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Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

邮发代号 80-972

2019 Impact Factor: 2.657

Frontiers in Energy  2021, Vol. 15 Issue (4): 946-958   https://doi.org/10.1007/s11708-021-0754-z
  本期目录
Improvement of solidification model and analysis of 3D channel blockage with MPS method
Reo KAWAKAMI1(), Xin LI1, Guangtao DUAN2, Akifumi YAMAJI1, Isamu SATO3, Tohru SUZUKI3
1. Cooperative Major in Nuclear Energy, Graduate School and Advanced Science and Engineering, Faculty of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo, 169-8555, Japan
2. Department of Nuclear Engineering and Management, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
3. Department of Nuclear Safety Engineering, Faculty of Engineering, Tokyo City University, 1-28-1 Tamazutsumi, Setagaya-ku, Tokyo, 158-0087, Japan
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Abstract

In a severe accident of a nuclear power reactor, coolant channel blockage by solidified molten core debris may significantly influence the core degradations that follow. The moving particle semi-implicit (MPS) method is one of the Lagrangian-based particle methods for analyzing incompressible flows. In the study described in this paper, a novel solidification model for analyzing melt flowing channel blockage with the MPS method has been developed, which is suitable to attain a sufficient numerical accuracy with a reasonable calculation cost. The prompt velocity diffusion by viscosity is prioritized over the prompt velocity correction by the pressure term (for assuring incompressibility) within each time step over the “mushy zone” (between the solidus and liquidus temperature) for accurate modeling of solidification before fixing the coordinates of the completely solidified particles. To sustain the numerical accuracy and stability, the corrective matrix and particle shifting techniques have been applied to correct the discretization errors from irregular particle arrangements and to recover the regular particle arrangements, respectively. To validate the newly developed algorithm, 2-D benchmark analyses are conducted for steady-state freezing of the water in a laminar flow between two parallel plates. Furthermore, 3-D channel blockage analyses of a boiling water reactor (BWR) fuel support piece have been performed. The results show that a partial channel blockage develops from the vicinity of the speed limiter, which does not fully develop into a complete channel blockage, but still diverts the incoming melt flow that follows to the orifice region.

Key wordsboiling water reactor (BWR)    severe accident    channel blockage    moving particle semi-implicit (MPS) method    solidification
收稿日期: 2020-11-24      出版日期: 2022-01-04
Corresponding Author(s): Reo KAWAKAMI   
 引用本文:   
. [J]. Frontiers in Energy, 2021, 15(4): 946-958.
Reo KAWAKAMI, Xin LI, Guangtao DUAN, Akifumi YAMAJI, Isamu SATO, Tohru SUZUKI. Improvement of solidification model and analysis of 3D channel blockage with MPS method. Front. Energy, 2021, 15(4): 946-958.
 链接本文:  
https://academic.hep.com.cn/fie/CN/10.1007/s11708-021-0754-z
https://academic.hep.com.cn/fie/CN/Y2021/V15/I4/946
Fig.1  
Fig.2  
Fig.3  
Case A B C D E F
Re 700 1200 2300
θW 2.5 1.1 0.6 0.4 1.1
Tab.1  
Fig.4  
Case A B C D E F
Re 700 1200 2300
u¯mo/(m? s 1) 0.02625 0.045 0.08625
θW 2.5 1.1 0.6 0.4 1.1
T0/°C 2.0 4.0 4.0 6.0 4.0
TW/°C –5.0 –4.4 –2.4 –2.4 –4.4
Tab.2  
Fig.5  
Fig.6  
Fig.7  
Fig.8  
Property SS/B4C Zr SS
Density/(kg·m–3) 6646 6520 7930
Specific heat/(J·(kg·K)–1) 452 377 840
Latent heat/(kJ·kg–1) 289 230 268
Melting temperature/K 1420 2100 1700
Thermal conductivity/(W·mK–1) 30.8 36.0 21.0
Tab.3  
Different simulation cases
SS/B4C Zr Zr-FlowRate_H Zr-Superheat_H
Melt SS/B4C Zr Zr Zr
Inflow mass/kg 18 29 29 29
Inflow rate/(kg·s–1) 0.12 0.12 0.24 0.12
Initial melt temperature and superheat/K 1430/10 2110/10 2110/10 2310/210
Tab.4  
Fig.9  
Fig.10  
Fig.11  
Fig.12  
α Threshold parameter
C Corrective matrix
Cp Specific heat capacity
CR Parameter of Ramacciotti model
d Dimension number
f Force
g Gravity
H Half of the flow channel width
h Enthalpy
k Thermal conductivity
l0 Particle size
L Row vector
n0 Initial particle number density
P Pressure
Q Heat source
Re Reynolds number
re Effective interaction radius
r Position vector
t Time
T Temperature
T0 Inflow temperature
TW Wall temperature
u Velocity vector
umo Inflow rate
w(r) Weight function
x,y Position
γ Solid fraction
θw Dimensionless wall temperature
λ Correction factor
μ Dynamic viscosity
v Kinematic viscosity
ρ Density
ϕ A scalar quantity
i,j Particle identification number
I Liquidus
s Solidus
  
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