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新型装配式环氧树脂混凝土地下综合管廊结构优化分析

Optimization analysis of the structure of the new prefabricated epoxy resin concrete underground comprehensive pipe gallery
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摘要 本文设计了一种新型装配式地下综合管廊的结构形式,并将全新配比的环氧树脂混凝土材料作为结构材料应用于装配式地下综合管廊结构,可显著提高地下结构的抗渗性和耐腐蚀性;应用于实际中可有效降低地下综合管廊的维修率,全寿命周期成本大幅度降低。同时,本文借助有限元软件分析了不同跨度、不同板厚、不同预应力筋数量等参数对结构的变形及受力性能的影响。研究结果表明:综合管廊跨径、底板厚度、预应力筋数量是影响结构受力和变形的重要参数,在实际设计中应综合考虑以上影响因素,对综合管廊进行优化设计,以达到结构受力合理,材料用量最省的目的。 This article designs a new type of prefabricated underground comprehensive pipe gallery structure,and applies a new proportion of epoxy resin concrete material as the structural material to the prefabricated underground comprehensive pipe gallery structure,which can significantly improve the impermeability and corrosion resistance of the underground structure.When applied in practical processes,it can effectively reduce the maintenance rate of the underground comprehensive pipe gallery and significantly reduce the full life cycle cost.At the same time,this article uses finite element software to analyze different spans the influence of parameters such as different plate thicknesses and quantities of prestressed reinforcement on the deformation and stress performance of the structure is studied.The research results show that the span of the comprehensive pipe gallery,the thickness of the bottom plate,and the quantity of prestressed reinforcement are important parameters that affect the stress and deformation of the structure.In actual design,the above influencing factors should be comprehensively considered to optimize the design of the comprehensive pipe gallery,in order to achieve the goal of reasonable structural stress and the most economical material consumption.
作者 蔡婧娓 李江宁 朱毅 CAI Jing-wei;LI Jiang-ning;ZHU Yi(School of civil engineering,Jilin Jianzhu university,Changchun 130118,China)
出处 《吉林建筑大学学报》 CAS 2024年第3期22-28,共7页 Journal of Jilin Jianzhu University
基金 吉林省教育厅科学技术研究项目(JJKH20240375KJ)。
关键词 装配式 环氧树脂混凝土 地下综合管廊 影响因素 优化分析 prefabricated epoxy resin concrete underground comprehensive pipe gallery influencing factors optimization analysis
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