Nuclear Engineering and Technology

  • 제53권4호
  • /
  • Pages.1304-1310
  • /
  • 2021
  • /
  • 1738-5733(pISSN)
  • /
  • 2234-358X(eISSN)
한국원자력학회 (Korean Nuclear Society)
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Development of a novel reconstruction method for two-phase flow CT with improved simulated annealing algorithm

  • Yan, Mingfei (School of Energy and Power Engineering, Xi'an Jiaotong University) ;
  • Hu, Huasi (School of Energy and Power Engineering, Xi'an Jiaotong University) ;
  • Hu, Guang (School of Energy and Power Engineering, Xi'an Jiaotong University) ;
  • Liu, Bin (Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China) ;
  • He, Chao (Institute of Nuclear Physics and Chemistry, China Academy of Engineering Physics) ;
  • Yi, Qiang (Institute of Nuclear Physics and Chemistry, China Academy of Engineering Physics)
  • 투고 : 2020.03.03
  • 심사 : 2020.09.16
  • 발행 : 2021.04.25
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초록

Two-phase flow, especially gas-liquid two-phase flow, has a wide application in industrial field. The diagnosis of two-phase flow parameters, which directly determine the flow and heat transfer characteristics, plays an important role in providing the design reference and ensuring the security of online operation of two-phase flow system. Computer tomography (CT) is a good way to diagnose such parameters with imaging method. This paper has proposed a novel image reconstruction method for thermal neutron CT of two-phase flow with improved simulated annealing (ISA) algorithm, which makes full use of the prior information of two-phase flow and the advantage of stochastic searching algorithm. The reconstruction results demonstrate that its reconstruction accuracy is much higher than that of the reconstruction algorithm based on weighted total difference minimization with soft-threshold filtering (WTDM-STF). The proposed method can also be applied to other types of two-phase flow CT modalities (such as X(𝛄)-ray, capacitance, resistance and ultrasound).

키워드

과제정보

The research is supported by the NSAF Joint Fund of China (Grant No. U1830128) and the National Natural Science Foundation of China (Grant No. 11975182 and 11875214).

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