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Journal of Tsinghua University(Science and Technology)    2021, Vol. 61 Issue (7) : 756-767     DOI: 10.16511/j.cnki.qhdxxb.2021.26.003
Research Article |
Intelligent scheduling for high arch dams
WANG Fei1, LIU Jinfei1, YIN Xishuang1, TAN Yaosheng2, ZHOU Tiangang2, YANG Zhiyue2, FENG Bo2, YANG Xiaolong2
1. PowerChina Chengdu Engineering Corporation Limited, Chengdu 611130, China;
2. China Three Gorges Projects Development Co., Ltd., Chengdu 610041, China
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Abstract  The construction of arch dams is often affected by severe natural environmental conditions and the complex construction processes which slow construction progress. Construction scheduling simulations provide effective management tools for arch dam construction progress planning. Intelligent construction methods based on the Internet of Things (IoT) have been used in the construction of hydropower stations such as the Xiluodu, Wudongde and Baihetan high arch dams. During these projects, arch dam construction management has gradually evolved from simple manual interactions to intelligent systems. However, the simulation parameters often do not accurately reflect the actual construction state, so the simulation resources do not accurately match the actual conditions and schedule optimization, construction resource allocation, project coupling, and multi-party collaboration can be at very different states. Intelligent scheduling simulations based on the Internet of Things have been developed to improve construction scheduling for high arch dams. Finally, this paper summarizes the key technologies for intelligent schedule simulations and identifies key directions for future intelligent schedule simulations.
Keywords high arch dams      construction scheduling      intelligent simulations      big data      Internet of Things     
ZTFLH:  TV51  
Issue Date: 08 June 2021
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WANG Fei
LIU Jinfei
YIN Xishuang
TAN Yaosheng
ZHOU Tiangang
YANG Zhiyue
FENG Bo
YANG Xiaolong
Cite this article:   
WANG Fei,LIU Jinfei,YIN Xishuang, et al. Intelligent scheduling for high arch dams[J]. Journal of Tsinghua University(Science and Technology), 2021, 61(7): 756-767.
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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2021.26.003     OR     http://jst.tsinghuajournals.com/EN/Y2021/V61/I7/756
  
  
  
  
  
  
  
  
  
  
  
  
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