0
引言
AI-structure Copilot 又迎来新一轮功能升级。
在持续打磨底层智能设计算法的同时,我们也始终关注工程师在实际使用过程中的真实体验。无论是剪力墙设计中底部加强区的设置是否合理,还是设计条件输入是否足够完整;无论是楼板划分是否更符合主流分析软件的建模习惯,还是构件和荷载修改是否足够高效便捷,这些看似细节的问题,都会直接影响工程师的使用效率和设计体验。
针对这些实际需求,AI-structure Copilot v0.4.5 对结构设计参数设置与工具面板功能进行了进一步完善。新版本新增底部加强区设置,优化设计条件输入逻辑,并引入基于虚梁规则的楼板划分机制,使生成模型更加规范、更加贴近工程实际;与此同时,工具面板也同步升级,支持更高效的批量编辑与荷载修改操作,并新增软件安装/更新进度展示功能,让整体使用过程更加直观、顺畅、安心。
1
更完善的结构设计功能
(1)增加底部加强区的设置
在剪力墙结构设计中,底部加强部位的确定十分关键。根据规范要求,底部加强部位的高度可取底部两层和墙体总高度 1/10 二者的较大值。为此,AI-structure Copilot 在楼层组装界面中新增了底部加强区设置功能。
用户点击“刷新”按钮后,系统即可自动识别楼层信息,计算符合规范要求的底部加强区层数及建议墙厚。同时,系统也保留了足够的灵活性,支持用户对加强区层数和墙厚进行手动调整。该功能实现了规范要求与模型参数的有效联动,有助于进一步提升模型设置的合理性与规范性。
图1 增加底部加强区的设置
(2)更完善的设计条件输入
为了进一步提升设计输入的完整性与准确性,新版本在参数设置页面中增加了结构抗震等级自动判断功能,为后续智能设计提供更可靠的依据。
在“基本信息”栏中,新增了“抗震设防类别”选项。用户依次完成设计条件输入后,进入“楼层信息”栏进行楼层组装,系统将根据各标准层层高的累加结果自动计算结构总高度;随后进入“信息校核”栏时,系统可结合设防烈度、场地类别等信息,自动判断当前结构的抗震等级,并进一步区分抗震措施与构造措施。
这一更新使设计条件输入更加系统、清晰,也为后续结构智能设计提供了更准确的参数基础。
图2 更完善的设计条件输入
(3)更合理的基于虚梁规则的楼板划分算法
该功能充分参考了 PKPM 建模中利用“剪力虚梁”拆分楼板的工程习惯,在自动生成墙体与梁系的同时,智能布置虚梁,对复杂楼板进行合理分割。该机制能够有效减少畸形楼板的产生,使后续进入结构分析引擎时,楼板单元更加规则,网格划分更加顺畅,从而提升整体建模质量与分析适配性。
图3 引入虚梁使楼板更加规则
2
工具面板功能更新
图4 全新工具面板
(1)增加构件尺寸批量编辑功能
在实际工程设计中,外围构件往往由于受力需求或建筑造型要求,其截面尺寸通常大于内部构件。此前,如需对这类特定构件进行尺寸调整,往往需要逐个选中并逐一修改,效率相对较低。
针对这一问题,新版本在工具面板中新增了“构件尺寸批量编辑”功能。用户选择待修改的结构平面图后,点击如“X向外墙厚度”等按钮,对应构件便会在图中高亮闪烁显示。该功能支持用户依据特定规则一次性调整多个构件的尺寸,大幅提升了结构修改效率,也使设计调整过程更加便捷直观。
(a)“构件尺寸批量编辑”功能面板
(b)“构件尺寸批量编辑”绘图区显示
图5 增加构件尺寸批量编辑功能
(2)用户修改梁上线荷载、楼板均布荷载功能更新
此前有工程师反馈,智能设计完成后,结构荷载与构件属性的编辑修改还不够方便。针对这一使用需求,本次版本对相关功能进行了进一步完善。
图6 完善了结构构件新建和编辑功能
以下面案例中的楼梯的荷载输入为例:结构建模分析中,通常将楼梯间的楼板厚度设置为0,再布置楼梯荷载。对此,我们在AI-structure中对楼梯间楼板设置参数,输入板厚h=0,恒荷载 DeadLoad=8kN/m2,LiveLoad=3.5kN/m2。 按照上述条件完成输入后,系统会自动对修改后的板构件进行重新渲染,如图7(a)所示;提交智能设计计算后,在导出的 PKPM 模型中,可以看到修改后的板厚与荷载均已正确写入,如图7(b)所示。
梁上线荷载的修改操作与楼板均布荷载的修改流程类似,用户可参照相同方式完成调整。
(a) 在Copilot中修改楼板均布荷载
(a) 修改后的板均布荷载在PKPM中输出
图7 板构件修改案例
(板厚h=0,恒荷载DeadLoad=8kN/m2, LiveLoad=3.5kN/m2)
3
软件安装/更新增加进度条
此前有工程师反馈,在软件更新过程中,由于缺乏清晰的进度反馈,往往容易误以为程序“卡住”了。在无法判断还需等待多久的情况下,部分用户甚至会选择强行关闭程序,从而影响更新过程的顺利完成。
为进一步优化使用体验,新版本正式加入了实时进度条功能。更新过程中,用户可以清晰看到当前进度与传输状态,更直观地掌握软件安装和更新情况。该功能有效缓解了等待过程中的不确定感,让更新过程更加透明、稳定、可控。
图8 增加进度条展示更新进度
4
结语
AI-structure Copilot 的每一次升级,都是课题组在“AI+结构设计”方向上的一次持续探索。
从结构设计参数的完善,到工具面板交互体验的优化,我们始终希望把工程师在实际工作中的真实需求,转化为更高效、更顺畅、更可靠的设计支持能力。
欢迎大家继续试用 AI-structure Copilot 实验室版功能,也欢迎提出宝贵意见和建议。课题组将持续打磨相关算法与产品体验,为工程设计提供更加智能、更加实用的辅助工具。
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
(20260312)
(20260305)
(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/s10518-025-02164-3
Liao 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.2025.120662
Qin 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.2025.120810
Fei 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: 10.1177/13694332251353614
Gu 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--
热门跟贴