0
内容提要
发布了从AIstructure自动生成YJK/PKPM建模文件的功能,可实现从CAD的AIstructure中直接导出YJK/PKPM的建模文件,用YJK/PKPM软件便可打开结构分析计算模型。
产品下载网址:https://ai-structure.com/#/IntelligentDesign

【AIstructure-Copilot可自动导出YJK/PKPM模型】
1
AIstructure-Copilot直接输出结构模型
1.1 结构模型文件
很多工程师和我们联系,说虽然AIstructure可以很快完成结构设计,但是基于AIstructure的设计结果建立结构计算模型仍不够方便。此前,我们提供了一套Python的开源代码,可将AIstructure-Copilot输出的剪力墙-梁建模信息JSON文件转化为结构计算模型。
但是使用这个代码还需要安装Python程序并配置各种执行环境,对结构工程师不够友好。
因此,我们本次更新,实现了直接将JSON建模文件转化为不同版本软件均可打开的模型文件。YJK的模型文件为.ymd文件,双击.ymd文件可直接打开;PKPM为.jwd文件,则需要打开PKPM软件,新建一个空白模型文件,然后导入.jwd文件。
注:目前仅实现了1个标准层剪力墙和梁构件的自动建模,后续我们将会持续完善。
以下是9个典型案例,经过测试,目前AIstructure可以有效生成大部分常规剪力墙结构的模型文件。

YJK
PKPM

案例1

YJK
PKPM

案例2

YJK
PKPM

案例3

YJK
PKPM

案例4

YJK
PKPM

案例5

YJK
PKPM

案例6

YJK
PKPM

案例7

YJK
PKPM

案例8

YJK
PKPM

案例9
1.2 补充说明
目前得到的标准层剪力墙-梁模型还无法直接进行计算,还需要进行楼板生成、荷载施加、楼层组装等系列操作。
注意,YJK/PKPM模型,在楼板生成前,请先执行“形成网点”、“清理网点”的操作,可以更有效的生成楼板。

网格编辑界面(YJK和PKPM类似)
2
结语
我们增加了从AIstructure中直接输出YJK/PKPM模型的功能,实现了AIstructure设计后,直接可以得到在YJK和PKPM软件中打开的模型文件,并且可有效兼容多个软件版本。

后续,我们还将尽快在网页版中更新相关设计技术。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。
3
致谢
感谢YJK和PKPM团队专家对于输出模型文件的介绍和指导!
联系方式
QQ群,AI-structure-交流群:741840451
AIstructure-Copilot实现“三驾马车”驱动:Diffusion Model智能设计上线!(20231103)
AIstructure-Copilot-v0.1.2更新:精细化考虑抗震设计条件影响的全新GNN版本,请您来试试(20230928)
ai-structure.com:剪力墙结构材料用量AI预测模块上线测试(20230731)
AIstructure-Copilot:嵌入CAD平台的结构智能设计助手(20230711)
建筑结构生成式智能设计在日内瓦国际发明展上获“评审团特别嘉许金奖”(20230519)
ai-structure.com:土木工程自然语言规则AI解译模块上线测试(20230513)
AI剪力墙设计问卷调查结果(20230508)
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, 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, 2023, 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, 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

学术报告视频
公众号文章
---End--