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A comparative study of different radial basis function interpolation algorithms in the reconstruction and path planning of γ radiation fields

  • Yulong Zhang (School of Nuclear Science and Technology, University of South China) ;
  • Jinjia Cao (School of Nuclear Science and Technology, University of South China) ;
  • Biao Zhang (School of Nuclear Science and Technology, University of South China) ;
  • Xiaochang Zheng (School of Nuclear Science and Technology, University of South China) ;
  • Wei Chen (School of Nuclear Science and Technology, University of South China)
  • Received : 2023.04.26
  • Accepted : 2024.02.22
  • Published : 2024.07.25

Abstract

Accurate reconstruction of radiation field and path planning are very important for the safety of operators in the process of dismantling nuclear facilities. Based on radial basis function (RBF) interpolation algorithm, this paper discussed the application of inverse multiquadric radial basis Function (IMRBF) interpolation method to the reconstruction of gamma radiation field, and proved the feasibility of reconstructing a radiation field with multiple γ sources. The average relative errors of IMRBF interpolation results were 4.28% and 8.76%, respectively, for the experimental scenarios with single and double gamma sources. After comparing the consistency between the simulated scene and the experimental scene, IMRBF method and Cubic Spline method were respectively used to reconstruct the gamma radiation field by Geant4 simulation data. The results showed that the interpolation accuracy of IMRBF method was superior to that of Cubic Spline method. Further, more RBF interpolation algorithms were used to reconstruct the multi-γ source radiation field, and then the Probabilistic Roadmap (PRM) algorithm was used to optimize the human walking path in the radiation field reconstructed by different interpolation methods. The optimal paths in radiation fields generated by multiple interpolation methods were compared. The results herein contribute to a comprehensive understanding of RBF interpolation methods in reconstructing γ radiation fields and their application in optimizing paths in radiation environments. The insights may provide valuable information for decision-making in radiation protection during the decommissioning of nuclear facilities.

Keywords

Acknowledgement

This research was funded by ITER Project of Ministry of Science and Technology (2022YFE03080002), the Key Laboratory of Magnetic Confinement Nuclear Fusion Research in Hengyang (Grant No. 2018KJ108), the Hunan Nuclear Fusion International Science and Technology Innovation Cooperation Base (Grant No. 2018WK4009), and Key Fund Project of Hunan Provincial Department of Education (20A417).

References

  1. Z.Y. Wang, W.Q. Huang, et al., Application status of interpolation algorithm in radiation field reconstruction, Ordnance Automation 41 (7) (2022) 29-35, https://doi.org/10.7690/bgzdh.2022.07.008. 
  2. D. Shepard, A two-dimensional interpolation function for irregularly-spaced data, in: Proceedings of the 1968 23rd ACM National Conference, 1968, pp. 517-524, https://doi.org/10.1145/800186.810616, 1968. 
  3. P. Monestiez, L. Dubroca, E. Bonnin, et al., Geostatistical modelling of spatial distribution of Balaenoptera physalus in the Northwestern Mediterranean Sea from sparse count data and heterogeneous observation efforts, Ecol. Model. 193 (3-4) (2006) 615-628, https://doi.org/10.1016/j.ecolmodel.2005.08.042. 
  4. M. Buhmann, Radial basis functions, Acta Numer. 9 (2000) 1-38, https://doi.org/10.1017/S0962492900000015. 
  5. G. Chai, et al., An inverse distance weighting spatial interpolation algorithm with second order accuracy, Chin. J. Comput. Phys. 37 (4) (2020) 393-402, https://doi.org/10.19596/j.cnki.1001-246x.8074. 
  6. Lu George Y, Wong David W, An adaptive inverse-distance weighting spatial interpolation technique, Comput. Geosci. 34 (9) (2008) 1044-1055, https://doi.org/10.1016/j.cageo.2007.07.010. 
  7. X. Yu, Y. Wu, L. He, Improvement and comparison of inverse range-weighted meshing interpolation algorithms, Chin. J. Eng. Geophys. 10 (6) (2013) 900-904, https://doi.org/10.3969/j.issn.1672-7940.2013.06.027. 
  8. J.H. Gu, P. Xu, Y. Dong, et al., Research on adaptive VIRE indoor location algorithm based on Kriging interpolation, Computer Engineering and Applications 54 (12) (2018) 100-104, https://doi.org/10.3778/j.issn.1002-8331.1709-0242. 
  9. S. Lee, G. Wolberg, Shin S Y. Scattered data interpolation with multilevel B-splines, IEEE Trans. Visual. Comput. Graph. 3 (3) (1997) 228-244, https://doi.org/10.1109/2945.620490. 
  10. H. Li, Y. Zhao, et al., Research on interpolation reconstruction and visualization of radiation dose field based on Kriging theory, RADIATION PROTECTION 39 (6) (2019) 475-482. http://journal01.magtech.org.cn/Jwk3_fsfh/CN/Y2019/V39/I6/475. 
  11. H. Li, Y. Zhao, Q. Cao, L. He, J. Li, L. Liu, γ-radiation field reconstruction method based on source activity inversion calculations, Journal of Tsinghua University (Sci. & Technol.) 10 (2020) 880-886, https://doi.org/10.16511/j.cnki.qhdxxb.2020.25.014. 
  12. H. Wang, Selection of shape parameters in radial basis function interpolation, Adv. Appl. Math. 9 (9) (2020) 1444-1455, https://doi.org/10.12677/AAM.2020.99170. 
  13. W. Wang, J. Zhou, et al., Research on three-dimensional modeling of strata block based on radial basis function, Rock Soil Mech. 33 (3) (2012) 939-944, https://doi.org/10.16285/j.rsm.2012.03.041. 
  14. A.M. Grigoryev, O.L. Tashlykov, Route optimization during works in nonstationary radiation fields with obstacles, AIP Conf. Proc. 2174 (1) (2019) 020216, https://doi.org/10.1063/1.5134367. 
  15. A.M. Grigoryev, O.L. Tashlykov, et al., Determination of radiation field parameters for the problems of routing optimization based on interpolation with radial basis functions, AIP Conf. Proc. 2313 (2020) 020007, https://doi.org/10.1063/5.0032248. 
  16. O.L. Tashlykov, et al., Reducing the exposure dose by optimizing the route of personnel movement when visiting specified points and taking into account the avoidance of obstacles, Energies 15 (21) (2022) 8222, https://doi.org/10.3390/en15218222. 
  17. O.L. Tashlykov, A.N. Sesekin, A.G. Chentsov, et al., Development of methods for route optimization of work in inhomogeneous radiation fields to minimize the dose load of personnel, Energies 15 (13) (2022) 4788, https://doi.org/10.3390/en15134788. 
  18. X. Sai, Y. Chen, et al., Preliminary application of Multiquadric scattered data interpolation technique in gamma radiation field visualization, Nucl. Technol. 39 (2016) 100501, https://doi.org/10.11889/j.0253-3219.2016.hjs.39.100501. 
  19. R.G. Regis, C.A. Shoemaker, Improved Strategies for radial basis function methods for Global optimization, J. Global Optim. 37 (2007) 113-135, https://doi.org/10.1007/s10898-006-9040-1. 
  20. R.L. Hardy, Multiquadric equations of topography and other irregular surfaces, Journal of geophysical research 76 (8) (1971) 1905-1915, https://doi.org/10.1029/JB076i008p01905. 
  21. J. Allison, K. Amako, et al., Geant4 developments and applications, IEEE Trans. Nucl. Sci. 53 (1) (2006) 270-278, https://doi.org/10.1109/TNS.2006.869826. 
  22. M.K. Li, Y.K. Liu, M.J. Peng, et al., A fast simulation method for radiation maps using interpolation in a virtual environment, J. Radiol. Prot. 38 (3) (2018) 892-907, https://doi.org/10.1088/1361-6498/aac392. 
  23. A.M. Grigoryev, O.L. Tashlykov, Solving a routing optimization of works in radiation fields with using a supercomputer, AIP Conf. Proc. (2018) 020028, https://doi.org/10.1063/1.5055101, 2015. 
  24. L.E. Kavraki, P. Svestka, J.C. Latombe, M.H. Overmars, Probabilistic roadmaps for path planning in high-dimensional configuration spaces, IEEE Trans. Robot. Autom. 12 (4) (1996) 566-580, https://doi.org/10.1109/70.508439. 
  25. E.W. Dijkstra, A Note on two problems in connexion with graphs, in: Edsger Wybe Dijkstra: His Life, Work, and Legacy, 2022, pp. 287-290, https://doi.org/10.1145/3544585.3544600. 
  26. P.E. Hart, N.J. Nilsson, B. Raphael, A formal basis for the heuristic determination of minimum cost paths, IEEE Trans. Syst. Sci. Cybern. 4 (2) (1968), 100-107.10.1109/TSSC.1968.300136. 
  27. A.G. Chentsov, A.N. Sesekin, et al., On one modification of traveling salesman problem oriented on application in atomic engineering, in: AIP Conference Proceedings, vol. 1293, American Institute of Physics, 2010, pp. 197-202, https://doi.org/10.1063/1.3515586, 1. 
  28. A.N. Sesekin, O.L. Tashlykov, S.Y. Shcheklein, A.G. Chentsov, Route optimization in the removal of radiation hazards, WIT Trans. Ecol. Environ. 190 (2014) 919-926, https://doi.org/10.2495/EQ140862.