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SONG Tianshuai, YU Caizhao, QIN Yanlong, SHI Guoliang, LIU Zhansheng, ZHOU Enkai. An Intelligent Optimization Method for Large Underground Space Construction Scheme Under Low Carbon Target[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(5): 25-32. doi: 10.3724/j.gyjzG23111317
Citation: SONG Tianshuai, YU Caizhao, QIN Yanlong, SHI Guoliang, LIU Zhansheng, ZHOU Enkai. An Intelligent Optimization Method for Large Underground Space Construction Scheme Under Low Carbon Target[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(5): 25-32. doi: 10.3724/j.gyjzG23111317

An Intelligent Optimization Method for Large Underground Space Construction Scheme Under Low Carbon Target

doi: 10.3724/j.gyjzG23111317
  • Received Date: 2023-11-13
    Available Online: 2024-06-22
  • The construction of large underground spaces is an important field of transformation and upgrading of the construction industry. In the construction process of large underground spaces, how to obtain the optimal construction scheme and achieve the goal of green environmental protection is an urgent problem to be solved. Aiming at low carbon, the study proposed an intelligent optimization method for large underground space construction. According to the calculation method of carbon emissions, the construction scheme optimization framework was formed, and the key factors affecting the construction energy consumption were obtained. Based on the analysis of key factors, the influence mechanism of various components and construction paths on carbon emissions was clarified. Driven by the improved Dijkstra algorithm, an intelligent optimization method of construction path was formed. On this basis, the BP neural network optimized by genetic algorithm formed the coupling relationship between carbon emission and hoisting scheme. The optimal construction scheme was obtatined accurately under the low-carbon goal. Taking the construction site of the three major building shared facilities project of the city sub-center as an example, the case analysis was carried out to verify the feasibility of the proposed method. By analyzing the construction carbon emissions, the best construction path was formed.
  • [1]
    刘占省,史国梁,孙佳佳.数字孪生技术及其在智能建造中的应用[J].工业建筑,2021,51(3):184-192.
    [2]
    陈鑫磊,张学民,陈进,等.基于碳排放评价的超小净距隧道绿色施工优化研究[J].中国公路学报,2022,35(1):59-70.
    [3]
    肖建庄,夏冰,肖绪文.工程结构可持续性设计理论架构[J].土木工程学报,2020,53(6):1-12.
    [4]
    王卫东,姚激,岳建勇,等.软土地基文物建筑地下空间开发的关键技术与应用[J].建筑结构学报,2023,44(12):92-99.
    [5]
    满庆鹏,郑慕华,常远,等.基于动态仿真技术的装配式建筑施工人员配置优化:以流水施工模式为例[J].土木工程学报,2023,56(9):178-188.
    [6]
    BESANA D, TIRELLI D. Reuse and retrofitting strategies for a net zero carbon building in milan: an analytic evaluation[J/OL]. Sustainability, 2022, 14[2022-11-02].https://https://doi.org/10.3390/su142316115.
    [7]
    GUSTAVSSON L,JOELSSON A,SATHRE R.Life cycle primary energy use and carbon emission of an eight-storey wood-framed apartment building [J].Energy and Buildings,2010,42 (2):230-242.
    [8]
    ZABALZA B I,ARANDA U A,SCARPELLINI S.Life cycle assessment in buildings:state-of-the-art and simplified LCA methodology as a complement for building certification[J].Building and Environment,2009,44 (12):2510-2520.
    [9]
    GUO C,XU J,YANG L,et al.Life cycle evaluation of greenhouse gas emissions of a highway tunnel:a case study in China [J].Journal of Cleaner Production,2019,211:972-980.
    [10]
    BOYOUNG P,SEBEOM P,YOSOON C,et al.Calculation of a diesel vehicle’s carbon dioxide emissions during haulage operations in an underground mine using GIS [J].Tunnel and Underground Space,2015,25 (4):373-382.
    [11]
    鲍学英,许锟.考虑碳排放的铁路隧道施工机械配置优化模型[J].铁道学报,2020,42(9):157-164.
    [12]
    陈湘生,付艳斌,陈曦,等.地下空间施工技术进展及数智化技术现状[J].中国公路学报,2022,35(1):1-12.
    [13]
    李小雪,雷可,谭忠盛,等.城市地下空间施工风险因素耦合效应研究[J].土木工程学报,2021,54(增刊1):76-86.
    [14]
    LIU Z S, SHI G L, QIN J, et al. Prestressed steel material-allocation path and construction using intelligent digital twins[J/OL]. Metals, 2022, 12[2022-04-06].https://doi.org/10.3390/met12040631.
    [15]
    ZHU A M, ZHANG Z Q, PAN W. Crane-lift path planning for high-rise modular integrated construction through metaheuristic optimization and virtual prototyping[J/OL]. Automation in Construction, 2022,141[2022-04-06]. https://doi.org/10.1016/j.autcon.2022.104434.
    [16]
    SOLTANI A R, TAWFIK H, FERNANDO T. Path planning in construction sites: performance evaluation of the Dijkstra, A*, and GA search algorithms[J]. Advanced Engineering Informatics, 2002,16(4): 291-303.
    [17]
    KIM M, HAM Y, KOO C, et al. Simulating travel paths of construction site workers via deep reinforcement learning considering their spatial cognition and wayfinding behavior[J/OL]. Automation in Construction, 2023,147[2022-11-23].https://doi.org/10.1016/j.autcon.2022.104715.
    [18]
    贾兆琪,杨璐,及炜煜,等.基于生命周期评价的钢结构碳排放计算模型研究[J].工业建筑,2023,53(增刊1):301-308,319.
    [19]
    秦林,郝欣,汪林.顶管技术在地下空间中小型管道施工中的应用[J].现代隧道技术,2022,59(增刊2):228-233.
    [20]
    左松涛,毛占利,范传刚,等.基于地铁站场景的改进型Dijkstra算法疏散路径规划研究[J].铁道科学与工程学报,2023,20(5):1624-1635.
    [21]
    谢新连,刘毅,何傲.海上施工水域船舶航线规划数学建模及求解[J].重庆交通大学学报(自然科学版),2019,38(9):7-12.
    [22]
    戴益民,李怿歆,徐瑛,等.基于GA-BP神经网络的风雹耦合所致冰雹冲击力预测[J/OL].工程力学,2024[2024-04-23].http://kns.cnki.net/kcms/detail/11.

    2595.o3.20230928.1755.018.html.
    [23]
    丁建文,魏霞,高鹏举,等.基于GA-BP神经网络的软土路基运营期沉降预测[J].东南大学学报(自然科学版),2023,53(4):585-591.
    [24]
    冷晟,付有为,马万太,等.基于GA-BP神经网络的喷射成形锭坯形貌调控技术[J].华南理工大学学报(自然科学版),2023,51(2):27-34.
    [25]
    DENG Y, YANG X, HUANG Y, et al. Calculation method of intermediate bearing displacement value for multisupported shafting based on neural network[J]. Journal of Ship Research, 2020,65(4):286-292.
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