atw - International Journal for Nuclear Power | 01.2020

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atw Vol. 65 (2020) | Issue 1 ı January RESEARCH AND INNOVATION 34 (a) ƒ and j factors | Fig. 10. ƒ, j and JF factors with respect to inclination and chevron corrugation. inclination and chevron corrugations on the flow characteristics and thermal performance. It is mainly because of their bulk flow pattern – zig-zag flow. Most of working fluid turns to the groove of the opposite plate at corrugation contacts in the zig-zag flow. So the structure difference of inclination and chevron corrugations has barely influence on flow and heat transfer. Therefore, ƒ, j and JF are almost constant. 4 Summary Comparison between results of numerical simulations and experimental data has verified that CFD simulation is reliable for studies on the corrugation CPSHE. The RNG k-ε turbulence model has been validated more preciously than the laminar model in CPSHE at low Reynolds number from 5 to 50. The corrugation inclination angle β, ratio of pitch to height p/h and corrugation styles have been taken as major parameters of the circular corrugated plate influencing the performance of heat transfer. Some conclusions are obtained as follow: (1) When Reynolds number is low ( 5-50) and p/h=5, the bulk flow pattern is zig-zag flow, no matter how much the corrugation angle is. (2) Flow maldistribution exists in every channel, and it is at a minimum with β=45°. (3) The flow resistance and thermal performance increases with increasing β. When β>60°, increasing rate of thermal performance is low. The comprehensive performance with β= 45° is the best at the Re range from 5 to 50. (4) The flow resistance and thermal performance decreases with reducing p/h. The comprehensive performance with p/h=3.3 is the best. (5) There is nearly no difference between inclination and chevron corrugations in CPSHE at low Reynolds number. Nomenclature ɑ [m 2 /s] Coefficient of thermal Diffusion B [m] Plate width De [m] Hydraulic diameter Ƒ [-] Friction factor G k [-] Generation of turbulence kinetic energy H [m] Corrugation height I [-] Turbulence intensity J [-] Colburn factor L [m] Corrugation length Nu [-] Nusselt number P, ΔP [kPa] Pressure, Pressure drop Pr [-] Prandtl number T [K] Temperature u [m/s] Fluid velocity v [m 2 /s] Kinematic viscosity Greek symbols Α [-] Turbulence Prandtl number β [°] Inclination angle Ρ [kg/m 3 ] Density Subscripts ε [-] ε equation k [-] k equation 1 [-] x-component 2 [-] y-component 3 [-] z-component o, w [-] Lubricating-oil, wall References [1] W.W. Focke, P.G. Knibbe, Flow visualization in parallel-plate ducts with corrugated walls, J. Fluid Mech., 165 (1986): 73–77. [2] G. Gaiser, V. Kottke, Flow phenomena and local heat and mass transfer in corrugated passages, Chem. Eng. Technol., 12 (1989):400–405. [3] A. Muley, R.M. Manglik, Experimental study of turbulent flow heat transfer and pressure drop in a plate heat exchanger with chevron plates, Journal of Heat Transfer, 121(1999):110-117. [4] W.W. Focke, J. Zachariades, I. Olivier, The effect of the corrugation inclination angle on the thermo hydraulic performance of plate heat exchangers, Int. J. Heat Mass Transfer 28 (1985): 1469–1479. [5] A.G. Kanaris, A.A. Mouza, S.V. Paras, Flow and heat transfer prediction in a corrugated plate heat exchanger using a CFD code, Chem. Eng. Technol., 8 (2006): 923-930. [6] J. Lee, K.S. Lee, Flow characteristic and thermal performance in chevron type plate heat exchangers, International Journal of Heat and Mass Transfer., 78(2014): 699-706. [7] W. Li, H.X. Li, G.Q. Li, Numerical and experimental analysis of composite fouling in corrugated plate heat exchangers. International Journal of Heat and Mass Transfer, 63 (2013): 351-360. [8] S.M. Lee, K.Y. Kim, Thermal performance of a double-faced printed circuit heat exchanger with thin plates, Journal of Thermophysics and Heat Transfer, 28 (2014): 251-257. [9] Z.J. Luan, G.M. Zhang, Flow resistance and heat transfer characteristics of a new-type plate heat exchanger. Journal of Hydrodynamics, 20 (2008): 524-529. [10] V. Yakhot, S.A. Orczag, Renormalization group analysis of turbulence, Basic theory. Scient. Comput, 1 (1986): 3-11. [11] J.Y. Yun, K.S. Lee, Influence of design parameters on the heat transfer and flow friction characteristics of the heat exchanger with slit fins, Int. J. Heat Mass Transfer, 43 (2000): 2529–2539. [12] M.S. Kim, J. Lee, Correlations and optimization of a heat exchanger with offset-strip fins, Int. J. Heat Mass Transfer, 54 (2011): 2073–2079. [13] J. Lee, K.S. Lee, Correlations and shape optimization in a channel with aligned dimples and protrusions, Int. J. Heat Mass Transfer, 64 (2013): 444–451. Authors (b) JF factor Shen Ya-jie Gao Yong-heng Zhan Yong-jie CNNP Nuclear Power Operations Management Co Ltd Jiaxing, China Research and Innovation CFD Simulation of Flow Characteristics and Thermal Performance in Circular Plate and Shell Oil Coolers ı Shen Ya-jie, Gao Yong-heng and Zhan Yong-jie
atw Vol. 65 (2020) | Issue 1 ı January Research on Neutron Diffusion and Thermal Hydraulics Coupling Calculation based on FLUENT and its Application Analysis on Fast Reactors Xuebei Zhang, Chi Wang and Hongli Chen The neutron diffusion equation is defined based on the User Defined Function (UDF) and the User Defined Scalar (UDS) functions of the FLUENT. The neutron diffusion equation is solved iteratively by using the solver of the FLUENT with the Finite Volume Method (FVM). At the same time, the mass, momentum and energy equations are solved iteratively. At each iteration, the power distribution (flux distribution) obtained by the iteration of the neutron diffusion equation is transferred to the thermal-hydraulics calculation and is used as the heat source term. At the same time, the temperature distribution obtained from the thermal-hydraulics calculation is transferred to the neutron diffusion calculation and the macroscopic cross sections of the materials are corrected to realize the coupling calculation of the neutron diffusion and the thermal-hydraulics under the same solver of the FLUENT without needing to develop the interface program and the computational cost is saved. 2D-TWIGL benchmark problem is calculated by the FLUENT solver to verify the feasibility for the neutron diffusion. Through the modeling and calculation of the 5 x 5 PWR assembly model, the calculation results are compared with the results of other programs to verify the feasibility of the coupling method and the correctness of data transfer. Then this coupling method is applied to calculate the hot assembly of a modular lead-cooled fast reactor (M 2 LFR-1000) to verify that the thermal-hydraulics characteristics (the maximum fuel temperature and the maximum cladding outer surface temperature) are all within the corresponding thermalhydraulics design limits. RESEARCH AND INNOVATION 35 Key words: neutron diffusion and thermal- hydraulics coupling; UDF and UDS functions; 5 x 5 PWR assembly; M 2 LFR-1000 hot assembly. Traditionally, the best estimation procedure is generally used in reactor design and reactor safety analysis. With the improvement of computer performance and the development of parallel computing, the high confidence simulation of reactor has been paid more attention in the research of reactor design, scheme optimization and safety analysis. Only by considering the multi-physical feedback in reactor simulation, can high confidence simulation be realized. And the neutron diffusion and thermalhydraulics coupling calculation is an important part of multi-physics coupling calculation [1-2]. The actual operation of the reactor is a process of neutrons and thermal reciprocal feedback. Temperature coefficient (fuel temperature coefficient and moderator temperature coefficient) is an important factor for reactivity control in normal operation of reactor [3]. To achieve accurate calculation of reactor operation and transient conditions, the effects of fuel temperature, moderator temperature and density on local neutron flux and system reactivity must be considered. Computational Fluid Dynamics (CFD) program FLUENT can realize the fine simulation of reactor core and fuel assembly by coupling the mass continuity equation, momentum equation and energy conservation equation. The UDS (User Defined Scalar) in the FLUENT can solve a kind of diffusion equation by using the solver in Fluent. It has been widely used in multi-phase flow coupling calculation and flow-field and electric field coupling calculation. H.G.Wang, W.Q.Yang, P.Senior [4] used the UDS to add the water diffusion equation in air and solid phase to FLUENT. And the hydrodynamic parameters of heat and mass transfer between two phases were added to the UDF of FLUENT to simulate the complex gas-solid multi phase process of batch fluidized bed drying. P. Donoso- GarcaL, L. Henrquez- Vargas [5] used the twodimensional numerical simulation method to simulate the turbulent state of the adiabatic regenerative porous medium burner coupled with thermoelectric components. The time and volume averaged transport equation and the two order turbulence model were adopted. The FLUENT was used to simulate the burner through its UDF (user-defined function) and UDS (user- defined scalar) interface to obtain additional terms involving turbulence and thermal energy. The flow field and electric field were calculated considering the effects of inlet velocity and composition, thermal conductivity of porous media and thermal insulation materials on the burner. Y. Liu, Y. P. Liu, S. M. Tao [6] established a three-dimensional (3D) unsteady mathematical model of alumina ball regenerator, and solved it by commercial computational fluid dynamics (CFD) software FLUENT based on the porous medium hypothesis. The standard K-e turbulence model was combined with standard wall function to simulate gas flow and the momentum equation was modified to consider the effect of porous media on fluid flow. The user defined function (UDF) program was programmed in C language and connected with FLUENT. The userdefined scalar (UDS) transfer equation of solid energy conservation was defined. And the heat transfer and thermo-physical properties between gas and solid phases were calculated. J. Jang, H. Arastoopour [7] used ANSYS/FLUENT computational fluid dynamics (CFD) program to simulate the gas-solid two-phase flow pattern, the mixing and drying process of drug particles in three different scales of bubbling fluidized bed dryers. The capacity of water transfer and simulation of drying process was calculated. The user-defined scalar transfer equation (UDS) was added to FLUENT to simulate the flow pattern and heat and mass transfer process of drug drying process based on bubbling fluidized bed. Based on the UDF (User Defined Function) and UDS (User Defined Scalar) functions of FLUENT, Xi’an Jiaotong University Research and Innovation Research on Neutron Diffusion and Thermal Hydraulics Coupling Calculation based on FLUENT and its Application Analysis on Fast Reactors ı Xuebei Zhang, Chi Wang and Hongli Chen
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