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Tytuł artykułu

Reverse engineering-inspired parametric 3D geometry model of marine propeller

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this study, an effective parametric 3D geometry model of a propeller was established with the aid of reverse engineering. The goal is to reduce the free parameters while automating the modelling of the propeller. The process of building the parametric model begins by generating an initial point cloud by defining the feature matrix associated with the propeller blade profile shape. Subsequently, the initial point cloud is deformed and refined by the deformation feature matrix and resampling. Finally, a 3D geometry model of the propeller is generated by surface reconstruction. The model can be built automatically by interactively modifying the feature matrices. Two numerical analyses illustrate the performance of the parametric 3D geometry model. Specifically, two propellers are constructed using the proposed model to estimate the shape error between the reconstructed propellers and the original offset of the propellers. These propellers are selected as research objects to determine the hydrodynamic performance error between the propeller constructed by the proposed model and a benchmark propeller. According to the results of the numerical study, the parametric 3D geometry model can precisely reconstruct the aforementioned geometry within a valid error range. The hydrodynamic error analysis demonstrates that the geometric inaccuracy from the reconstructed model has less impact on the propeller performance. This indicates that the model described in this study is generalised and robust. Moreover, some uncommon propeller CAD models were generated in batches using the parametric 3D geometry model.
Rocznik
Tom
Strony
35--47
Opis fizyczny
Bibliogr. 28 poz., rys., tab.
Twórcy
autor
  • School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan, China
  • School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan, China
autor
  • School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan, China
autor
  • School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan, China
Bibliografia
  • 1. P. Król, “Blade section profile array lifting surface design method for marine screw propeller blade,” Polish Maritime Research, vol. 26, no. 4, 3919, pp.134-141, 2019. doi: /10.2478/ pomr-2019-0075.
  • 2. P. Król, “Analysis of model-scale open-water test uncertainty,” Polish Maritime Research, vol. 29, no. 4, 3922, pp. 4-11, 2022. doi: /10.2478/pomr-2022-0039.
  • 3. A. Nadery and H. Ghassemi, “Numerical investigation of the hydrodynamic performance of the propeller behind the ship with and without Wed,” Polish Maritime Research, vol. 27, no. 4, 3920, pp. 50-59, 2020. doi: /10.2478/ pomr-2020-0065.
  • 4. D. S. Greeley, “Numerical method for propeller design and analysis in steady flow,” SNAME Transactions, vol. 90, pp. 415-453, 1982.
  • 5. M. Diez, A. Serani, E. F. Campana, et al., “Design space dimensionality reduction for single-and multi-disciplinary shape optimization,” Proceedings of AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference (MA&O). AVIATION 2016, Washington DC, USA. 13-17 June, 2016. doi: 10.2514/6.2016-4295.
  • 6. I. Marinić-Kragić, D. Vučina, and M. Ćurković, “Efficient shape parameterization method for multidisciplinary global optimization and application to integrated ship hull shape optimization workflow,” Computer-Aided Design, vol. 80, 2016, ISSN 0010-4485. doi: 10.1016/j.cad.2016.08.001.
  • 7. A. Miao, M. Zhao, and D. Wan, “CFD-based multi-objective optimisation of S60 Catamaran considering demihull shape and separation,” Applied Ocean Research, vol. 97, 2020. doi:10.1016/j.apor.2020.102071.
  • 8. A. Serani, F. Stern, E. F. Campana, et al., “Hull-form stochastic optimization via computational-cost reduction methods,” Engineering with Computers, vol. 38 (Suppl. 3), pp. 2245-2269, 2022. doi:10.1007/s00366-021-01375-x.
  • 9. S. Gaggero, “Numerical design of a RIM-driven thruster using a RANS-based optimization approach,” Applied Ocean Research, vol. 94, 101941, 2020. doi:10.1016/j. apor.2019.101941.
  • 10. S. Gaggero, J. Gonzalez-Adalid, and M. P. Sobrino, “Design and analysis of a new generation of CLT propellers,” Applied Ocean Research, vol. 59, pp. 424-450, 2016. doi:10.1016/j. apor.2016.06.014.
  • 11. S. Gaggero, G. Tani, D. Villa, M. Viviani, P. Ausonio, P. Travi, G. Bizzarri, and F. Serra, “Efficient and multiobjective cavitating propeller optimization: An application to a high-speed craft,” Applied Ocean Research, vol. 64, pp. 31-57, 2017. doi:10.1016/j.apor.2017.01.018.
  • 12. S. Gaggero, G. Vernengo, and D. Villa, “A marine propeller design method based on two-fidelity data levels,” Applied Ocean Research, vol. 123, 103156, 2022. doi:10.1016/j. apor.2022.103156.
  • 13. D. Bertetta, S. Brizzolara, S. Gaggero, M. Viviani, and L. Savio, “CPP propeller cavitation and noise optimization at different pitches with panel code and validation by cavitation tunnel measurements,” Ocean Engineering, vol. 53, pp. 177-195, 2012. doi:10.1016/j.oceaneng.2012.06.026.
  • 14. X. Ye, T. R. Jackson, and N. M. Patrikalakis, “Geometric design of functional surfaces,” Computer-Aided Design, vol. 28, no. 9, pp. 741-52, 1996. doi:10.1016/0010-4485(95)00080-1.
  • 15. G. W. Vickers, “Computer-aided manufacture of marine propellers,” Computer-Aided Design, vol. 9, no. 4, pp. 26774, 1977. doi:10.1016/0010-4485(77)90008-2.
  • 16. Y. C. Kim, Y. M. Lee, M. J. Son, T. W. Kim, and J. C. Suh, “Generating cutter paths for marine propellers without interference and gouging,” Journal of Marine Science and Technology, vol. 14, no. 3, pp. 275-84, 2009. doi:10.1007/ s00773-008-0033-2.
  • 17. C. S. Lee and J. H. Lee, “Geometric modeling and tool path generation of model propellers with a single setup change,” The International Journal of Advanced Manufacturing Technology, vol. 50, no. 1, pp. 253-63, 2010. doi:10.1007/ s00170-009-2495-8.
  • 18. F. Pérez-Arribas and R. Pérez-Fernández, “B-spline design model for propeller blades,” Advances in Engineering Software, vol. 118, pp. 35-44, 2018. doi:10.1016/j. advengsoft.2018.01.005.
  • 19. A. Arapakopoulos, R. Polichshuk, Z. Segizbayev, S. Ospanov, A. I. Ginnis, and K. V.Kostas, “Parametric models for marine propellers,” Ocean Engineering, vol. 192, 106595, 2019. doi:10.1016/j.oceaneng.2019.106595.
  • 20. T. Várady, R. R. Martin, and J. Cox, “Reverse engineering of geometric models—an introduction,” Computer-Aided Design, vol. 29, no. 4, pp. 255–268, 1997. doi:10.1016/ s0010-4485(96)00054-1.
  • 21. M. G. Cox, The numerical evaluation of B-splines. Technical report, National Physics Laboratory DNAC 4, 1971. doi:10.1093/imamat/10.2.134.
  • 22. C. De Boor, “On calculation with B-splines,” Journal of Approximation Theory, vol. 6, pp. 50–62, 1972. doi:https:// doi.org/10.1016/0021-9045(72)90080-9.
  • 23. P. Lancaster and K. Salkauskas, “Surfaces generated by moving least squares methods,” Mathematics of Computation, vol. 37, no. 155, pp. 141-158, 1981. doi:10.2307/2007507.
  • 24. Q. H. Zeng and D. T. Lu, “Curve and surface fitting based on moving least-squares methods,” Journal of Engineering Graphics, vol. 25, no. 1, pp. 84-89, 2004. doi:1003-0158(2004)01-0084-06.
  • 25. A. Yazaki, E. Kuramochi, and T. Kumasaki, “Open water test series with modified AU-type four-bladed propeller models,” Journal of Zosen Kiokai, vol. 108, pp. 99-104, 1960.
  • 26. S. Leone, C. Testa, L. Greco, and F. Salvatore, “Computational analysis of self-pitching propellers performance in open water,” Ocean Engineering, vol. 64, pp. 122-134, 2013. doi:https://doi.org/10.1016/j.oceaneng.2013.02.012.
  • 27. W. Zhu and H. Gao, “Hydrodynamic characteristics of bioinspired marine propeller with various blade sections,” Ships and Offshore Structures, 2020. doi:10.1080/1744530 2.2020.1713039.
  • 28. S. Joe and F. Y. Kuo, “Remark on Algorithm 659: Implementing Sobol’s Quasirandom Sequence Generator,” ACM Transactions on Mathematical Software, vol. 29, no. 1, pp. 49–57, 2003. doi:10.1145/42288.214372.
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c3a82db7-0eb2-4db2-8d34-486cf564590b
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