Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
권호 표지
DOI QR코드

DOI QR Code

Simulation analysis and evaluation of decontamination effect of different abrasive jet process parameters on radioactively contaminated metal

  • Lin Zhong (School of Nuclear Science and Technology, University of South China) ;
  • Jian Deng (School of Nuclear Science and Technology, University of South China) ;
  • Zhe-wen Zuo (School of Mechanical Engineering, University of South China) ;
  • Can-yu Huang (School of Mechanical Engineering, University of South China) ;
  • Bo Chen (Zoomlion Heavy Industry Science and Technology Co., Ltd.) ;
  • Lin Lei (School of Resource Environment and Safety Engineering, University of South China) ;
  • Ze-yong Lei (School of Nuclear Science and Technology, University of South China) ;
  • Jie-heng Lei (School of Electrical Engineering, University of South China) ;
  • Mu Zhao (China Nuclear Industry 24 Construction Co., Ltd.) ;
  • Yun-fei Hua (Hunan Nuclear Industry Honghua Machinery Co., Ltd.)
  • Received : 2022.12.29
  • Accepted : 2023.07.06
  • Published : 2023.11.25
Download PDF
⟨ Previous Next ⟩

Abstract

A new method of numerical simulating prediction and decontamination effect evaluation for abrasive jet decontamination to radioactively contaminated metal is proposed. Based on the Computational Fluid Dynamics and Discrete Element Model (CFD-DEM) coupled simulation model, the motion patterns and distribution of abrasives can be predicted, and the decontamination effect can be evaluated by image processing and recognition technology. The impact of three key parameters (impact distance, inlet pressure, abrasive mass flow rate) on the decontamination effect is revealed. Moreover, here are experiments of reliability verification to decontamination effect and numerical simulation methods that has been conducted. The results show that: 60Co and other homogeneous solid solution radioactive pollutants can be removed by abrasive jet, and the average removal rate of Co exceeds 80%. It is reliable for the proposed numerical simulation and evaluation method because of the well goodness of fit between predicted value and actual values: The predicted values and actual values of the abrasive distribution diameter are Ф57 and Ф55; the total coverage rate is 26.42% and 23.50%; the average impact velocity is 81.73 m/s and 78.00 m/s. Further analysis shows that the impact distance has a significant impact on the distribution of abrasive particles on the target surface, the coverage rate of the core area increases at first, and then decreases with the increase of the impact distance of the nozzle, which reach a maximum of 14.44% at 300 mm. It is recommended to set the impact distance around 300 mm, because at this time the core area coverage of the abrasive is the largest and the impact velocity is stable at the highest speed of 81.94 m/s. The impact of the nozzle inlet pressure on the decontamination effect mainly affects the impact kinetic energy of the abrasive and has little impact on the distribution. The greater the inlet pressure, the greater the impact kinetic energy, and the stronger the decontamination ability of the abrasive. But in return, the energy consumption is higher, too. For the decontamination of radioactively contaminated metals, it is recommended to set the inlet pressure of the nozzle at around 0.6 MPa. Because most of the Co elements can be removed under this pressure. Increasing the mass and flow of abrasives appropriately can enhance the decontamination effectiveness. The total mass of abrasives per unit decontamination area is suggested to be 50 g because the core area coverage rate of the abrasive is relatively large under this condition; and the nozzle wear extent is acceptable.

Keywords

Acknowledgement

This research was supported by the National Key Research and Development Program of China (No. 2019YFC1907704).

References

  1. C. Ramesh, N. Murugesan, V. Ganesan, N. Sivai Bharasi, M.G. Pujar, U. Kamachi Mudali, Studies on dissolution behavior of the surface layer of sodium-exposed SS 316LN in decontaminating formulation using PEMHS, Nucl. Technol. 197 (2017) 99-109, https://doi.org/10.13182/NT15-141. 
  2. W. Zhao, J. Cao, S. Wang, X. Wen, Y. Zhang, R. Ding, J. Peng, Study on laser decontamination technology for metal scraps with radioactively contaminated surfaces, Hedongli Gongcheng/Nuclear Power Eng. 42 (2021) 250-255, https://doi.org/10.13832/j.jnpe.2021.05.0250. 
  3. D. Gurau, R. Deju, The use of chemical gel for decontamination during decommissioning of nuclear facilities, Radiat. Phys. Chem. 106 (2015) 371-375, https://doi.org/10.1016/j.radphyschem.2014.08.022. 
  4. J. Holecek, P. Otahal, Non-destructive decontamination of building materials, Radiat. Phys. Chem. 116 (2015) 393-396, https://doi.org/10.1016/j.radphyschem.2015.03.005. 
  5. A.J. Potiens, J.C. Dellamano, R. Vicente, M.P. Raele, N.U. Wetter, E. Landulfo, Laser decontamination of the radioactive lightning rods, Radiat. Phys. Chem. 95 (2014) 188-190, https://doi.org/10.1016/j.radphyschem.2013.03.043. 
  6. L. Zhong, J. Lei, J. Deng, Z. Lei, L. Lei, X. Xu, Existing and potential decontamination methods for radioactively contaminated metals-A Review, Prog. Nucl. Energy 139 (2021) 103854, https://doi.org/10.1016/j.pnucene.2021.103854. 
  7. L. Li, Z. Gu, W. Xu, Y. Tan, X. Fan, D. Tan, Mixing mass transfer mechanism and dynamic control of gas-liquid-solid multiphase flow based on VOF-DEM coupled, Energy 272 (2023) 127015, https://doi.org/10.1016/j.energy.2023.127015. 
  8. L. Li, W. Xu, Y. Tan, Y. Yang, J. Yang, D. Tan, Fluid-induced vibration evolution mechanism of multiphase free sink vortex and the multi-source vibration sensing method, Mech. Syst. Signal Process. 189 (2023) 110058, https://doi.org/10.1016/j.ymssp.2022.110058. 
  9. S. Pradhan, S.R. Das, P.C. Jena, D. Dhupal, Machining performance evaluation under recently developed sustainable HAJM process of zirconia ceramic using hot SiC abrasives: an experimental and simulation approach, Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci. 236 (2022) 1009-1035, https://doi.org/10.1177/09544062211010199. 
  10. S. Pradhan, D. Dhupal, S.R. Das, P.C. Jena, Experimental investigation and optimization on machined surface of Si3N4ceramic using hot SiC abrasive in HAJM, Mater. Today Proc. 44 (2021) 1877-1887, https://doi.org/10.1016/j.matpr.2020.12.066. 
  11. S. Pradhan, S.R. Das, B.K. Nanda, P.C. Jena, D. Dhupal, Experimental investigation on machining of hardstone quartz with modified AJM using hot silicon carbide abrasives, J. Brazilian Soc. Mech. Sci. Eng. 42 (2020), https://doi.org/10.1007/s40430-020-02644-4. 
  12. Q. Lin, H. Liu, C. Zhu, R.G. Parker, Investigation on the effect of shot peening coverage on the surface integrity, Appl. Surf. Sci. 489 (2019) 66-72, https://doi.org/10.1016/j.apsusc.2019.05.281. 
  13. Q. Lin, P. Wei, H. Liu, J. Zhu, C. Zhu, J. Wu, A CFD-FEM numerical study on shot peening, Int. J. Mech. Sci. 223 (2022) 107259, https://doi.org/10.1016/j.ijmecsci.2022.107259. 
  14. V.B. Nguyen, H.J. Poh, Y.W. Zhang, Predicting shot peening coverage using multiphase computational fluid dynamics simulations, Powder Technol. 256 (2014) 100-112, https://doi.org/10.1016/j.powtec.2014.01.097. 
  15. M. Jebahi, A. Gakwaya, J. Levesque, O. Mechri, K. Ba, Robust methodology to simulate real shot peening process using discrete-continuum coupled method, Int. J. Mech. Sci. 107 (2016) 21-33, https://doi.org/10.1016/j.ijmecsci.2016.01.005. 
  16. M. Ebrahimi, M. Crapper, CFD-DEM simulation of turbulence modulation in horizontal pneumatic conveying, Particuology 31 (2017) 15-24, https://doi.org/10.1016/j.partic.2016.05.012. 
  17. L. Chen, X. Yang, G. Li, J. Yang, C. Wen, X. Li, C. Snape, Dynamic modelling of fluidisation in gas-solid bubbling fluidised beds, Powder Technol. 322 (2017) 461-470, https://doi.org/10.1016/j.powtec.2017.09.039. 
  18. S. Wang, H. Li, R. Wang, X. Wang, R. Tian, Q. Sun, Effect of the inlet angle on the performance of a cyclone separator using CFD-DEM, Adv. Powder Technol. 30 (2019) 227-239, https://doi.org/10.1016/j.apt.2018.10.027. 
  19. D. Zhou, X. Ma, Y. Du, F. Zhang, Y. Chen, H. Wang, Study on EDEM-Fluent Coupled Simulation of Nozzle Structure Parameters in Sandblasting Process, vol. 51, 2022, pp. 192-201, https://doi.org/10.16490/j.cnki.issn.1001-3660.2022.01.020. 
  20. X. Liu, J. Gu, G. Qi, L. Yang, A. Li, Optimization of shot peening process parameters based on CFD-DEM simulation, Surf. Technol. (1) (2018) 8-15, https://doi.org/10.16490/j.cnki.issn.1001-3660.2018.01.002. 
  21. J. Chen, Y. Wang, X. Li, R. He, S. Han, Y. Chen, Erosion prediction of liquid-particle two-phase flow in pipeline elbows via CFD-DEM coupled method, Powder Technol. 275 (2015) 182-187, https://doi.org/10.1016/j.powtec.2014.12.057. 
  22. Y. Liu, J. Zhang, J. Wei, X. Liu, Optimum structure of a laval nozzle for an abrasive air jet based on nozzle pressure ratio, Powder Technol. 364 (2020) 343-362, https://doi.org/10.1016/j.powtec.2020.01.086. 
  23. J.F. Archard, Contact and rubbing of flat surfaces, J. Appl. Phys. 24 (1953) 981-988, https://doi.org/10.1063/1.1721448. 
  24. S. Huang, Z. Tang, J. Huang, C. Ou, Z. Hui, Investigation of influencing factors of wear in a sandblasting machine by CFD-DEM coupled, Part. Sci. Technol. 40 (2022) 838-847, https://doi.org/10.1080/02726351.2021.2018531. 
  25. G. Chen, D.L. Schott, G. Lodewijks, Sensitivity analysis of DEM prediction for sliding wear by single iron ore particle, Eng. Comput. (Swansea, Wales) 34 (2017) 2031-2053, https://doi.org/10.1108/EC-07-2016-0265. 
  26. W. Fuchao, Research on wear evaluation method of bulk transfer system using DEM simulation. https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CMFD201802&filename=1017300936.nh, 2015. 
  27. Y. Wang, J. Tan, X. Cai, D. Ren, X. Ma, Numerical simulation of subsonic and transonic viscous flow around airfoil using meshless method coupled with RNGk-ε turbulent model, Acta Aeronautica Astronautica Sinica 36 (2016) 1411-1421, https://doi.org/10.7527/S1000-6893.2014.0120. 
  28. V. Yakhot, S.A. Orszag, Renormalization group analysis of turbulence. I. Basic theory, J. Sci. Comput. 1 (1986) 3-51, https://doi.org/10.1007/BF01061452. 
  29. S.A. Morsi, A.J. Alexander, An investigation of particle trajectories in two-phase flow systems, J. Fluid Mech. 55 (1972) 193-208, https://doi.org/10.1017/S0022112072001806. 
  30. L. Pan, Q. Wang, Z. He, Practical Multinomial Flow Numerical Simulation-ANSYS Fluent Multinomial Flow Model and its Engineering Application, China Science Publishing & Media Ltd., Beijing, 2020. 
  31. W. Zhang, Study on the Acceleration Dynamics of Abrasive in Premixed Abrasive Water Jet, Chongqing University, 2017. https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CDFDLAST2018&filename=1018701998.nh. 
  32. W. Zuo, Abrasive Accelerated Mechanisms and Distribution Law in Pre-mixed Abrasive Jet, Chongqing University, 2012. 
  33. M. Ebrahimi, M. Crapper, J.Y. Ooi, Experimental and simulation studies of dilute horizontal pneumatic conveying, Part. Sci. Technol. 32 (2014) 206-213, https://doi.org/10.1080/02726351.2013.851133. 
  34. ANSYS Inc, Ansys Fluent Theory Guide, ANSYS Inc., USA, 2020. 
  35. B. Oesterle, T. Bui Dinh, Experiments on the lift of a spinning sphere in a range of intermediate Reynolds numbers, Exp. Fluid 25 (1998) 16-22, https://doi.org/10.1007/s003480050203. 
  36. C.B. Solnordal, C.Y. Wong, J. Boulanger, An experimental and numerical analysis of erosion caused by sand pneumatically conveyed through a standard pipe elbow, Wear 336-337 (2015) 43-57, https://doi.org/10.1016/j.wear.2015.04.017. 
  37. Q. Zhang, T. Guo, G. Hong, L. Cao, Numerical prediction of particle trajectories in an erosion experiment, Baozha Yu Chongji/Explosion Shock Waves 41 (2021) 1-8, https://doi.org/10.11883/bzycj-2020-0118. 
  38. L. Zhong, J. Lei, Z. Zuo, J. Tu, J. Deng, Z. Lei, M. Zhao, Y. Hua, Simulation analysis of the decontamination effect of different nozzles abrasive jet based on CFD-DEM, Part. Sci. Technol. (2022), https://doi.org/10.1080/02726351.2022.2158147.