基于BIM技术与模拟退火算法的村镇轻钢框架结构智能设计方法
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天津大学

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国家重点基础研究发展计划(973计划),国家建筑工程技术研究中心开放基金资助课题


Intelligent Design Method of Rural Light Steel Frame Structure Based on BIM Technology and Simulated Annealing Algorithm
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Tianjin University

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    摘要:

    传统的村镇住宅结构设计流程需要人工进行大量的试算与重复建模工作,而村镇住宅受制于建设成本,无法像城镇住宅一样通过设计师进行专业的结构设计与验算,其安全性与经济性均难以满足要求。为此,提出了一种村镇轻钢框架结构的智能设计方法,包括智能建模与智能优化两个环节。首先,基于图层自动识别算法、光学字符识别技术、自适应分块算法提出了村镇轻钢框架结构BIM智能建模方法,包括图层识别、轴文本数据提取、墙体轮廓提取等,智能建模结果基本满足实际工程要求。之后,基于所提出的两阶段模拟退火算法给出了村镇轻钢框架结构的智能优化方法,优化速度较快,优化效果良好。最后,通过实际工程案例对所提出的智能设计方法进行了验证,结果表明,所提出的村镇轻钢框架结构智能设计方法具有可行性,与传统的人工设计方法相比,设计周期可缩短70%以上,材料用量和结构设计指标相当。

    Abstract:

    In the traditional structural design process, rural buildings require a lot of manual calculations and repeated modeling. However, due to the construction cost, rural buildings cannot be designed and checked professionally by designers like urban buildings, and their safety and economy are difficult to meet the requirements. Therefore, an intelligent design approach to structural design of rural light steel frame structure was proposed, including the intelligent modeling and intelligent optimization. Based on the automatic layer automatic classification method (ALCM), optical character recognition technology (OCR) and adaptive block algorithm, BIM intelligent modeling method of rural light steel frame structure was proposed where layer recognition, the extraction of axis text data and wall contour were included, and generated structural models meted the requirements of practical application. Based on the proposed two-stage simulated annealing algorithm, the intelligent optimization method of rural light steel frame structure was given. The proposed intelligent design method was verified by practical engineering cases and the results showed that the proposed intelligent design method of rural light steel frame structure was feasible. Compared with the traditional manual design method, the design period could be shortened by more than 70%, and the material consumption and structural design parameters were similar.

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  • 收稿日期:2022-11-22
  • 最后修改日期:2023-01-06
  • 录用日期:2023-01-11
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