版和研发中的测试版的设计结果都提供给用户。这样喜欢稳定的用户还是可以继续使用稳定版的设计结果,喜欢尝新的用户可以看看测试版的设计结果。也欢迎大家及时将发现的测试版的问题反馈给我们。这样我们可以及时调整AI算法。待测试版的算法稳定后,我们将移植测试版的结果到新的稳定版里面。
图1 新增测试版设计结果,第一组为测试版设计结果,第二到四组为稳定版设计结果
2
算法深度融合,AI设计能力更强大
2023年11月以来,AIstructure-Copilot采用生成对抗网络、图神经网络、扩散模型等不同的AI算法进行结构智能设计,可以给出不同的设计方案供用户选择。随着研究的深入,我们算法库里面的算法越来越多,我们综合考虑设计的效果和结果的多样性,将不同算法融合成3套算法,分别生成相应的设计结果供用户选用。
3
前处理功能持续提升
3.1 部分墙体、轴线提取能力提升
针对一些复杂图纸,之前的版本对部分轴线和墙体的识别能力不足,需要用户后期手动进行修改调整,AIstructure-Copilot-V0.3.4版本对此进行了升级优化,如图2和图3所示,新的版本识别能力显著增强。
(a)升级优化前
(b)升级优化后
图2 复杂图纸部分墙体的提取
(a)升级优化前
(b)升级优化后
图3 复杂图纸部分窗轴线的提取
3.2 管道井附近墙体提取能力提升
在部分隔墙与建筑墙出现偏移时,旧版本在管道井部分会出现构件轴线提取异常的情况,AIstructure-Copilot-V0.3.4版本对此进行了优化处理,如图4所示。
(a)升级优化前
(b)升级优化后
图4 管道井部分的构件处理
4
结语
AIstructure-Copilot发展至今,算法不断进化,操作也更加便捷,带给用户更好的使用体验,可以更好的辅助工程师开展工作,欢迎大家试用。
这里有彩蛋哦!随着住建部好房子标准的公布,我们的工程师也在加紧对AI进行新标准设计的训练,敬请期待!
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(https://ai-structure.com)。
相关论文
Liao WJ, Lu XZ, Huang YL, Zheng Z, Lin YQ, Automated structural design of shear wall residential buildings using generative adversarial networks, Automation in Construction, 2021, 132: 103931. DOI: 10.1016/j.autcon.2021.103931.
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.
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.
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.
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.
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.
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.
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.
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
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, 52(11): 3281-3303. DOI:10.1002/eqe.3862.
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.
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, 2024, 39(4): 518-538. DOI: 10.1111/mice.13094.
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.
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, 79: 107873. DOI:10.1016/j.jobe.2023.107873
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
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
Qin SZ, Liao WJ, Huang SN, Hu KG, Tan Z, Gao Y, Lu XZ, AIstructure-Copilot: assistant for generative AI-driven intelligent design of building structures, Smart Construction, 2024, DOI: 10.55092/sc20240001
Gu Y, Huang YL, Liao WJ, Lu XZ, Intelligent design of shear wall layout based on diffusion models, Computer-Aided Civil and Infrastructure Engineering, 2024, 39(23):3610-3625. DOI: 10.1111/mice.13236
Fei YF, Liao WJ, Zhao PJ, Lu X*, Guan H, Hybrid surrogate model combining physics and data for seismic drift estimation of shear-wall structures, Earthquake Engineering & Structural Dynamics, 2024, 53(10): 3093-3112. DOI: 10.1002/eqe.4151
Han J, Lu XZ, Gu Y, Cai Q, Xue HJ, Liao WJ, Optimized data representation and understanding method for the intelligent design of shear wall structures, Engineering Structures, 2024, 315: 118500. DOI: 10.1016/j.engstruct.2024.118500
Qin SZ, Guan H, Liao WJ, Gu Y, Zheng Z, Xue HJ, Lu XZ, Intelligent design and optimization system for shear wall structures based on large language models and generative artificial intelligence, Journal of Building Engineering, 2024, 95: 109996. DOI: 10.1016/j.jobe.2024.109996
Wang ZH, Yue Y, Chen Y, Liao WJ, Li CS, Hu KG, Tan Z, Lu XZ. Expert experience-embedded evaluation and decision-making method for intelligent design of shear wall structures. Journal of Computing in Civil Engineering-ASCE, 2025, 39(1). DOI: 10.1061/JCCEE5.CPENG-6076
Tan Z, Qin SZ, Hu KG, Liao WJ, Gao Y, Lu XZ, Intelligent generation and optimization method for the retrofit design of RC frame structures using buckling-restrained braces, Earthquake Engineering & Structural Dynamics, 2025, 54(2): 530-547. DOI: 10.1002/eqe.4268
Yu Y, Chen Y, Liao WJ, Wang ZH, Zhang SL, Kang YJ, Lu XZ, Intelligent generation and interpretability analysis of shear wall structure design by learning from multidimensional to high-dimensional features, Engineering Structures, 2025, 325: 119472. DOI: 10.1016/j.engstruct.2024.119472
Qin SZ, Liao WJ, Huang YL, Zhang Shulu, Gu Y, Han J, Lu XZ, Intelligent design for component size generation in reinforced concrete frame structures using heterogeneous graph neural networks, Automation in Construction, 2025, 171: 105967.
Xia JK, Liao WJ, Han B, Zhang SL, Lu XZ, Intelligent co-design of shear wall and beam layouts using a graph neural network, Automation in Construction, 2025, 172: 106024.