DOI QR코드

DOI QR Code

Target alignment method of inertial confinement fusion facility based on position estimation

  • Lin, Weiheng (Joint Laboratory on High Power Laser and Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Science) ;
  • Zhu, Jianqiang (Joint Laboratory on High Power Laser and Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Science) ;
  • Liu, Zhigang (Joint Laboratory on High Power Laser and Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Science) ;
  • Pang, Xiangyang (Joint Laboratory on High Power Laser and Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Science) ;
  • Zhou, Yang (Joint Laboratory on High Power Laser and Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Science) ;
  • Cui, Wenhui (Joint Laboratory on High Power Laser and Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Science) ;
  • Dong, Ziming (Joint Laboratory on High Power Laser and Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Science)
  • 투고 : 2021.12.27
  • 심사 : 2022.05.02
  • 발행 : 2022.10.25

초록

Target alignment technology is one of the most critical technologies in laser fusion experiments and is an important technology related to the success of laser fusion experiments. In this study, by combining the open-loop and closed-loop errors of the target alignment, the Kalman state observer is used to estimate the position of the target, which improves the observation precision of the target alignment. Then the optimized result is used to guide the alignment of the target. This method can greatly optimize the target alignment error and reduce uncertainty. With the improvement of the target alignment precision, it will greatly improve the reliability and repeatability of the experiments' results, thereby improving the success rate of the experiments.

키워드

과제정보

This work was carried out within the framework of the SG-II-U high-power laser facility, and was supported by the funding: Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA25020201), the National Natural Science Foundation of China (NSFC) (61827816, 11875308, 61675215), Scientific Instrument Developing Project of the Chinese Academy of Sciences (YJKYYQ20180024), and Shanghai Science and Technology Innovation Action Plan Project (19142202600).

참고문헌

  1. B. Mark, et al., Status of NIF laser and high power laser research at LLNL, Proc. SPIE High Power Lasers Fusion Res. IV (2017), 1008403, https://doi.org/10.1117/12.2257571.
  2. M.J. Guardalben, et al., Laser-system model for enhanced operational performance and flexibility on OMEGA EP, High Power Laser Sci. Eng. e8 (2020) 56-70, https://doi.org/10.1017/hpl.2020.6.
  3. J.L. Miquel, et al., Overview of the laser mega joule (LMJ) facility and PETAL Project in France, Rev. Laser Eng. 42 (2) (2020) 131, https://doi.org/10.2184/lsj.42.2_131.
  4. W. Zheng, et al., Laser performance upgrade for precise ICF experiment in SGIII laser facility, Matter Radiat. Extremes 2 (2017) 5, https://doi.org/10.1016/j.mre.2017.07.004.
  5. J.Q. Zhu, et al., Status and development of high-power laser facilities at the NLHPLP, High Power Laser Sci. Eng. 6 (4) (2018) e55, https://doi.org/10.1017/hpl.2018.46.
  6. T. Wang, et al., Development of target fabrication for laser-driven inertial confinement fusion at research center of laser fusion, High Power Laser Sci. Eng. e5 (2017) 28-36, https://doi.org/10.1017/hpl.2017.4.
  7. S.E. Bodner, The path to electrical energy using laser fusion, High Power Laser Sci. Eng. 7 (4) (2019) e63, https://doi.org/10.1017/hpl.2019.51.
  8. Z.X. Zhang, et al., The 1 PW/0.1 Hz laser beamline in SULF facility, High Power Laser Sci. Eng. (2020) e4, https://doi.org/10.1017/hpl.2020.3.
  9. M. Galletti, et al., Ultra-broadband all-OPCPA petawatt facility fully based on LBO, High Power Laser Sci. Eng. (2020) e31, https://doi.org/10.1017/hpl.2020.31.
  10. F. Isono, et al., High-power non-perturbative laser delivery diagnostics at the final focus of 100-TW-class laser pulses, 2021, p. e25, https://doi.org/10.1017/hpl.2021.12.
  11. P.D. Nicola, et al., Beam and target alignment at the national ignition facility using the target alignment sensor (TAS), Proc. SPIE - Int. Soc. Opt. Eng. 8505 (6) (2012) 318-322, https://doi.org/10.1117/12.930173.
  12. D.H. Kalantar, et al., An overview of target and diagnostic alignment at the National Ignition Facility, Proc. SPIE - Int. Soc. Opt. Eng. 8505 (2012), 850509, https://doi.org/10.1117/12.969066, 09.
  13. M. Luttmann, et al., Laser Megajoule alignment to target chamber center, SPIE LASE 7616 (2011), 76160N, https://doi.org/10.1117/12.873561.
  14. L. Ren, et al., Target alignment in the Shen-Guang II Upgrade laser facility, High Power Laser Sci. Eng. 6 (1) (2018) 58-66, https://doi.org/10.1017/hpl.2018.4.
  15. Y. Zhou, et al., Research on the system of nanosecond target aiming and positioning of the SG-II Updated laser facility, Chin. J. Lasers 41 (12) (2014) 163-169, https://doi.org/10.3788/CJL201441.1208002.
  16. H. Yang, et al., Mechanical design and analysis of an indirect-drive cryogenic target, J. Fusion Energy 35 (4) (2016) 673-682, https://doi.org/10.1007/ s10894-016-0091-0.
  17. I.V. Aleksandrova, et al., Advanced fuel layering in line-moving, high-gain direct-drive cryogenic targets, High Power Laser Sci. Eng. 7 (3) (2019) e38, https://doi.org/10.1017/hpl.2019.23.
  18. Z.Y. Jiao, et al., Design and performance of final optics assembly in SG-II Upgrade laser facility, High Power Laser Sci. Eng. 6 (2018) 14-24, https://doi.org/10.1017/hpl.2018.8, 02.
  19. C. Gibson, et al., Design of the NIF cryogenic target system, Fusion Sci. Technol. 55 (3) (2008) 233-236, https://doi.org/10.13182/FST08-3453.
  20. R.G. Brown, P. Hwang, Introduction to Random Signals and Applied Kalman Filtering, John Wiley & Sons Publication, USA, 1997.
  21. B. Feng, et al., Image-based displacement and rotation detection using scale invariant features for 6 degree of freedom ICF target positioning, Appl. Opt. 54 (13) (2015) 76-80, https://doi.org/10.1364/AO.54.004130.
  22. J.P. Mitchell, et al., Sensor fusion of laser trackers for use in large-scale precision metrology, Proc. SPIE - Int. Soc. Opt. Eng. (2004) 5263, https://doi.org/10.1117/12.515021.
  23. W. Liu, et al., Coordinate uncertainty analyses of coupled multiple measurement systems, Meas. Sci. Technol. 21 (6) (2010), 065103, https://doi.org/10.1088/0957-0233/21/6/065103.
  24. E.M. Craparo, et al., Sensor placement in active multistatic sonar networks, Nav. Res. Logist. 64 (4) (2017) 287-304, https://doi.org/10.1002/nav.21877.
  25. L. Wallace, et al., Development of a UAV-LiDAR system with application to forest inventory, Remote Sens. Basel 4 (6) (2012) 1519-1543, https://doi.org/10.3390/rs4061519.
  26. Y.P. Li, et al., Large-scale absolute distance measurement with dual freerunning all-polarization-maintaining femtosecond fiber lasers, Chin. Opt Lett. 17 (2019), 091202, https://doi.org/10.3788/COL201917.091202.
  27. S.Y. Chen, et al., Kalman filter for robot vision: a survey, IEEE Trans. Ind. Electron. 59 (11) (2012) 4409-4420, https://doi.org/10.1109/TIE.2011.2162714.
  28. S.L. Sun, et al., Multi-sensor optimal information fusion Kalman filter- ScienceDirect, Automatica 40 (6) (2004) 1017-1023, https://doi.org/10.1016/j.automatica.2004.01.014.
  29. K. Ansari, et al., Real-time positioning based on Kalman filter and implication of singular spectrum analysis, Geosci. Rem. Sens. Lett. IEEE (99) (2020), https://doi.org/10.1109/LGRS.2020.2964300.
  30. N. Zade, et al., Target tracking based on approximate localization technique in deterministic directional passive sensor network, J. Ambient Intell. Hum. Comput. 11 (2021), https://doi.org/10.1007/s12652-020-02783-5.
  31. J.B. Zhao, et al., A robust iterated extended Kalman filter for power system dynamic state estimation, IEEE Trans. Power Syst. 32 (4) (2017) 3205-3216, https://doi.org/10.1109/TPWRS.2016.2628344.