Susumu Yamashita, Nao Kondo, Takanori Sugawara, Hideaki Monji, Hiroyuki Yoshida
{"title":"加速器驱动系统热工设计工具的基准仿真代码:梁窗周围流动特性的验证和基准仿真","authors":"Susumu Yamashita, Nao Kondo, Takanori Sugawara, Hideaki Monji, Hiroyuki Yoshida","doi":"10.1080/00223131.2023.2268676","DOIUrl":null,"url":null,"abstract":"ABSTRACTA detailed computational fluid dynamics code named JAEA Utility Program for Interdisciplinary Thermal-hydraulics Engineering and Research (JUPITER) for the thermal-hydraulics around the beam window (BW) of accelerator-driven system (ADS) was used to confirm the validity of the thermal-hydraulics design tool based on the ANSYS Fluent. The Fluent uses the Reynolds-averaged Navier – Stokes (RANS) model and can quickly calculates the turbulent flow around the BW as a BW design tool. First, the results of JUPITER were compared with the experimental results using a mock-up BW system in water to confirm the validity of JUPITER. This study confirmed that the numerical results are in good agreement with the experimental results. Thus, JUPITER could be used as a benchmark code. A benchmark simulation for the Fluent calculation was also performed using validated JUPITER to demonstrate the applicability of JUPITER as an alternative for experiments. Therefore, the mean values around the BW agreed with each other (e.g. the mean velocity profile for the stream and horizontal directions). Therefore, results confirmed that JUPITER demonstrated a good performance in validating the thermal-hydraulics design tool as a fluid dynamics solver. Moreover, Fluent has sufficient accuracy as a thermal-hydraulics design tool for the ADS.KEYWORDS: Computational fluid dynamics (CFD)thermal-hydraulicsaccelerator-driven system (ADS)beam windowlead-bismuth eutectic flowDisclaimerAs a service to authors and researchers we are providing this version of an accepted manuscript (AM). Copyediting, typesetting, and review of the resulting proofs will be undertaken on this manuscript before final publication of the Version of Record (VoR). During production and pre-press, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal relate to these versions also. AcknowledgmentsThis research was conducted using the supercomputer HPE SGI8600 at the Japan Atomic Energy Agency. The authors would like to express their gratitude to Mr. Asari (LIFULL Co., Ltd.) for fruitful discussions about the mock-up experiment.NomenclatureTableDisplay TableFigure 1. Conceptual view of LBE-cooled ADS (left) and its BW (right)Display full sizeFigure 2. Schematic diagram of the experimental apparatusDisplay full sizeFigure 3. System of the experimental analysisDisplay full sizeFigure 4. Definitions of jet part and its axes. (a) Free jet part, (b) Impinging jet part. The dotted line indicates the centerline of the jet.Display full sizeFigure 5. Radial distribution of the velocity for the y-direction in the free jet part. (a) numerical simulation and (b) experimentDisplay full sizeFigure 6. Comparison between the simulation and the experiment in the free jet partDisplay full sizeFigure 7. Centerline velocity distribution in impinging jet partDisplay full sizeFigure 8. Comparison between the simulation and the experiment for nondimensional velocity distribution in impinging jet part for several s/D positionsDisplay full sizeFigure 9. Schematic diagram of the pressure measurementDisplay full sizeFigure 10. Pressure fluctuation on the BW. Left: numerical simulation, right: experimentDisplay full sizeFigure 11. Computational system in vertical cross-section C-C’ for JUPITER and FluentDisplay full sizeFigure 12. Computational grid for JUPITER (a) and Fluent (b)Display full sizeFigure 13. Distribution of the volumetric heat source. Left: PHITS, right: fitting functionDisplay full sizeFigure 14. Velocity vector distribution for JUPITER (left) and Fluent (right)Display full sizeFigure 15. Temperature distribution for JUPITER (left) and Fluent (right)Display full sizeFigure 16. Comparison between JUPITER and Fluent results for the spanwise mean velocity profile in the y-direction. Circle: Fluent, solid line: JUPITER. The velocity contour indicates the Fluent result.Display full sizeFigure 17. Comparison between JUPITER and Fluent results for the streamwise mean velocity profile in the y-direction. Circle: Fluent, solid line: JUPITER. The velocity contour indicates the Fluent result.Display full sizeFigure 18. Comparison between JUPITER and Fluent results for the mean temperature profile in the y-direction. Circle: Fluent, solid line: JUPITER. The temperature contour indicates the JUPITER result.Display full sizeFigure 19. Time changes of the temperature distribution by JUPITER for the grid resolution, 388 × 1632 × 2Display full sizeFigure 20. Velocity magnitude and temperature distribution at the jet and bulk boundary in 0.2 m ≤ y ≤ 0.6 mDisplay full sizeFigure 21. Inside and outside surface temperature distribution of the BW for the s-direction in the grid case (a); 184 × 816 × 2Display full sizeFigure 22. Inside and outside surface temperature distribution of the BW for the s-direction in the grid case (b); 388 × 1632 × 2Display full sizeFigure 23. Inside and outside surface temperature distribution of the BW for the s-direction in the grid case (c); 776 × 3264 × 2Display full sizeFigure 24. Counter flow on the BW surface (left) and the local high temperature distribution due to the counter flow (right) in the coarse grid; 184 × 816 × 2Display full sizeReferences Tsujimoto K, Sasa T, Nishihara K et al. Neutronics design for lead-bismuth cooled accelerator-driven system for transmutation of minor actinide. J Nucl Sci Technol. 2004; 41: 21–36. 1 10.1080/18811248.2004.9715454 [Taylor & Francis Online] [Web of Science ®], [Google Scholar] Accelerator-driven Systems (ADS) and Fast Reactors (FR) in Advanced Nuclear Fuel Cycles A Comparative Study. NEA OECD Publishing. 2002 ; ISBN :92-64-18482-1. [Google Scholar] Status of Accelerator Driven Systems Research and Technology Development. IAEA-TECDOC-1766, 2015. [Google Scholar] Mantha V, Mohanty A.K., Satyamurthy P. Thermal hydraulics studies of spallation target for one-way coupled Indian accelerator driven systems with low energy proton beam. Pramana journal of physics. 2007; 68: 355–363. [Crossref] [Web of Science ®], [Google Scholar] Cho C, Tak N, Choi J et al. CFD analysis of the HYPER spallation target. Ann Nucl Energy. 2008; 35: 1256–1263. 7 10.1016/j.anucene.2007.12.011 [Crossref] [Web of Science ®], [Google Scholar] Menter F.R. Zonal Two Equation k-ω Turbulence Model for Aerodynamic Flows. AIAA 24th Fluid Dynamics Conference. 1993. [Google Scholar] Daubner M, Batta A, Fellmoser F, Lefhalm C.H., Mack K.J., Stieglitz R. Turbulent heat mixing of a heavy liquid metal flow within the MEGAPIE window geometry: The heated jet experiments. Journal of Nuclear Material. 2004; 335: 286–292. [Crossref] [Web of Science ®], [Google Scholar] Gohar Y, Cao Y, Kraus A.R. ADS design concept for disposing of the U.S. spent nuclear fuel inventory. Ann Nucl Energy. 2021; 160: DOI: 10.1016/j.anucene.2021.108385. [Crossref] [Web of Science ®], [Google Scholar] Saito S, Wan T, Okubo N, Obayashi H, Watanabe N, Odaira N, Kinoshita H, Yamaki K, Kita S, Yoshimoto H, Sasa T. Status of LBE study and experimental plan at JAEA. Proc. 3rd J-PARC Symposium. 2021; 33: 011041-1-011041-6. [Crossref], [Google Scholar] Aït Abderrahim H, Kupschus P, Malambu E, Benoit Ph, Van Tichelen K, Arien B, Vermeersch F, D’hondt P, Jongen Y, Ternier S, Vandeplassche D. MYRRHA: A multipurpose accelerator driven system for research & development. Nuclear Instruments and Methods in Physics Research A. 2001; 463: 487–494. [Crossref] [Web of Science ®], [Google Scholar] Schyns M, Aït Abderrahim H, Baeten P, Fernandez R, Debruyn D. The MYRRHA ADS Project in Belgium Enters the Front End Engineering Phase. Proc. 2nd Int. Symp. Science at J-PARC. 2015; 8. [Google Scholar] Nishihara K, Sugawara T, Tsujimoto K. PSi project for Accelerator-Driven System. Proc. 4th International Workshop on Technology and Components of Accelerator-Driven Systems (TCADS–4). 2019. [Google Scholar] Sugawara T, Watanabe N, Nishihara K. PSi project in JAEA; Plant design part. Proc. Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020). 2020. [Google Scholar] Tsujimoto K, Oigawa H, Kikuchi K, Kurata Y, Mizumoto M, Sasa T, Saito S, Nishihara K, Umeno M, Takei H. Feasibility of lead-bismuth-cooled accelerator-driven system for minor-actinide transmutation. Nucl. Tehnol. 2008; 161: 315–328. [Taylor & Francis Online] [Web of Science ®], [Google Scholar] Sugawara T, Nishihara K, Obayashi H et al. Conceptual Design Study of Beam Window for Accelerator-Driven System. J Nucl Sci Technol. 2010; 47: 953–962. 10 10.1080/18811248.2010.9720974 [Taylor & Francis Online] [Web of Science ®], [Google Scholar] Sugawara T, Eguchi Y, Obayashi H et al. Conceptual design study of beam window for accelerator-driven system with subcriticality adjustment rod. Nucl Eng Des. 2018; 331: 11–23. 10.1016/j.nucengdes.2018.02.011 [Crossref] [Web of Science ®], [Google Scholar] Sato T, Iwamoto Y, Hashimoto S, et al. Features of Particle and Heavy Ion Transport code System (PHITS) version 3.02. J Nucl Sci Technol. 2018; 55: 684–690. 6 10.1080/00223131.2017.1419890 [Taylor & Francis Online] [Web of Science ®], [Google Scholar] Ansys, Inc. Ansys Fluent [internet]. [ cited 2022]. Available from: https://www.ansys.com/products/fluids/ansys-fluent. [Google Scholar] Ansys, Inc. Ansys Mechanical [internet]. [ cited 2022]. Available from: https://www.ansys.com/products/structures/ansys-mechanical. [Google Scholar] Yamashita S, Ina T, Idomura Y, Yoshida H. A numerical simulation method for molten material behavior in nuclear reactors. Nucl Eng Des. 2017; 332: 301–312. [Crossref], [Google Scholar] Yamashita S, Tokushima K, Kurata M, Yoshida H. Development of numerical simulation method for melt relocation behavior in nuclear reactors: validation and applicability for actual core structures. Mech Eng J. 2017; 4: 1–13. [Crossref], [Google Scholar] Kim J, Kim D, Choi H. An immersed boundary finite-volume method for simulations of flow in complex geometries. J Comput Phys. 2001 Feb; 171: 132–150. [Crossref] [Web of Science ®], [Google Scholar] Kawamura T, Kuwahara K. Computation of High Reynolds Number Flow around a Circular Cylinder with Surface Roughness. AIAA, 22nd Aerospace Sciences Meeting. 1984. [Crossref], [Google Scholar] Japan Society of Civil Engineering. Introduction to Numerical Simulation Methods for Flow in Wind Engineering. 1992. [Google Scholar] Rai M.M, Moin P. Direct Simulation of Turbulent Flow Using Finite Difference Schemes. J Comput Phys. 1991; 96: 15–53. [Crossref] [Web of Science ®], [Google Scholar] Miyauchi T, Hirata T, Tanahashi M. Direct Numerical Simulation of Three-Dimensional Homogeneous Isotropic Trubulence by High-Order Finite Difference Scheme (Comparison with the Spectral Method and the Experiment). Transactions of the Japan Society of Mechanical Engineers. B. 1995; 61: 168–173. [Crossref], [Google Scholar] Hayashi S, Ohmoto T, Yakita K, Hirakawa R. Fundamental Study on Direct Numerical Simulation Using Upwind Difference Scheme. J appl mech. 1999; 2: 599–608. [Crossref], [Google Scholar] Adams NA, Hickel S, Franz S Implicit subgrid-scale modeling by adaptive deconvolution. J Comput Phys. 2004; 200: 412–431. 2 10.1016/j.jcp.2004.04.010 [Crossref] [Web of Science ®], [Google Scholar] Ono A, Yamashita S, Suzuki T, Yoshida H. Numerical simulation of two-phase flow in 4x4 simulated bundle. Mechanical Engineering Journal. 2020; 7. 3 19-00583-19-00583 10.1299/mej.19-00583 [Crossref] [Web of Science ®], [Google Scholar] Yamashita S, Uesawa S, Ono A, Yoshida H. Development of a numerical simulation method for air cooling of fuel debris by JUPITER. Mechanical Engineering Journal. 2023; 10: DOI: 10.1299/mej.22-00485. [Crossref], [Google Scholar] Gottlieb S, Shu C.W. Total variation diminishing Runge–Kutta schemes, Mathematics of Computation. 1998; 67: 73–85. [Crossref] [Web of Science ®], [Google Scholar] Jiang G, Shu CW Efficient implementation of weighted eno schemes. J Comput Phys. 1996 Jan; 126: 202–228. 1 10.1006/jcph.1996.0130 [Crossref] [Web of Science ®], [Google Scholar] Tani I, Komatsu Y. Impingement of a Round Jet on Flat Surface. Proc. 11th congress of Appl. Mech. 1964; 672–676. [Google Scholar] Shakouchi T, Matsumoto A, Watanabe A. Heat and Fluid Flow Properties of Circular Impinging Jet with a Low Nozzle to Plate Spacing. Trans. JSME, Ser. B. 2001; 66: 2650–2655. [Google Scholar] Technical Design Report on J-PARC Transmutation Experimental Facility – ADS Target Test Facility (TEF-T) –. JAEA-Technology. 2017; 003: 22. [Google Scholar] Handbook on Lead-bismuth Eutectic Alloy and Lead Properties, Materials Compatibility, Thermal-hydraulics and Technologies. 2015; [internet], Available from: https://www.oecd-nea.org/jcms/pl_14972/handbook-on-lead-bismuth-eutectic-alloy-and-lead-properties-materials-compatibility-thermal-hydraulics-and-technologies-2015-edition?details=true. [Google Scholar] The Japan Society of Mechanical Engineers. Heat Transfer 5th edition. 2009; 332. [Google Scholar] Chui E.H., Raithby GD. Computation of radiant heat transfer on a non-orthogonal mesh using the finite-volume method. Numer. Heat Transfer. 1993; 23: 269–288. [Taylor & Francis Online] [Web of Science ®], [Google Scholar] Menter F.R., Carregal Ferreira J., Esch T., Konno B. The SST Turbulence Model with Improved Wall Treatment for Heat Transfer Predictions in Gas Turbines. Proc. International Gas Trubine Congress. 2003. [Google Scholar] Kajishima T. Numerical Simulation of Turbulent Flows. Japan: Yokendo Ltd.; 2003. p.171–172. [Google Scholar]Notes1 RANS, which is also translated as the Reynolds-averaged model, is one of the turbulence models. RANS is an ensemble-averaged method of solving the Navier – Stokes equations, which are the equations of fluid motion, and all turbulence effects are represented by the turbulence model. RANS performs averaging in space and time, thus reducing the computational cost.2 Total Variation Diminishing (TVD) Runge – Kutta methods are one of the temporal discretization methods of differential equations. These methods guarantee that the total variation of the solution does not increase. For example, if the solution represents a velocity profile, spurious oscillations caused by the numerical method may trigger instability in the simulation. Using a TVD method would ensure that this situation does not occur.3 Weighted Essentially Non-oscillatory (WENO) methods are one of the numerical solutions of differential equations, which is categorized as high-resolution schemes. These schemes’ merit is their ability to achieve high-order accuracy in smooth regions while maintaining stable, non-oscillatory, and sharp discontinuity transitions. Thus, the schemes are suitable for problems containing both strong discontinuities and complex smooth solution features.4 In fact, there are no materials and flow in the vacuum region, but numerical calculations cannot set up a situation where there is nothing. Therefore, only the characteristic that no heat is transferred in the vacuum region was reproduced by giving a very small thermal conductivity, and the properties of T91 were used as assumed values for the other physical properties.","PeriodicalId":16526,"journal":{"name":"Journal of Nuclear Science and Technology","volume":"10 1","pages":"0"},"PeriodicalIF":1.5000,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Benchmark simulation code for the thermal-hydraulics design tool of the accelerator-driven system: validation and benchmark simulation of flow behavior around the beam window\",\"authors\":\"Susumu Yamashita, Nao Kondo, Takanori Sugawara, Hideaki Monji, Hiroyuki Yoshida\",\"doi\":\"10.1080/00223131.2023.2268676\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACTA detailed computational fluid dynamics code named JAEA Utility Program for Interdisciplinary Thermal-hydraulics Engineering and Research (JUPITER) for the thermal-hydraulics around the beam window (BW) of accelerator-driven system (ADS) was used to confirm the validity of the thermal-hydraulics design tool based on the ANSYS Fluent. The Fluent uses the Reynolds-averaged Navier – Stokes (RANS) model and can quickly calculates the turbulent flow around the BW as a BW design tool. First, the results of JUPITER were compared with the experimental results using a mock-up BW system in water to confirm the validity of JUPITER. This study confirmed that the numerical results are in good agreement with the experimental results. Thus, JUPITER could be used as a benchmark code. A benchmark simulation for the Fluent calculation was also performed using validated JUPITER to demonstrate the applicability of JUPITER as an alternative for experiments. Therefore, the mean values around the BW agreed with each other (e.g. the mean velocity profile for the stream and horizontal directions). Therefore, results confirmed that JUPITER demonstrated a good performance in validating the thermal-hydraulics design tool as a fluid dynamics solver. Moreover, Fluent has sufficient accuracy as a thermal-hydraulics design tool for the ADS.KEYWORDS: Computational fluid dynamics (CFD)thermal-hydraulicsaccelerator-driven system (ADS)beam windowlead-bismuth eutectic flowDisclaimerAs a service to authors and researchers we are providing this version of an accepted manuscript (AM). Copyediting, typesetting, and review of the resulting proofs will be undertaken on this manuscript before final publication of the Version of Record (VoR). During production and pre-press, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal relate to these versions also. AcknowledgmentsThis research was conducted using the supercomputer HPE SGI8600 at the Japan Atomic Energy Agency. The authors would like to express their gratitude to Mr. Asari (LIFULL Co., Ltd.) for fruitful discussions about the mock-up experiment.NomenclatureTableDisplay TableFigure 1. Conceptual view of LBE-cooled ADS (left) and its BW (right)Display full sizeFigure 2. Schematic diagram of the experimental apparatusDisplay full sizeFigure 3. System of the experimental analysisDisplay full sizeFigure 4. Definitions of jet part and its axes. (a) Free jet part, (b) Impinging jet part. The dotted line indicates the centerline of the jet.Display full sizeFigure 5. Radial distribution of the velocity for the y-direction in the free jet part. (a) numerical simulation and (b) experimentDisplay full sizeFigure 6. Comparison between the simulation and the experiment in the free jet partDisplay full sizeFigure 7. Centerline velocity distribution in impinging jet partDisplay full sizeFigure 8. Comparison between the simulation and the experiment for nondimensional velocity distribution in impinging jet part for several s/D positionsDisplay full sizeFigure 9. Schematic diagram of the pressure measurementDisplay full sizeFigure 10. Pressure fluctuation on the BW. Left: numerical simulation, right: experimentDisplay full sizeFigure 11. Computational system in vertical cross-section C-C’ for JUPITER and FluentDisplay full sizeFigure 12. Computational grid for JUPITER (a) and Fluent (b)Display full sizeFigure 13. Distribution of the volumetric heat source. Left: PHITS, right: fitting functionDisplay full sizeFigure 14. Velocity vector distribution for JUPITER (left) and Fluent (right)Display full sizeFigure 15. Temperature distribution for JUPITER (left) and Fluent (right)Display full sizeFigure 16. Comparison between JUPITER and Fluent results for the spanwise mean velocity profile in the y-direction. Circle: Fluent, solid line: JUPITER. The velocity contour indicates the Fluent result.Display full sizeFigure 17. Comparison between JUPITER and Fluent results for the streamwise mean velocity profile in the y-direction. Circle: Fluent, solid line: JUPITER. The velocity contour indicates the Fluent result.Display full sizeFigure 18. Comparison between JUPITER and Fluent results for the mean temperature profile in the y-direction. Circle: Fluent, solid line: JUPITER. The temperature contour indicates the JUPITER result.Display full sizeFigure 19. Time changes of the temperature distribution by JUPITER for the grid resolution, 388 × 1632 × 2Display full sizeFigure 20. Velocity magnitude and temperature distribution at the jet and bulk boundary in 0.2 m ≤ y ≤ 0.6 mDisplay full sizeFigure 21. Inside and outside surface temperature distribution of the BW for the s-direction in the grid case (a); 184 × 816 × 2Display full sizeFigure 22. Inside and outside surface temperature distribution of the BW for the s-direction in the grid case (b); 388 × 1632 × 2Display full sizeFigure 23. Inside and outside surface temperature distribution of the BW for the s-direction in the grid case (c); 776 × 3264 × 2Display full sizeFigure 24. Counter flow on the BW surface (left) and the local high temperature distribution due to the counter flow (right) in the coarse grid; 184 × 816 × 2Display full sizeReferences Tsujimoto K, Sasa T, Nishihara K et al. Neutronics design for lead-bismuth cooled accelerator-driven system for transmutation of minor actinide. J Nucl Sci Technol. 2004; 41: 21–36. 1 10.1080/18811248.2004.9715454 [Taylor & Francis Online] [Web of Science ®], [Google Scholar] Accelerator-driven Systems (ADS) and Fast Reactors (FR) in Advanced Nuclear Fuel Cycles A Comparative Study. NEA OECD Publishing. 2002 ; ISBN :92-64-18482-1. [Google Scholar] Status of Accelerator Driven Systems Research and Technology Development. IAEA-TECDOC-1766, 2015. [Google Scholar] Mantha V, Mohanty A.K., Satyamurthy P. Thermal hydraulics studies of spallation target for one-way coupled Indian accelerator driven systems with low energy proton beam. Pramana journal of physics. 2007; 68: 355–363. [Crossref] [Web of Science ®], [Google Scholar] Cho C, Tak N, Choi J et al. CFD analysis of the HYPER spallation target. Ann Nucl Energy. 2008; 35: 1256–1263. 7 10.1016/j.anucene.2007.12.011 [Crossref] [Web of Science ®], [Google Scholar] Menter F.R. Zonal Two Equation k-ω Turbulence Model for Aerodynamic Flows. AIAA 24th Fluid Dynamics Conference. 1993. [Google Scholar] Daubner M, Batta A, Fellmoser F, Lefhalm C.H., Mack K.J., Stieglitz R. Turbulent heat mixing of a heavy liquid metal flow within the MEGAPIE window geometry: The heated jet experiments. Journal of Nuclear Material. 2004; 335: 286–292. [Crossref] [Web of Science ®], [Google Scholar] Gohar Y, Cao Y, Kraus A.R. ADS design concept for disposing of the U.S. spent nuclear fuel inventory. Ann Nucl Energy. 2021; 160: DOI: 10.1016/j.anucene.2021.108385. [Crossref] [Web of Science ®], [Google Scholar] Saito S, Wan T, Okubo N, Obayashi H, Watanabe N, Odaira N, Kinoshita H, Yamaki K, Kita S, Yoshimoto H, Sasa T. Status of LBE study and experimental plan at JAEA. Proc. 3rd J-PARC Symposium. 2021; 33: 011041-1-011041-6. [Crossref], [Google Scholar] Aït Abderrahim H, Kupschus P, Malambu E, Benoit Ph, Van Tichelen K, Arien B, Vermeersch F, D’hondt P, Jongen Y, Ternier S, Vandeplassche D. MYRRHA: A multipurpose accelerator driven system for research & development. Nuclear Instruments and Methods in Physics Research A. 2001; 463: 487–494. [Crossref] [Web of Science ®], [Google Scholar] Schyns M, Aït Abderrahim H, Baeten P, Fernandez R, Debruyn D. The MYRRHA ADS Project in Belgium Enters the Front End Engineering Phase. Proc. 2nd Int. Symp. Science at J-PARC. 2015; 8. [Google Scholar] Nishihara K, Sugawara T, Tsujimoto K. PSi project for Accelerator-Driven System. Proc. 4th International Workshop on Technology and Components of Accelerator-Driven Systems (TCADS–4). 2019. [Google Scholar] Sugawara T, Watanabe N, Nishihara K. PSi project in JAEA; Plant design part. Proc. Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020). 2020. [Google Scholar] Tsujimoto K, Oigawa H, Kikuchi K, Kurata Y, Mizumoto M, Sasa T, Saito S, Nishihara K, Umeno M, Takei H. Feasibility of lead-bismuth-cooled accelerator-driven system for minor-actinide transmutation. Nucl. Tehnol. 2008; 161: 315–328. [Taylor & Francis Online] [Web of Science ®], [Google Scholar] Sugawara T, Nishihara K, Obayashi H et al. Conceptual Design Study of Beam Window for Accelerator-Driven System. J Nucl Sci Technol. 2010; 47: 953–962. 10 10.1080/18811248.2010.9720974 [Taylor & Francis Online] [Web of Science ®], [Google Scholar] Sugawara T, Eguchi Y, Obayashi H et al. Conceptual design study of beam window for accelerator-driven system with subcriticality adjustment rod. Nucl Eng Des. 2018; 331: 11–23. 10.1016/j.nucengdes.2018.02.011 [Crossref] [Web of Science ®], [Google Scholar] Sato T, Iwamoto Y, Hashimoto S, et al. Features of Particle and Heavy Ion Transport code System (PHITS) version 3.02. J Nucl Sci Technol. 2018; 55: 684–690. 6 10.1080/00223131.2017.1419890 [Taylor & Francis Online] [Web of Science ®], [Google Scholar] Ansys, Inc. Ansys Fluent [internet]. [ cited 2022]. Available from: https://www.ansys.com/products/fluids/ansys-fluent. [Google Scholar] Ansys, Inc. Ansys Mechanical [internet]. [ cited 2022]. Available from: https://www.ansys.com/products/structures/ansys-mechanical. [Google Scholar] Yamashita S, Ina T, Idomura Y, Yoshida H. A numerical simulation method for molten material behavior in nuclear reactors. Nucl Eng Des. 2017; 332: 301–312. [Crossref], [Google Scholar] Yamashita S, Tokushima K, Kurata M, Yoshida H. Development of numerical simulation method for melt relocation behavior in nuclear reactors: validation and applicability for actual core structures. Mech Eng J. 2017; 4: 1–13. [Crossref], [Google Scholar] Kim J, Kim D, Choi H. An immersed boundary finite-volume method for simulations of flow in complex geometries. J Comput Phys. 2001 Feb; 171: 132–150. [Crossref] [Web of Science ®], [Google Scholar] Kawamura T, Kuwahara K. Computation of High Reynolds Number Flow around a Circular Cylinder with Surface Roughness. AIAA, 22nd Aerospace Sciences Meeting. 1984. [Crossref], [Google Scholar] Japan Society of Civil Engineering. Introduction to Numerical Simulation Methods for Flow in Wind Engineering. 1992. [Google Scholar] Rai M.M, Moin P. Direct Simulation of Turbulent Flow Using Finite Difference Schemes. J Comput Phys. 1991; 96: 15–53. [Crossref] [Web of Science ®], [Google Scholar] Miyauchi T, Hirata T, Tanahashi M. Direct Numerical Simulation of Three-Dimensional Homogeneous Isotropic Trubulence by High-Order Finite Difference Scheme (Comparison with the Spectral Method and the Experiment). Transactions of the Japan Society of Mechanical Engineers. B. 1995; 61: 168–173. [Crossref], [Google Scholar] Hayashi S, Ohmoto T, Yakita K, Hirakawa R. Fundamental Study on Direct Numerical Simulation Using Upwind Difference Scheme. J appl mech. 1999; 2: 599–608. [Crossref], [Google Scholar] Adams NA, Hickel S, Franz S Implicit subgrid-scale modeling by adaptive deconvolution. J Comput Phys. 2004; 200: 412–431. 2 10.1016/j.jcp.2004.04.010 [Crossref] [Web of Science ®], [Google Scholar] Ono A, Yamashita S, Suzuki T, Yoshida H. Numerical simulation of two-phase flow in 4x4 simulated bundle. Mechanical Engineering Journal. 2020; 7. 3 19-00583-19-00583 10.1299/mej.19-00583 [Crossref] [Web of Science ®], [Google Scholar] Yamashita S, Uesawa S, Ono A, Yoshida H. Development of a numerical simulation method for air cooling of fuel debris by JUPITER. Mechanical Engineering Journal. 2023; 10: DOI: 10.1299/mej.22-00485. [Crossref], [Google Scholar] Gottlieb S, Shu C.W. Total variation diminishing Runge–Kutta schemes, Mathematics of Computation. 1998; 67: 73–85. [Crossref] [Web of Science ®], [Google Scholar] Jiang G, Shu CW Efficient implementation of weighted eno schemes. J Comput Phys. 1996 Jan; 126: 202–228. 1 10.1006/jcph.1996.0130 [Crossref] [Web of Science ®], [Google Scholar] Tani I, Komatsu Y. Impingement of a Round Jet on Flat Surface. Proc. 11th congress of Appl. Mech. 1964; 672–676. [Google Scholar] Shakouchi T, Matsumoto A, Watanabe A. Heat and Fluid Flow Properties of Circular Impinging Jet with a Low Nozzle to Plate Spacing. Trans. JSME, Ser. B. 2001; 66: 2650–2655. [Google Scholar] Technical Design Report on J-PARC Transmutation Experimental Facility – ADS Target Test Facility (TEF-T) –. JAEA-Technology. 2017; 003: 22. [Google Scholar] Handbook on Lead-bismuth Eutectic Alloy and Lead Properties, Materials Compatibility, Thermal-hydraulics and Technologies. 2015; [internet], Available from: https://www.oecd-nea.org/jcms/pl_14972/handbook-on-lead-bismuth-eutectic-alloy-and-lead-properties-materials-compatibility-thermal-hydraulics-and-technologies-2015-edition?details=true. [Google Scholar] The Japan Society of Mechanical Engineers. Heat Transfer 5th edition. 2009; 332. [Google Scholar] Chui E.H., Raithby GD. Computation of radiant heat transfer on a non-orthogonal mesh using the finite-volume method. Numer. Heat Transfer. 1993; 23: 269–288. [Taylor & Francis Online] [Web of Science ®], [Google Scholar] Menter F.R., Carregal Ferreira J., Esch T., Konno B. The SST Turbulence Model with Improved Wall Treatment for Heat Transfer Predictions in Gas Turbines. Proc. International Gas Trubine Congress. 2003. [Google Scholar] Kajishima T. Numerical Simulation of Turbulent Flows. Japan: Yokendo Ltd.; 2003. p.171–172. [Google Scholar]Notes1 RANS, which is also translated as the Reynolds-averaged model, is one of the turbulence models. RANS is an ensemble-averaged method of solving the Navier – Stokes equations, which are the equations of fluid motion, and all turbulence effects are represented by the turbulence model. RANS performs averaging in space and time, thus reducing the computational cost.2 Total Variation Diminishing (TVD) Runge – Kutta methods are one of the temporal discretization methods of differential equations. These methods guarantee that the total variation of the solution does not increase. For example, if the solution represents a velocity profile, spurious oscillations caused by the numerical method may trigger instability in the simulation. Using a TVD method would ensure that this situation does not occur.3 Weighted Essentially Non-oscillatory (WENO) methods are one of the numerical solutions of differential equations, which is categorized as high-resolution schemes. These schemes’ merit is their ability to achieve high-order accuracy in smooth regions while maintaining stable, non-oscillatory, and sharp discontinuity transitions. Thus, the schemes are suitable for problems containing both strong discontinuities and complex smooth solution features.4 In fact, there are no materials and flow in the vacuum region, but numerical calculations cannot set up a situation where there is nothing. Therefore, only the characteristic that no heat is transferred in the vacuum region was reproduced by giving a very small thermal conductivity, and the properties of T91 were used as assumed values for the other physical properties.\",\"PeriodicalId\":16526,\"journal\":{\"name\":\"Journal of Nuclear Science and Technology\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Nuclear Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/00223131.2023.2268676\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NUCLEAR SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Nuclear Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/00223131.2023.2268676","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NUCLEAR SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
利用JAEA跨学科热工水力工程与研究实用程序(Utility Program for Interdisciplinary thermal-hydraulic Engineering and Research,简称JUPITER)详细计算流体力学代码,对加速器驱动系统(ADS)梁窗周围热工水力设计工具的有效性进行了验证。Fluent使用reynolds -average Navier - Stokes (RANS)模型,可以快速计算出BW周围的湍流,作为BW设计工具。首先,将JUPITER的计算结果与水中BW系统模型的实验结果进行了比较,验证了JUPITER的有效性。研究结果表明,数值计算结果与实验结果吻合较好。因此,JUPITER可以用作基准代码。还使用经过验证的JUPITER对Fluent计算进行了基准模拟,以证明JUPITER作为实验替代方案的适用性。因此,BW周围的平均值是一致的(例如,水流和水平方向的平均速度剖面)。因此,结果证实,JUPITER在验证热工设计工具作为流体动力学求解器方面表现良好。关键词:计算流体动力学(CFD)热液压加速器驱动系统(ADS)束流窗铅铋共晶流免责声明作为对作者和研究人员的服务,我们提供了这个版本的接受稿件(AM)。在最终出版版本记录(VoR)之前,将对该手稿进行编辑、排版和审查。在制作和印前,可能会发现可能影响内容的错误,所有适用于期刊的法律免责声明也与这些版本有关。本研究是在日本原子能机构的超级计算机HPE SGI8600上进行的。作者对Asari先生(LIFULL Co., Ltd)对模型实验进行的富有成果的讨论表示感谢。NomenclatureTableDisplay表lbe冷却ADS的概念图(左)和BW(右)实验装置原理图显示全尺寸图3。系统实验分析显示全尺寸图4。射流零件及其轴的定义。(a)自由射流部分,(b)冲击射流部分。虚线表示喷气机的中心线。显示完整尺寸图5自由射流部分y方向速度的径向分布。(a)数值模拟(b)实验自由射流部分的仿真与实验对比显示全尺寸图7。撞击射流部件的中心线速度分布显示全尺寸图8。几个s/D位置冲击射流零件无因次速度分布的仿真与实验比较压力测量示意图显示全尺寸图10。BW压力波动。左:数值模拟,右:实验计算系统在垂直截面C-C '为木星和FluentDisplay全尺寸图12。木星计算网格(a)和Fluent计算网格(b)体积热源的分布。左:PHITS,右:拟合功能显示全尺寸图14木星(左)和Fluent(右)的速度矢量分布显示完整尺寸图15。木星(左)和Fluent(右)的温度分布木星和Fluent在y方向上的展向平均速度剖面的比较。圆:流畅,实线:木星。速度轮廓线表示Fluent结果。显示完整尺寸图17木星和Fluent在y方向上的平均流速剖面结果的比较。圆:流畅,实线:木星。速度轮廓线表示Fluent结果。显示完整尺寸图18。木星和Fluent在y方向平均温度分布结果的比较。圆:流畅,实线:木星。温度等高线表示木星的结果。显示完整尺寸图19。木星温度分布的时间变化,网格分辨率,388 × 1632 × 20.2 m≤y≤0.6 m范围内射流与体边界处的速度大小和温度分布(a)栅格情况下s方向BW内外表面温度分布;显示全尺寸图22。(b)栅格情况下s方向BW内外表面温度分布;显示全尺寸图23。 4实际上,真空区域内是没有物质和流动的,但是数值计算不能建立一个什么都没有的情况。因此,通过给出非常小的导热系数,只再现了真空区域无热传递的特性,并将T91的性质作为其他物理性质的假设值。
Benchmark simulation code for the thermal-hydraulics design tool of the accelerator-driven system: validation and benchmark simulation of flow behavior around the beam window
ABSTRACTA detailed computational fluid dynamics code named JAEA Utility Program for Interdisciplinary Thermal-hydraulics Engineering and Research (JUPITER) for the thermal-hydraulics around the beam window (BW) of accelerator-driven system (ADS) was used to confirm the validity of the thermal-hydraulics design tool based on the ANSYS Fluent. The Fluent uses the Reynolds-averaged Navier – Stokes (RANS) model and can quickly calculates the turbulent flow around the BW as a BW design tool. First, the results of JUPITER were compared with the experimental results using a mock-up BW system in water to confirm the validity of JUPITER. This study confirmed that the numerical results are in good agreement with the experimental results. Thus, JUPITER could be used as a benchmark code. A benchmark simulation for the Fluent calculation was also performed using validated JUPITER to demonstrate the applicability of JUPITER as an alternative for experiments. Therefore, the mean values around the BW agreed with each other (e.g. the mean velocity profile for the stream and horizontal directions). Therefore, results confirmed that JUPITER demonstrated a good performance in validating the thermal-hydraulics design tool as a fluid dynamics solver. Moreover, Fluent has sufficient accuracy as a thermal-hydraulics design tool for the ADS.KEYWORDS: Computational fluid dynamics (CFD)thermal-hydraulicsaccelerator-driven system (ADS)beam windowlead-bismuth eutectic flowDisclaimerAs a service to authors and researchers we are providing this version of an accepted manuscript (AM). Copyediting, typesetting, and review of the resulting proofs will be undertaken on this manuscript before final publication of the Version of Record (VoR). During production and pre-press, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal relate to these versions also. AcknowledgmentsThis research was conducted using the supercomputer HPE SGI8600 at the Japan Atomic Energy Agency. The authors would like to express their gratitude to Mr. Asari (LIFULL Co., Ltd.) for fruitful discussions about the mock-up experiment.NomenclatureTableDisplay TableFigure 1. Conceptual view of LBE-cooled ADS (left) and its BW (right)Display full sizeFigure 2. Schematic diagram of the experimental apparatusDisplay full sizeFigure 3. System of the experimental analysisDisplay full sizeFigure 4. Definitions of jet part and its axes. (a) Free jet part, (b) Impinging jet part. The dotted line indicates the centerline of the jet.Display full sizeFigure 5. Radial distribution of the velocity for the y-direction in the free jet part. (a) numerical simulation and (b) experimentDisplay full sizeFigure 6. Comparison between the simulation and the experiment in the free jet partDisplay full sizeFigure 7. Centerline velocity distribution in impinging jet partDisplay full sizeFigure 8. Comparison between the simulation and the experiment for nondimensional velocity distribution in impinging jet part for several s/D positionsDisplay full sizeFigure 9. Schematic diagram of the pressure measurementDisplay full sizeFigure 10. Pressure fluctuation on the BW. Left: numerical simulation, right: experimentDisplay full sizeFigure 11. Computational system in vertical cross-section C-C’ for JUPITER and FluentDisplay full sizeFigure 12. Computational grid for JUPITER (a) and Fluent (b)Display full sizeFigure 13. Distribution of the volumetric heat source. Left: PHITS, right: fitting functionDisplay full sizeFigure 14. Velocity vector distribution for JUPITER (left) and Fluent (right)Display full sizeFigure 15. Temperature distribution for JUPITER (left) and Fluent (right)Display full sizeFigure 16. Comparison between JUPITER and Fluent results for the spanwise mean velocity profile in the y-direction. Circle: Fluent, solid line: JUPITER. The velocity contour indicates the Fluent result.Display full sizeFigure 17. Comparison between JUPITER and Fluent results for the streamwise mean velocity profile in the y-direction. Circle: Fluent, solid line: JUPITER. The velocity contour indicates the Fluent result.Display full sizeFigure 18. Comparison between JUPITER and Fluent results for the mean temperature profile in the y-direction. Circle: Fluent, solid line: JUPITER. The temperature contour indicates the JUPITER result.Display full sizeFigure 19. Time changes of the temperature distribution by JUPITER for the grid resolution, 388 × 1632 × 2Display full sizeFigure 20. Velocity magnitude and temperature distribution at the jet and bulk boundary in 0.2 m ≤ y ≤ 0.6 mDisplay full sizeFigure 21. Inside and outside surface temperature distribution of the BW for the s-direction in the grid case (a); 184 × 816 × 2Display full sizeFigure 22. Inside and outside surface temperature distribution of the BW for the s-direction in the grid case (b); 388 × 1632 × 2Display full sizeFigure 23. Inside and outside surface temperature distribution of the BW for the s-direction in the grid case (c); 776 × 3264 × 2Display full sizeFigure 24. Counter flow on the BW surface (left) and the local high temperature distribution due to the counter flow (right) in the coarse grid; 184 × 816 × 2Display full sizeReferences Tsujimoto K, Sasa T, Nishihara K et al. Neutronics design for lead-bismuth cooled accelerator-driven system for transmutation of minor actinide. J Nucl Sci Technol. 2004; 41: 21–36. 1 10.1080/18811248.2004.9715454 [Taylor & Francis Online] [Web of Science ®], [Google Scholar] Accelerator-driven Systems (ADS) and Fast Reactors (FR) in Advanced Nuclear Fuel Cycles A Comparative Study. 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For example, if the solution represents a velocity profile, spurious oscillations caused by the numerical method may trigger instability in the simulation. Using a TVD method would ensure that this situation does not occur.3 Weighted Essentially Non-oscillatory (WENO) methods are one of the numerical solutions of differential equations, which is categorized as high-resolution schemes. These schemes’ merit is their ability to achieve high-order accuracy in smooth regions while maintaining stable, non-oscillatory, and sharp discontinuity transitions. Thus, the schemes are suitable for problems containing both strong discontinuities and complex smooth solution features.4 In fact, there are no materials and flow in the vacuum region, but numerical calculations cannot set up a situation where there is nothing. Therefore, only the characteristic that no heat is transferred in the vacuum region was reproduced by giving a very small thermal conductivity, and the properties of T91 were used as assumed values for the other physical properties.
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The Journal of Nuclear Science and Technology (JNST) publishes internationally peer-reviewed papers that contribute to the exchange of research, ideas and developments in the field of nuclear science and technology, to contribute peaceful and sustainable development of the World.
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