摘要
研究目的:隧道工程设计方案受其地形条件、地质构造、水文特征、气象条件、围岩类别等多因素影响,具有典型的开放性、复杂性、自组织、自相似、非平衡性等复杂系统特点和演化规律。根据以上特点,本文主要运用FMEA、RCM、BP神经网络、BIM等技术,对隧道工程设计方案进行智能比选与动态优化,为隧道工程设计方案优化提供重要参考。研究结论:(1)方案设计前,搜集大量已完类似工程项目的设计方案资料,构建了隧道工程设计方案历史数据库;(2)结合拟建工程特征,运用PSO聚类分析方法,从设计方案历史数据库中筛选出相似度较高的备选方案;(3)综合考虑工程各参与方需求,运用FMEA、RCM技术对各备选方案设计指标进行系统分析与优化,并运用BPNN模型预测各备选设计方案的全寿命周期造价,以全寿命周期造价最低为原则,优选设计方案;(4)运用BIM、ILS技术对优选设计方案进行深度优化;(5)本研究成果可为高速公路隧道、桥梁等工程设计方案优化提供参考。
Research purposes:The tunnel engineering design scheme is influenced by many factors,such as topographic conditions,which has the characteristics and evolution laws of typical complex system,such as openness,complexity,self-organization,self-similarity and non-balance.According to the above characteristics,this paper mainly uses FMEA,RCM,BPNN,BIM and other technologies to conduct intelligent comparison and dynamic optimization of tunnel engineering design scheme,which provides an important reference for tunnel engineering design scheme optimization.Research conclusions:(1)Before the scheme design,a large number of design scheme data of similar projects are collected,and builted the historical database of tunnel engineering design scheme.(2)Combined with the characteristics of the proposed project,the alternatives with high similarity from the historical database of design scheme are selected by using the PSO cluster analysis method.(3)Considering the needs of all parties involved in the project,the design indexes of each alternative scheme are analyzed and optimized by FMEA and RCM technology.The life cycle cost of each alternative design scheme is predicted by BPNN.Based on the principle of the lowest WLC,the optimal design scheme is selected.(4)BIM and ILS technology are used to deeply optimize the optimal design scheme.(5)The research results can provide reference for the optimization of highway tunnel and bridge engineering design.
作者
段晓晨
喇海霞
刘晓庆
DUAN Xiaochen;LA Haixia;LIU Xiaoqing(Shijiazhuang Tiedao University,Shijiazhuang,Hebei 050043,China)
出处
《铁道工程学报》
EI
北大核心
2021年第3期48-52,101,共6页
Journal of Railway Engineering Society
基金
河北省自然基金(G2019210226)
河北省交通厅科技项目计划(Y2011083)
河北省博士研究生创新资助项目(CXZZBS2021110)。
