0
引言
我们的建筑结构AI设计助手 AI-structure Copilot 带着全新的优化体验来啦!在深耕底层核心算法的同时,我们始终关注工程师每一次点击的“顺畅感”。
本次更新深度聚焦各位工程师在使用过程中遇到的三个突出问题:
(1) 部分用户面临插件太多导致AI-structure安装冲突;
(2) 前处理识别结果心里没底;
(3) 建模分析排查错误像“开盲盒”。
新版本通过引入全新的底层挂载技术,以及直观的视觉辅助、精准的诊断功能,不仅显著降低了大家在建模板块的“盲目排错成本”,且每一步操作的直观性也有了大幅的跃升!
1
软件安装引入自动挂载功能
之前有工程师反馈,在安装软件时偶尔会遇到莫名其妙的报错打断。经排查,发现是部分电脑的 Windows 注册表权限在“捣乱”,通常由于多个插件修改注册表产生冲突。
为了让大家告别这个烦恼,本次更新我们全新引入了自动挂载技术!它取消了复杂的注册表验证,大幅降低对系统权限的依赖,让软件部署更安全,安装成功率提升!
【如果安装出现新的问题,也欢迎及时反馈】
2
增加识别结果校核后的衬图显示功能
在进行设计前处理时,很多工程师总有些不放心:识别生成的构件轴线到底准不准?
为了给大家吃颗“定心丸”,我们在完成识别结果校核后,贴心地加入了“自动显示原图作为衬图”的功能!生成的轴线会与原始灰底图完美叠合,位置对错一目了然。同时,为了保持图面清爽,衬图被专属安置在 GANIO_BUILDING_GRAY 图层,配合图层一键显隐功能,让图纸管理井井有条,校核工作更加高效。
![]()
(a)无衬图效果
![]()
(b)有衬图效果
图1 增加识别结果校核后的衬图显示
3
增加结构建模分析具体报错信息的提示
针对结构建模分析过程中可能出现的失败工况,新版本增加了对具体失败原因的提示机制。
软件将直接为用户输出详尽的错误原因及定位信息(如特定构件的参数缺失、楼层组装、建模失败、计算分析失败、结果提取失败等)。该功能将大幅降低用户在CAD使用中的设计结果排错成本,显著提升整体设计的顺畅度。
![]()
图2 提示结构建模分析失败的具体报错信息
4
典型案例
我们基于新版本软件也对典型案例进行了使用测试,典型测试对比如下图所示。典型案例是一个10层剪力墙结构(层高3米),6度(0.05g)抗震设防。
![]()
(a) 上一版本(v0.4.3)智能设计结果-标准层2
![]()
(a) 新版本(v0.4.4)智能设计结果-标准层2
图3 新/旧版本程序的典型案例设计结果对比
典型改进体现在:
(1)识别更合理:前处理的构件轴线与房间识别合理性提升,剪力墙与梁系布置更自然,不容易出现“怎么排布都别扭”的情况。
(2)低烈度工程不再过分保守:针对低烈度地区设计偏保守的问题,新版本会更有效地控制剪力墙过长的问题,并把长墙调整为更合适的连肢墙形式,让结构体系更符合工程师对“低烈度剪力墙方案”的整体直觉。
(3)楼板划分更规整:面向后续结构建模中楼板设计规整的需求,在智能设计过程中增加“虚梁”构件,让楼板构件划分更规则、后续更顺。
5
结语
AI-structure Copilot的每一次升级,都是课题组在“AI+结构设计”领域的又一次探索。我们坚信,AI辅助工程师高效高质量设计的目标会逐步转化为现实。欢迎大家对我们的最新版本软件功能进行试用,并多多提供意见和建议。
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)。
--End--
3分钟视频演示剪力墙结构智能设计完整操作流程
1分钟视频建筑户型平面生成与编辑流程
ai-structure.com联系方式
QQ群
AI-structure-交流1群:741840451(已满)
AI-structure-交流2群:1053974604(欢迎加入)
商务问题请联系:
黄盛楠(huangshengnan@mail.tsinghua.edu.cn)
技术问题请联系:
廖文杰(liaowj17@tsinghua.org.cn)
ai-structure.com往期文章
(20260211)
(20260209)
(20260123)
(20251226)
(20251211)
(20251210)
(20251120)
(20251030)
(20251027)
(20250926)
(20250913)
(20250912)
(20250911)
(20250828)
(20250723)
(20250703)
(20250609)
(20250606)
(20250513)
(20250414)
(20250314)
(20250221)
(20250218)
(20250212)
(20250117)
(20241228)
(20241227)
(2024/12/02)
(20241104)
(20241018)
(20240909)
(20240830)
(20240809)
(20240726)
(20240712)
(20240628)
(20240522)
(20240520)
(20240511)
(20240419)
(20240329)
(20240315)
(20240308)
(20240219)
(20240126)
(20231230)
(20231222)
(20231208)
(20231201)
(20231103)
(20231008)
(20230928)
(20230915)
(20230731)
(20230711)
(20230519)
(20230518)
(20230513)
(20230508)
(20230503)
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.
Qin SZ, Liao WJ, Tan Z, Hu KG, Gao Y, Lu XZ, Comparative analysis of intelligent retrofit design methods of RC frame structures using buckling-restrained braces.
Bulletin of Earthquake Engineering
, 2025, DOI: 10.1007/s10518-025-02164-3Liao WJ, Zhang ZL, Liu B, Lu XZ, Liu DF, Liu Q, Duan ZJ, Liu C, Intelligent zoning design of concrete-faced rockfill dams using image-parameter fusion enhanced generative adversarial networks,
Engineering Structures
, 2025, 339: 120662. DOI: 10.1016/j.engstruct.2025.120662Qin SZ, Fei YF, Liao WJ, Lu XZ*, Leveraging data-driven artificial intelligence in optimization design for building structures: A review,
Engineering Structures
, 2025, 341: 120810. DOI: 10.1016/j.engstruct.2025.120810Fei YF, Lu XZ, Liao WJ, Guan H, Data enhancement for generative AI design of shear wall structures incorporating structural optimization and diffusion models,
Advances in Structural Engineering
, 2025, DOI: 10.1177/13694332251353614Gu Y, Qin SZ, Liao WJ, Lu XZ*, Intelligent design of dimensions of reinforced concrete frame structure components using diffusion models,
Computers in Industry
, 2026, 175: 104428. DOI: 10.1016/j.compind.2025.104428
![]()
相关资料
学术报告视频
论文和专利
---End--
特别声明:以上内容(如有图片或视频亦包括在内)为自媒体平台“网易号”用户上传并发布,本平台仅提供信息存储服务。
Notice: The content above (including the pictures and videos if any) is uploaded and posted by a user of NetEase Hao, which is a social media platform and only provides information storage services.