Verification of source term estimation method against measured data for spent fuel hardware characterization

2013 ◽  
Vol 58 ◽  
pp. 36-42 ◽  
Author(s):  
Dong-Keun Cho ◽  
Heui-Joo Choi ◽  
Jongtae Jeong
Keyword(s):  
Source Term ◽  
Estimation Method ◽  
Measured Data ◽  
Spent Fuel ◽  
Source Term Estimation

scholarly journals Verification of Source Term Estimation Method against Measured Data for Decommissioning Waste from a CANDU Reactor

2011 ◽  
Vol 48 (7) ◽  
pp. 1087-1093 ◽  
Author(s):  
Dong-Keun CHO ◽  
Gwang-Min SUN ◽  
Jongwon CHOI ◽  
Ho-Yeon YANG ◽  
Tae-Won HWANG
Keyword(s):  
Source Term ◽  
Estimation Method ◽  
Measured Data ◽  
Source Term Estimation

A source term estimation method for a nuclear accident using atmospheric dispersion models

2015 ◽  
Vol 58 (1/2) ◽  
pp. 39 ◽  
Author(s):  
Minsik Kim ◽  
Ryohji Ohba ◽  
Masamichi Oura ◽  
Shinsuke Kato ◽  
Masayuki Takigawa ◽  
...  
Keyword(s):  
Source Term ◽  
Atmospheric Dispersion ◽  
Estimation Method ◽  
Nuclear Accident ◽  
Dispersion Models ◽  
Atmospheric Dispersion Models ◽  
Source Term Estimation

Source Term Estimation in Nuclear Accidents Using 4D Variational Data Assimilation for Heterologous Atmospheric Condition

2014 ◽  
Author(s):  
Yun Liu ◽  
Sheng Fang ◽  
Hong Li ◽  
Jingyuan Qu ◽  
Dong Fang
Keyword(s):  
Wind Speed ◽  
Data Assimilation ◽  
Cost Function ◽  
Source Term ◽  
Atmospheric Stability ◽  
Estimation Method ◽  
Atmospheric Condition ◽  
Nuclear Accidents ◽  
Source Information ◽  
Source Term Estimation

The source information of the radionuclide release in nuclear accidents is a key issue of the nuclear emergency response. One way to estimate the source information is by inversing the radionuclide transportation process based on environment radiation monitoring data. The advantage of this method is that the required data are easy to obtain in accident. But it is vulnerable to large uncertainties in both data and transport model. To solve the problem, a source term estimation method based on four-dimensional variational (4DVAR) data assimilation technique was proposed for source term estimation in this study. The proposed method couples 4DVAR with the RIMPUFF air dispersion model. It formulates the inverse modelling of source term estimation as an optimization problem that is trying to find an optimal balance between real observation data and the background field. The advantage of this method is that the radionuclide transport in every time step is included in data assimilation and the result is global optimum in the whole assimilation period. The gradient for cost function is calculated by the backward integration of the adjoint model. Practical imperfectness of measurement were considered and integrated into the cost function. The proposed method was verified using numerical simulation for both homogeneous and heterologous atmospheric condition. The performance of the source term estimation method was also investigated with respect to different release profile, wind speed and atmospheric stability class. The simulation results demonstrate that the estimate matches the true release status well for both homogeneous and heterologous wind field. Also, the experimental results show that the proposed method has strong robustness to wind speed and atmospheric stability.

Federated Learning based Atmospheric Source Term Estimation in Urban Environments

2021 ◽  
pp. 107505
Author(s):  
Jinjin Xu ◽  
Wenli Du ◽  
Qiaoyi Xu ◽  
Jikai Dong ◽  
Bing Wang
Keyword(s):  
Source Term ◽  
Urban Environments ◽  
Source Term Estimation
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