0
功能简介
更新了梁构件布置设计功能,更深度的嵌入专家知识,降低了生成不合理次梁的概率,保证主梁设计合理性,以及更加规整的楼板划分。
AIstructure自动生成的梁布置设计(未经过人工调整)
1
功能更新
用户反馈中提到:AI设计的剪力墙结构梁布置,在部分区域次梁布置过多、过于复杂,不利于工程师后期进行微调和修改,建议对此进行调整。
因此,我们改进了算法,尽量保证楼板的规则性,并控制不必要的次梁生成。
(1)典型的改进后设计案例对比如下所示
Test 1案例(本版本设计结果)
Test 1案例(此前版本设计结果)
Test 2案例(本版本设计结果)
Test 2案例(此前版本设计结果)
Test 3案例(本版本设计结果)
Test 3案例(此前版本设计结果)
Test 4案例(本版本设计结果)
Test 4案例(此前版本设计结果)
Test 5案例(本版本设计结果)
Test 5案例(此前版本设计结果)
(2)部分不合理处,仍旧需要工程师手动调整
紫色圈中为待调整内容
2
智能设计云平台使用提示
目前,为了保证网站的安全性,AIstructure平台采用的是https协议,正确网址为:https://ai-structure.com。
虽然http协议对应的网站同样能提供相应服务,但是浏览器会提示不安全,如下图所示,同时部分功能使用可能会遇到浏览器阻止的问题,如有问题,请大家先切换至https协议网站。
3
结语
我们更新了梁布置生成功能,使得AIstructure生成的梁布置与工程师设计更加相似。
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。
联系方式
QQ群,AI-structure-交流群:741840451
黄盛楠:huangshengnan@mail.tsinghua.edu.cn
廖文杰:liaowj17@tsinghua.org.cn
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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.
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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
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
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