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数字化盾构隧道管片结构配筋与出图方法研究 被引量:1

Research on Digital Drawing Method of Reinforcement Bars for Shield Lining Structure
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摘要 研究目的:为提升盾构隧道管片的数字化设计水平及设计效率,本文提出一种基于内力计算结果及三维管片模型的数字化结构配筋与出图方法。利用随机森林算法生成配筋方案,基于配筋方案和三维管片模型建立钢筋参数化建模与排布算法,通过几何模型变换和剖切操作自动生成结构配筋图。研究结论:(1)基于随机森林算法的智能化配筋算法能模仿人工选筋和方案评价,并自动生成配筋方案;(2)利用参数化建模能自动实现配筋方案的三维模型与出图;(3)本文方法在武汉某隧道工程设计案例中得到验证,可应用于盾构隧道结构设计,其能满足施工图设计的前期成果要求,并减少设计人员的工作量。 Research purposes:In order to improve the digital design level and design efficiency of shield lining,a digital drawing method for reinforcement bars was proposed based on the mechanics calculation results and 3D shield segment model.The design of reinforcement bars was generated by using Random Forest algorithms.A set of parametric modeling and arrangement algorithms for reinforcement bars was created based on the design results and the 3D shield segment model.The drawing of reinforcement bars was automatically generated through interactive transformation and sectioning operations of the geometric models.These methods were tested and verified in an actual tunneling construction project in Wuhan.Research conclusions:(1)Using Random Forest algorithms can imitate manual selection and evaluation of reinforcement bars and automatically generate the design results;(2)The design results,including 3D model and drawing,can be automatically generated through parametric modeling method;(3)The drawing results from the parametric method can meet the accuracy requirements of preliminary design,and reduce the workload of designers.
作者 骆汉宾 李霖皓 陈珂 陈健 胡云华 龙凡 LUO Hanbin;LI Linhao;CHEN Ke;CHEN Jian;HU Yunhua;LONG Fan(Huazhong University of Science and Technology,Wuhan,Hubei 430074,China;Institute of Rock and Soil Mechanics,Chinese Academy of Sciences,Wuhan,Hubei 430071,China;Wuhan Municipal Engineering Design&Research Institute Co.Ltd,Wuhan,Hubei 430071,China)
出处 《铁道工程学报》 EI CSCD 北大核心 2023年第9期84-91,共8页 Journal of Railway Engineering Society
基金 国家自然科学基金(U21A20151,72101093) 湖北省重大科技创新项目(2020ACA006)。
关键词 盾构管片 人工智能 结构配筋 参数化设计 shield tunnel lining artificial intelligence reinforcement bars parametric design
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