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Parametric modeling method for integrated design and manufacturing of radial compressor impeller

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Abstract

Radial compressor impeller (RCI) manufacturing is moving toward to improve competitiveness through smart manufacturing. Although current CAD (computer-aided design) and CAM (computer-aided manufacturing) techniques provide multiple tools to construct and optimize complicated geometries of RCI, an adjustment of blade shape often leads to nonparametric geometric reconstruction. As the key geometric elements in RCI, set of streamlines (SSL) and meridional section (MS) play vital roles in modeling and aerodynamic optimization. This paper presents a novel approach for automatic extraction of SSL and MS from a RCI 3D model or workpiece. Furthermore, the presented method can interactively construct a parameterized RCI platform, which inputs and outputs the presented RCI parameters to existing CFD and CAM systems rapidly and effectively. An integrated acquisition is employed. The straight generatrix vectors (SGVs) are identified and their boundary points are defined. After the uniform partition of SGV segments, the sequent equant points along spanwise direction are packaged to fit SSL. To manipulate the smoothness and approximation, a double-fitting method is performed to generate SSL. A parameterized system for extracting SSL and modeling RCI is developed. The validities of the presented method in different systems are demonstrated. Furthermore, the presented method breaks conventional RCI development procedure and shortens RCI product cycles, which is desirable and significative for integrated RCI design and manufacturing.

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References

  1. Elfert M, Weber A, Wittrock D, Peters A, Voss C, Nicke E (2017) Experimental and numerical verification of an optimization of a fast rotating high performance radial compressor impeller. J Turbomach 139:101007

    Article  Google Scholar 

  2. Li Y, Liang F, Zhou Y, Ding S, Du F, Zhou M, Bi J, Cai Y (2017) Numerical and experimental investigation on thermohydrodynamic performance of turbocharger rotorbearing system. Appl Therm Eng 121:27–38. https://doi.org/10.1016/j.applthermaleng.2017.04.041

    Article  Google Scholar 

  3. Sadagopan A, Camci C (2019) A design strategy for a 6:1 supersonic mixed-flow compressor stage. Aerosp Sci Technol 87:265–277. https://doi.org/10.1016/j.ast.2019.02.026

    Article  Google Scholar 

  4. Xu Z, Ji F, Ding S, Zhao Y, Zhang X, Zhou Y, Zhang Q, Du F (2020) High-altitude performance characteristics and improvement methods of poppet valves 2-stroke aircraft diesel engine. Appl Energy 276:115471. https://doi.org/10.1016/j.apenergy.2020.115471

    Article  Google Scholar 

  5. Ning J, Zhu L (2019) Parametric design and surface topography analysis of turbine blade processing by turn-milling based on CAM. Int J Adv Manuf Technol 104:3977–3990. https://doi.org/10.1007/s00170-019-04037-x

    Article  Google Scholar 

  6. Koini GN, Sarakinos SS, Nikolos IK (2009) A software tool for parametric design of turbomachinery blades. Adv Eng Softw 40(1):41–51. https://doi.org/10.1016/j.advengsoft.2008.03.008

    Article  MATH  Google Scholar 

  7. Shen Y, Huang W, Zhang T, Yan L (2019) Parametric modeling and aerodynamic optimization of EXPERT configuration at hypersonic speeds. Aerosp Sci Technol 84:641–649. https://doi.org/10.1016/j.ast.2018.11.007

    Article  Google Scholar 

  8. Zhou Y, Shao L, Zhang C, Ji F, Li G, Ding S, Zhang Q, Du F (2020) Numerical and experimental investigation on dynamic performance of bump foil journal bearing based on journal orbit. Chin J Aeronaut. https://doi.org/10.1016/j.cja.2019.12.001

  9. Ji Y, Chen S, Zhu W (2020) The effect of pore numbers in the cell walls of soybean oil polyurethane foam on sound absorption performance. Appl Acoust 157:107010. https://doi.org/10.1016/j.apacoust.2019.107010

    Article  Google Scholar 

  10. Abadi SMA, Noori R, Ahmadpour A, Abadi SMNR, Meyer JP (2017) CFD-based shape optimization of steam turbine blade cascade in transonic two phase flows. Appl Therm Eng 112:1575–1589. https://doi.org/10.1016/j.applthermaleng.2016.10.058

    Article  Google Scholar 

  11. Luo J, Liu F (2018) Statistical evaluation of performance impact of manufacturing variability by an adjoint method. Aerosp Sci Technol 77:471–484. https://doi.org/10.1016/j.ast.2018.03.030

    Article  Google Scholar 

  12. Yi W, Ji L, Tian Y, Shao W, Li W (2011) An aerodynamic design and numerical investigation of transonic centrifugal compressor stage. J Therm Sci 20(3):211–217. https://doi.org/10.1007/s11630-011-0460-y

    Article  Google Scholar 

  13. Zhou Y, Xing T, Song Y, Li Y, Zhu X, Li G, Ding S (2020) Digital-twin-driven geometric optimization of centrifugal impeller with free-form blades for five-axis flank milling. J Manuf Syst. https://doi.org/10.1016/j.jmsy.2020.06.019

  14. Atac OF, Yun J, Noh T (2018) Aerodynamic design optimization of a micro radial compressor of a turbocharger. Energies 11. https://doi.org/10.3390/en11071827

  15. Tang X, Luo J, Liu F (2017) Aerodynamic shape optimization of a transonic fan by an adjoint-response surface method. Aerosp Sci Technol 68:26–36. https://doi.org/10.1016/j.ast.2017.05.005

    Article  Google Scholar 

  16. Tung LT, Ozkirimli O, Budak E (2016) Machining strategy development and parameter selection in 5-axis milling based on process simulations. Int J Adv Manuf Technol 85:1483–1500. https://doi.org/10.1007/s00170-015-8001-6

    Article  Google Scholar 

  17. Wang W, Li Q, Jiang Y (2020) A novel 3D surface topography prediction algorithm for complex ruled surface milling and partition process optimization. Int J Adv Manuf Technol 107:3817–3831. https://doi.org/10.1007/s00170-020-05263-4

    Article  Google Scholar 

  18. Li M, Huang J, Liu X, Wang J, Jia L (2018) Research on surface morphology of the ruled surface in five-axis flank milling. Int J Adv Manuf Technol 94:1655–1664. https://doi.org/10.1007/s00170-016-9849-9

    Article  Google Scholar 

  19. Li M, Liu X, Jia D, Liang Q (2015) Interpolation using non-uniform rational B-spline for the smooth milling of ruled-surface impeller blades. Proc Inst Mech Eng B J Eng Manuf 229(7):1118–1130. https://doi.org/10.1177/0954405415586966

    Article  Google Scholar 

  20. Zhang X, Zhu L, Ding H, Xiong Y (2012) Kinematic generation of ruled surface based on rational motion of point-line. Sci China Technol Sci 55(1):62–71. https://doi.org/10.1007/s11431-011-4609-4

    Article  MATH  Google Scholar 

  21. Wang CCL, Elber G (2014) Multi-dimensional dynamic programming in ruled surface fitting. Comput Aided Des 51(6):39–49. https://doi.org/10.1016/j.cad.2014.02.004

    Article  Google Scholar 

  22. Prez-Arribas F, Trejo-Vargas I (2012) Computer-aided design of horizontal axis turbine blades. Renew Energy 44:252–260. https://doi.org/10.1016/j.renene.2012.01.100

    Article  Google Scholar 

  23. Bagci E (2009) Reverse engineering applications for recovery of broken or worn parts and re-manufacturing: three case studies. Adv Eng Softw 40(6):407–418. https://doi.org/10.1016/j.advengsoft.2008.07.003

    Article  MATH  Google Scholar 

  24. Lin K, Huang C, Lai J, Tsai Y, Ueng W (2012) Automatic reconstruction of B-spline surfaces with constrained boundaries. Comput Ind Eng 62(1):226–244. https://doi.org/10.1016/j.cie.2011.09.010

    Article  Google Scholar 

  25. Xie W, Zou X, Yang J, Yang J (2012) Iteration and optimization scheme for the reconstruction of 3D surfaces based on non-uniform rational Bsplines. Comput Aided Des 44(11):1127–1140. https://doi.org/10.1016/j.cad.2012.05.004

    Article  Google Scholar 

  26. Jain S, Nigudkar N, Hasan F, Kumar A (2016) An integrated reverse engineering and rapid prototyping approach towards reconstruction of damaged impeller. Int J Ind Syst Eng 23:393–404. https://doi.org/10.1504/ijise.2016.077690

    Article  Google Scholar 

  27. Xu Y, Tan L, Cao S, Qu W (2017) Multiparameter and multiobjective optimization design of centrifugal pump based on orthogonal method. Proc Inst Mech Eng 231(14):2569–2579. https://doi.org/10.1177/0954406216640303

    Article  Google Scholar 

  28. Li X, Liu Z, Lin Y (2017) Multipoint and multiobjective optimization of a centrifugal compressor impeller based on genetic algorithm. Math Probl Eng 2017(1):1–18. https://doi.org/10.1155/2017/6263274

    Article  Google Scholar 

  29. Xia Z, Luo J, Li F (2019) Performance impact of flow and geometric variations for a turbine blade using an adaptive NIPC method. Aerosp Sci Technol 90:127–139. https://doi.org/10.1016/j.ast.2019.04.025

    Article  Google Scholar 

  30. Li Z, Zhang Y, Pan T, Lu H, Wu M, Zhang J (2018) Optimization strategy for a single-stage axisymmetric hub endwall in axial compressor by a modified transonic area rule. Aerosp Sci Technol 82-83:199–209. https://doi.org/10.1016/j.ast.2018.08.039

    Article  Google Scholar 

  31. Zhou Y, Wang H, Du F, Ding S (2014) Algorithm to construct line-shaped feature point clouds of single value ruled blades for gas turbines. J Manuf Sci Eng 136:041022. https://doi.org/10.1115/1.4027719

    Article  Google Scholar 

  32. Hsu M, Wang C, Herrema AJ, Schillinger D, Ghoshal A, Bazilevs Y (2015) An interactive geometry modeling and parametric design platform for isogeometric analysis. Comput Math Appl 70(71):1481–1500. https://doi.org/10.1016/j.camwa.2015.04.002

    Article  MathSciNet  MATH  Google Scholar 

  33. Yu L, Zhong L, Wang Y (2017) Shape optimization of generic rotary tool for five-axis flank milling. Int J Adv Manuf Technol 93:2921–2931. https://doi.org/10.1007/s00170-017-0750-y

    Article  Google Scholar 

  34. Hehn A, Mosdzien M, Grates D, Jeschke P (2018) Aerodynamic optimization of a transonic centrifugal compressor by using arbitrary blade surfaces. ASME Turbo Expo Turbomach Tech Conf Expos 140. https://doi.org/10.1115/GT2017-63470

  35. Chehouri A, Younes R, Ilinca A, Perron J (2015) Review of performance optimization techniques applied to wind turbines. Appl Energy 142(4):361–388. https://doi.org/10.1016/j.apenergy.2014.12.043

    Article  Google Scholar 

  36. Danilishin AM, Kozhukhov YV, Yun VK (2015) Multiobjective optimization for impeller shroud contour, the width of vane diffuser and the number of blades of the centrifugal compressor stage based on the CFD calculation. IOP Conf Ser Mater Sci Eng 90(1):012046. https://doi.org/10.1088/1757-899X/90/1/012046

    Article  Google Scholar 

  37. Lu Y, Bi Q, Zhu L (2016) Five-axis flank milling of impellers: optimal geometry of a conical tool considering stiffness and geometric constraints. Proc Inst Mech Eng B J Eng Manuf 230(1):38–52. https://doi.org/10.1177/0954405414553979

    Article  Google Scholar 

  38. Fan H, Xi G, Wang W, Cao Y (2016) An efficient five-axis machining method of centrifugal impeller based on regional milling. Int J Adv Manuf Technol 87:789–799. https://doi.org/10.1007/s00170-016-8467-x

    Article  Google Scholar 

  39. Lin AC, Chang H (2011) Automatic 3D measuring system for optical scanning of axial fan blades. Int J Adv Manuf Technol 57(5-8):701–717. https://doi.org/10.1007/s00170-011-3329-z

    Article  Google Scholar 

  40. Bus L, Elkadi M, Galligo A (2009) A computational study of ruled surfaces. J Symb Comput 44(3):232–241. https://doi.org/10.1016/j.jsc.2007.04.005

    Article  MathSciNet  MATH  Google Scholar 

  41. Bi Q, Zhu L, Wang Y, Ding H (2010) Analytical envelope surface representation of a conical cutter undergoing rational motion. Int J Adv Manuf Technol 47(5-8):719–730. https://doi.org/10.1007/s00170-009-2218-1

    Article  Google Scholar 

  42. Fan H, Wang W, Xi G (2013) A novel five-axis rough machining method for efficient manufacturing of centrifugal impeller with free-form blades. Int J Adv Manuf Technol 68:1219–1229. https://doi.org/10.1007/s00170-013-4913-1

    Article  Google Scholar 

  43. Francesc A, Jos Jaime N (2015) Reconstructions that combine interpolation with least squares fitting. Appl Numer Math 97:30–41. https://doi.org/10.1016/j.apnum.2015.06.005

    Article  MathSciNet  MATH  Google Scholar 

  44. Wang M, Sun Y (2014) Error prediction and compensation based on interference-free tool paths in blade milling. Int J Adv Manuf Technol 71(5-8):1309–1318. https://doi.org/10.1007/s00170-013-5535-3

    Article  Google Scholar 

  45. Perez-Arribas F, Castaneda-Sabadell I (2016) Automatic modelling of airfoil data points. Aerosp Sci Technol 55:449–457. https://doi.org/10.1016/j.ast.2016.06.016

    Article  Google Scholar 

  46. Wang S, Ye Z, Chen Z (2010) Design of three-order cubic non-uniform B-spline curve with multi-parameters. Int Conf Signal Process Syst. https://doi.org/10.1109/ICSPS.2010.5555550

  47. Wu J, Wen B, Zhou Y, Zhang Q, Ding S, Du F, Zhang S (2020) Eddy current sensor system for blade tip clearance measurement based on a speed adjustment model. Mech Syst Signal Process 139:106626. https://doi.org/10.1016/j.ymssp.2020.106626

    Article  Google Scholar 

  48. Ji F, Bao Y, Zhou Y, Du F, Zhu H, Zhao S, Li G, Zhu X, Ding S (2019) Investigation on performance and implementation of Tesla turbine in engine waste heat recovery. Energy Convers Manag 179:326–338. https://doi.org/10.1016/j.enconman.2018.10.071

    Article  Google Scholar 

  49. Xu L, Li Y, Ma S, Lee C (2015) A tool path generation method for freeform surface machining by introducing the tensor property of machining strip width. Comput Aided Des 66:1–13. https://doi.org/10.1016/j.cad.2015.03.003

    Article  Google Scholar 

  50. Li Z, Niu J, Wang X, Zhu L (2015) Mechanistic modeling of five-axis machining with a general end mill considering cutter runout. Int J Mach Tools Manuf 96(9):67–79. https://doi.org/10.1016/j.ijmachtools.2015.06.006

    Article  Google Scholar 

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Funding

This work was supported by the Basic Research Program of the National Natural Science Foundation of China (Grant Nos. 51775025 and 51775013) and China Key Research and Development plan (NO.2018YFB0104100).

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Authors and Affiliations

  1. School of Transportation Science and Engineering, Beihang University, Beijing, 100191, China

    Yu Zhou, Tong Xing, Yan Wang & Qi Zhang

  2. Aircraft/Engine Integrated System Safety Beijing Key Laboratory, Beihang University, Beijing, 100191, China

    Yu Zhou, Yue Song, Qi Zhang, Longtao Shao, Farong Du & Shuiting Ding

  3. School of Energy and Power Engineering, Beihang University, Beijing, 100191, China

    Yue Song, Longtao Shao, Farong Du & Shuiting Ding

Authors
  1. Yu Zhou
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  2. Yue Song
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  3. Tong Xing
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  4. Yan Wang
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  5. Qi Zhang
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  7. Farong Du
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  8. Shuiting Ding
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Contributions

Yu Zhou: conceptualization, methodology, software, validation, formal analysis, investigation, resources, data curation, writing - original draft, writing - review and editing.

Yue Song: software, validation, formal analysis, investigation, writing - review and editing, visualization.

Tong Xing: conceptualization, methodology, validation, investigation, resources, writing - review and editing.

Yan Wang: methodology, validation, investigation, resources, writing - original draft, writing - review and editing, visualization, supervision.

Qi Zhang: software, data curation, visualization.

Longtao Shao: software, data curation, visualization.

Farong Du: validation, formal analysis, resources, supervision, project administration.

Shuiting Ding: supervision, project administration, funding acquisition.

Corresponding author

Correspondence to Yan Wang.

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Zhou, Y., Song, Y., Xing, T. et al. Parametric modeling method for integrated design and manufacturing of radial compressor impeller. Int J Adv Manuf Technol 112, 1007–1021 (2021). https://doi.org/10.1007/s00170-020-06331-5

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