Development of GPU-Paralleled multi-resolution techniques for Lagrangian-based CFD code in nuclear thermal-hydraulics and safety
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In this study, we propose a fully parallelized adaptive particle refinement (APR) algorithm for smoothed particle hydrodynamics (SPH) to construct a stable and efficient multi-resolution computing system for nuclear safety analysis. The APR technique, widely employed by SPH research groups to adjust local particle resolutions, currently operates on a serialized algorithm. However, this serialized approach diminishes the computational efficiency of the system, negating the advantages of acceleration achieved through high-performance computing devices. To address this drawback, we propose a fully parallelized APR algorithm designed to enhance both efficiency and computational accuracy, facilitated by a new adaptive smoothing length model. For model validation, we simulated both hydrostatic and hydrodynamic benchmark cases in 2D and 3D environments. The results demonstrate improved computational efficiency compared to the conventional SPH method and APR with a serialized algorithm, and the model’s accuracy was confirmed, revealing favorable outcomes near the resolution interface. Through the analysis of jet breakup, we verified the performance and accuracy of the model, emphasizing its applicability in practical nuclear safety analysis.
Abstract
In this study, we propose a fully parallelized adaptive particle refinement (APR) algorithm for smoothed particle hydrodynamics (SPH) to construct a stable and efficient multi-resolution computing system for nuclear safety analysis. The APR technique, widely employed by SPH research groups to adjust local particle resolutions, currently operates on a serialized algorithm. However, this serialized approach diminishes the computational efficiency of the system, negating the advantages of acceleration achieved through high-performance computing devices. To address this drawback, we propose a fully parallelized APR algorithm designed to enhance both efficiency and computational accuracy, facilitated by a new adaptive smoothing length model. For model validation, we simulated both hydrostatic and hydrodynamic benchmark cases in 2D and 3D environments. The results demonstrate improved computational efficiency compared to the conventional SPH method and APR with a serialized algorithm, and the model’s accuracy was confirmed, revealing favorable outcomes near the resolution interface. Through the analysis of jet breakup, we verified the performance and accuracy of the model, emphasizing its applicability in practical nuclear safety analysis.
참고문헌 (44)
- T. Hohne, , Sci. Technol. Nucl. Install, 2010 (2010)
- R. Li, , Int. J. Energy Res, 2023, pp.1~13 (2023)
- G. Vijaya Kumar, , Nucl. Eng. Des, 365, pp.110682~ (2020)
- G. Choi, , Int. J. Energy Res., 2023 (2023)
- G. Duan, , Nucl. Eng. Des, 343, pp.218~231 (2019)
- Z. Bin Wang, , Appl. Math. Model, 40, pp.9625~9655 (2016)
- S. H. Park, , Front. Energy Res., 8 (2020)
- Y. B. Jo, , Ann. Nucl. Energy, 124, pp.132~149 (2019)
- Y. Beom Jo, , Nucl. Eng. Des, 405, pp.112228~ (2023)
- H. Y. Choi, , Nucl. Eng. Technol, 53, pp.3264~3274 (2021)
- Y. B. Jo, , Int. J. Multiph. Flow, 153, pp.104125~ (2022)
- Y. B. Jo, , Nucl. Eng. Technol, 53, pp.752~762 (2021)
- D. Valdez-Balderas, , J. Parallel Distrib. Comput, 73, pp.1483~1493 (2013)
- R. Vacondio, , Comput. Part. Mech, 8, pp.575~588 (2021)
- J. Feldman, , Int. J. Numer. Methods Eng, 72, pp.295~324 (2007)
- R. Vacondio, , Adv. Water Resour, 58, pp.10~23 (2013)
- R. Vacondio, , Comput. Methods Appl. Mech. Eng, 300, pp.442~460 (2016)
- R. Vacondio, , Comput. Methods Appl. Mech. Eng, 256, pp.132~148 (2013)
- X. Yang, , Phys. Rev. E, 96 (2017)
- X. Yang, , J. Comput. Phys., 443 (2021)
- W. T. Liu, , Acta Mech. Sin. Xuebao, 34, pp.601~613 (2018)
- D. A. Barcarolo, , J. Comput. Phys, 273, pp.640~657 (2014)
- L. Chiron, , J. Comput. Phys, 354, pp.552~575 (2018)
- H. Cheng, , Ocean Eng (2022)
- L. Hu, , Eng. Anal. Bound. Elem, 118, pp.108~123 (2020)
- A. H´erault, , J. Hydraul. Res, 48, pp.74~79 (2010)
- G. Oger, , Comput. Phys. Commun, 200, pp.1~14 (2016)
- X. Xia, , Environ. Model. Softw, 75, pp.28~43 (2016)
- P. Maruzewski, , SPHERIC Work (2008)
- Q. Xiong, , Comput. Phys. Commun, 184, pp.1701~1707 (2013)
- P. N. Sun, , Int. SPHERIC Work (2019)
- D. W. Holmes, , Adv. Eng. Softw, 42, pp.999~1008 (2011)
- R. A. Gingold, , Mon. Not. R. Astron. Soc, 181, pp.375~389 (1977)
- W. Dehnen, , Mon. Not. R. Astron. Soc, 425, pp.1068~1082 (2012)
- P. W. Cleary, , Appl. Math. Model, 22, pp.981~993 (1998)
- T. Zhuang, , AIP Adv., 10 (2020)
- J. Monaghan, , J. Comput. Phys, 110, pp.399~406 (1994)
- H. V. Dang, , Parallel Comput, 39, pp.737~750 (2013)
- A. Li, , Proc. Int. Conf. Supercomput, pp.109~118 (2015)
- M. Ihmsen, , Comput. Graph. Forum, 30, pp.99~112 (2011)
- M. Ge, , Aircr. Eng. Aerosp. Technol, 94, pp.515~530 (2022)
- U. Ghia, , J. Comput. Phys, 48, pp.387~411 (1982)
- H. Hysing, , Int. J. Numer. Methods Fluids, 60, pp.1259~1288 (2009)
- L. Manickam, , Int. J. Multiph. Flow, 91, pp.262~275 (2017)
