special column

Influence of blade multi-scale surface on aerodynamic performance of compressor and its high-performance manufacturing: A review

  • Dinghua ZHANG ,
  • Zhiwei HE ,
  • Xuebao ZHANG ,
  • Ming LUO
Expand
  • 1.Key Laboratory of High Performance Manufacturing for Aero-engine,Ministry of Industry and Information Technology,Northwestern Polytechnical University,Xi’an  710072,China
    2.Engineering Research Center of Aero-engine Advanced Manufacturing Technology,Ministry of Education,Northwestern Polytechnical University,Xi’an  710072,China
    3.AECC Sichuan Gas Turbine Establishment,Chengdu  610500,China

Received date: 2023-09-22

  Revised date: 2023-10-17

  Accepted date: 2023-12-09

  Online published: 2024-01-15

Supported by

Science Center for Gas Turbine Project (P2023-B-Ⅳ-002-001);National Natural Science Foundation of China(U2241249)

Abstract

Blade geometry error refinement control, surface corrugation control and reasonable arrangement of meso-microscopic bionic drag reduction structure are effective means to improve the aerodynamic performance of aero-engine compressor blades, and is also currently one of the key focuses of thenext generation of aero-engines. These structures usually have complex geometries and are difficult to manufacture. In this paper, we firstly review the changes of different scale surface features, such as blade geometry error, waviness and meso-microscopic bionic drag reduction structure, on the flow field characteristics, as well as the influence of different scale surface structural features on the aerodynamic performance of compressor, and analyze the manufacturing process of multi-scale surfaces and its latest progress. Secondly, the requirements for geometric shape tolerance range, waviness and meso-microscopic bionic structure manufacturing technology in the high-performance manufacturing of compressor blades under aerodynamic performance constraints are introduced. Finally, the research content and development direction for further enhancing the aerodynamic performance of compressor blades are prospected in the light of the current development of high-performance manufacturing of multi-scale surfaces.

Cite this article

Dinghua ZHANG , Zhiwei HE , Xuebao ZHANG , Ming LUO . Influence of blade multi-scale surface on aerodynamic performance of compressor and its high-performance manufacturing: A review[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2024 , 45(13) : 629642 -629642 . DOI: 10.7527/S1000-6893.2023.29642

References

1 温泉, 马宁, 南希. 航空发动机风扇/压气机技术发展趋势[J]. 航空动力2020(2): 42-46.
  WEN Q, MA N, NAN X. Development trend of aero engine fan and compressor technology[J]. Aerospace Power2020(2): 42-46 (in Chinese).
2 CHU W L, JI T Y, Chen X G, et al. Mechanism analysis and uncertainty quantification of blade thickness deviation on rotor performance[J]. Journal of Power and Energy2023237(6): 1188-1202.
3 GUO Z T, CHU W L, ZHANG H G, et al. Aerodynamic evaluation of cascade flow with actual geometric uncertainties using an adaptive sparse arbitrary polynomial chaos expansion[J]. Physics of Fluids202335(3): 036122.
4 ZHANG Q, XU S R, YU X J, et al. Nonlinear uncertainty quantification of the impact of geometric variability on compressor performance using an adjoint method[J]. Chinese Journal of Aeronautics202235(2): 17-21.
5 中国航空工业总公司六二四所. 叶片叶型的标注、公差与叶身表面粗糙度: [S]. 北京: 中国航空工业总公司, 1998.
  Gas Turbine Establishment. Marking, tolerances and surface roughness of the leaf blade: [S]. Beijing: Aviation Industry Corporation of China, 1998 (in Chinese).
6 GREINER D, GALVAN B, PERIAUX J, et al. Advances in evolutionary and deterministic methods for design, optimization and control in engineering and sciences[M]. 2015: 45-86.
7 孙培培, 李雯, 胡文颖. 仿生学在航空发动机领域的应用[J]. 航空动力2018(5): 12-15.
  SUN P P, LI W, HU W Y. Application of bionics in aero engines[J]. Aerospace Power2018(5): 12-15 (in Chinese).
8 ROBERTS W B. Advanced turbofan blade refurbishment technique[J]. Journal of Turbomachinery1995117(4): 666-667.
9 高丽敏, 杨光, 王浩浩, 等. 波纹度偏差对高负荷压气机叶型的影响[J]. 西安交通大学学报202357(3): 117-128.
  GAO L M, YANG G, WANG H H, et al. Effect of waviness deviation on the blade profile of the high-load compressor[J]. Journal of Xi’an Jiaotong University202357(3): 117-128 (in Chinese).
10 ZHANG C, KOIRALA S B. Investigation on drag reduction performance of aero engine blade with micro-texture[J]. Aerospace Science and Technology201872: 380-396.
11 邵文博, 胡博, 李雪松, 等. 加工误差对压气机叶栅气动性能的影响[J]. 装备环境工程202320(1): 22-29.
  SHAO W B, HU B, LI X S, et al. Impact of manufacturing variations on aerodynamic performance of compressor blade[J]. Equipment Environmental Engineering202320(1): 22-29 (in Chinese).
12 程超, 吴宝海, 郑海, 等. 叶片加工误差对压气机性能的影响[J]. 航空学报202041(2): 623237.
  CHENG C, WU B H, ZHENG H, et al. Effect of blade machining errors on compressor performance[J]. Acta Aeronautica et Astronautica Sinica202041(2): 623237 (in Chinese).
13 曾瑞慧, 高丽敏, 杨冠华, 等. 层流叶片在压气机中的应用研究[J]. 工程热物理学报201738(11): 2348-2356.
  ZENG R H, GAO L M, YANG G H, et al. Study on the application of laminar blades in compressors [J]. Journal of Engineering Thermophysics201738(11): 2348-2356 (in Chinese).
14 杨冠华, 高丽敏, 王浩浩, 等. 基于NURBS的扩压叶栅非对称前缘设计[J]. 航空动力学报202136(3): 655-663.
  YANG G H, GAO L M, WANG H H, et al. Asymmetric leading edge design of compressor cascades based on NURBS[J]. Journal of Aeronautical Power202136(3): 655-663 (in Chinese).
15 ELMSTROM M E, MILLSAPS K T, HOBSON G V, et al. Impact of nonuniform leading edge coatings on the aerodynamic performance of compressor airfoils[J]. Journal of Turbomachinery2011133(4): 041004.
16 WHEELER A P, SOFIA A, MILLER R J. The effect of leading-edge geometry on wake interactions in compressors[J]. Journal of Turbomachinery2009131(4): 041013.
17 史国华. 转子叶尖尾缘端削对轴流压气机失速裕度的影响机理[J]. 流体机械202351(5): 70-76.
  SHI G H. Mechanism of the effect of blade tip cutting at the rotor trailing edge on stall margin in an axial compressor[J]. Fluid Machinery202351(5): 70-76 (in Chinese).
18 SCHNELL R, LENGYEL K T, NICKE E. On the impact of geometric variability on fan aerodynamic performance, unsteady blade row interaction, and its mechanical characteristics[J]. Journal of Turbomachinery2014136(9): 091005.
19 REID L, URASEK D C. Experimental evaluation of the effects of a blunt leading edge on the performance of a transonic rotor[J]. Journal of Engineering for Gas Turbines and Power197395(3): 199-204.
20 ROBERTS W B. Axial Compressor performance restoration by blade profile control: 84-GT-232, V001T01A063[R]. Amsterdam: International Gas Turbine Institute, 1984.
21 TUCK E. A criterion for leading-edge separation[J]. Journal of Fluid Mechanics1991222: 33-37.
22 WALRAEVENS R E, CUMPSTY N A. Leading edge separation bubbles on turbomachine blades[J]. Journal of Turbomachinery1995117: 115-125.
23 TAIN L. Compressor leading edges in incompressible and compressible flows[D]. Cambridge: University of Cambridge, 1998: 38-46.
24 LIU H, LIU B, LI L, et al. Effect of leading-edge geometry on separation bubble on a compressor blade: GT2003-38217[R]. Atlanta: ASME, 2003.
25 GIEBMANNS A, SCHNELL R, STEINERT W, et al. Analyzing and optimizing geometrically degraded transonic fan blades by means of 2D and 3D simulations and cascade measurements: GT2012-69064[R]. Copenhagen: ASME, 2012.
26 GIEBMANNS A, BACKHAUS J, FREY C, et al. Compressor leading edge sensitivities and analysis with an adjoint flow solver: GT2013-94427, V06AT35A009[R]. San Antonio: ASME, 2013.
27 GOODHAND M N, MILLER R J, HANG W L. The impact of geometric variation on compressor two-dimensional incidence range[J]. Journal of Turbomachinery2015137(2): 021007.
28 CARTER A D. Blade profiles for axial-flow fans, pumps, compressors, etc[J]. Proceedings of the Institution of Mechanical Engineers1961175(1): 775-806.
29 李萍. 叶片加工误差及数据传递对压气机气动性能的影响[D]. 西安: 西北工业大学, 2015: 27-34
  LI P. Effect of blade machining error and data transfer on compressor aerodynamic performance[D]. Xi’an: Northwestern Polytechnical University, 2015: 27-34 (in Chinese).
30 郑似玉, 滕金芳, 羌晓青. 叶片加工超差对高压压气机性能影响和敏感性分析[J]. 机械工程学报201854(2): 216-224.
  ZHENG S Y, TENG J F, QIANG X Q. Sensitivity analysis of manufacturing variability on high-pressure compressor performance[J]. Journal of Mechanical Engineering201854(2): 216-224 (in Chinese).
31 耿少娟, 张小玉, 丁林超, 等. 转子叶片加工误差对1.5级跨声速压气机气动性能的影响[J]. 推进技术202142(1): 139-148.
  GENG S J, ZHANG X Y, DING L C, et al. Effects of rotor blade manufacturing variability on 1.5 stage transonic compressor aerodynamic performance[J]. Journal of Propulsion Technology202142(1): 139-148 (in Chinese).
32 陈卓远, 耿少娟, 刘帅鹏, 等. 轮廓度误差对超声速压气机叶栅气动性能的影响[J/OL]. 中国舰船研究, (2023-06-15)[2023-12-23]. .
  CHEN Z Y, GENG S J, LIU S P, et al. Effects of profile variability on aerodynamic performance of supersonic compressor cascade [J]. Chinese Journal of Ship Research, (2023-06-15)[2023-12-23]. .
33 LEBELE-ALAWA B T, HART H I, OGAJI S O, et al. Rotor-blades’ profile influence on a gas-turbine’s compressor effectiveness[J]. Applied Energy200885(6): 494-505.
34 郑似玉. 压气机叶片加工公差对气动性能的影响[D]. 上海:上海交通大学, 2019: 23-24.
  ZHENG S Y. Impact of manufacturing tolerance of compressor blade on aerodynamic performance[D]. Shanghai: Shanghai Jiao Tong University, 2019: 23-24 (in Chinese).
35 DIMITRIOS I P, COSTAS P. Aerodynamic shape optimization for minimum robust drag and lift reliability constraint[J]. Aerospace Science and Technology201655(13): 24-33.
36 KLAPPROTH J. Approximate relative total pressure losses of an infinite cascade of supersonic blades with finite leading-edge thickness: NACA-RM-E9L21[R]. 1950.
37 ROBERTS W, ARMIN A, KASSASEYA G, et al. The effect of variable chord length on transonic axial rotor performance[J]. Journal of Turbomachinery2002124(3): 351-357.
38 REITZ G, SCHLANGE S, FRIEDRICHS J. Design of experiments and numerical simulation of deteriorated high pressure compressor airfoils: GT2016-56024, V02AT37A002[R]. Seoul: ASME, 2016.
39 郑似玉, 滕金芳, 羌晓青. 轮廓度加工超差对压气机气动性能影响的数值研究[J]. 科学技术与工程201616(29): 317-320.
  ZHEN S Y, TENG J F, QIANG X Q. Numerical investigation of profile variability on axial compressor flow field performance[J]. Science Technology and Engineering201616(29): 317-320 (in Chinese).
40 郑似玉, 滕金芳, 羌晓青. 位置度超差对轴流压气机流场性能影响的数值研究[J]. 流体机械201644(11): 20-24.
  ZHENG S Y, TENG J F, QIANG X Q. Numerical investigation of positional variability on axial compressor flow field performance[J]. Fluid Machinery201644(11): 20-24 (in Chinese).
41 郑似玉, 滕金芳, 羌晓青. 压气机叶片扭转度加工超差分析与研究[J]. 节能技术201735(2): 99-102, 112.
  ZHENG S Y, TENG J F, QIANG X Q. Numerical research of twisted variability on axial compressor performance[J]. Energy Conservation Technology201735(2): 99-102, 112 (in Chinese).
42 于贤君, 庞健, 刘宝杰. 低速模拟在叶型加工偏差影响研究的应用[J]. 工程热物理学报201839(7): 1436-1446.
  YU X J, PANG J, LIU B J. The application of flow-speed simulation in researching the impact of blades manufacturing deviation on aerodynamic performance[J]. Journal of Engineering Thermophysics201839(7): 1436-1446 (in Chinese).
43 WANG J, ZHENG X. Review of geometric uncertainty quantification in gas turbines[J]. Journal of Engineering for Gas Turbines and Power2020142(7): 070801.
44 GARZON V E. Probabilistic aerothermal design of compressor airfoils[D]. Cambridge: Massachusetts Institute of Technology, 2003: 81-96.
45 HEINZE K, FRIEDL W H, VOGELER K, et al. Probabilistic HCF-Investigation of compressor blade: GT2009-59899[R]. Orlando: ASME, 2009.
46 GARZON V E, DARMOFAL D L. Impact of geometric variability on axial compressor performance[J]. Journal of Turbomachinery2003125(4): 692-703.
47 LANGE A, VOGELER K GüMMER V, et al. Introduction of a parameter based compressor blade model for considering measured geometry uncertainties in numerical simulation: GT2009-59937[R]. Orlando: ASME, 2009.
48 LANGE A, VOIGT M, VOGELER K, et al. Probabilistic CFD simulation of a high-pressure compressor stage taking manufacturing variability into account: GT2010-22484[R]. Glasgow: ASME, 2010.
49 LANGE A, VOIGT M, VOGELER K, et al. Impact of manufacturing variability on multistage high-pressure compressor performance[J]. Journal of Engineering for Gas Turbines and Power2012134(11): 112601.
50 WIENER N. The homogeneous chaos[J]. American Journal of Mathematics193860(13): 897-936.
51 CAMERON R H, MARTIN W T. The orthogonal development of nonlinear functionals in series of Fourier-Hermite functionals[J]. Annals of Mathematics194748(2): 385-392.
52 郭正涛, 楚武利, 晏松, 等. 加工误差对压气机叶栅气动性能及稳定性影响的数据挖掘[J]. 推进技术202243(3): 133-145.
  GUO Z T, CHU W L, YAN S, et al. Data mining on effects of manufacturing error on aerodynamic performance and stability of compressor cascade[J]. Journal of Propulsion Technology202243(3): 133-145 (in Chinese).
53 姬田园, 楚武利, 戴雨晨, 等. 叶顶间隙偏差对叶片气动性能影响的不确定性研究[J]. 推进技术202243(10): 134-146.
  JI T Y, CHU W L, DAI Y C, et al. Uncertainty research of effects of blade tip clearance deviation on blade aerodynamic Performance[J]. Journal of Propulsion Technology202243(10): 134-146 (in Chinese).
54 BERT J D, HABIB N, PHILIPPE P, et al. Numerical challenges in the use of polynomial chaos representations for stochastic processes[J]. SIAM Journal on Scientific Computing200426(2): 698-719.
55 LOEVEN G, WITTEVEEN J, BIJL H. Probabilistic collocation: an efficient non-intrusive approach for arbitrarily distributed parametric uncertainties[C]∥45th AIAA Aerospace Sciences Meeting. 2007: 3845-3858.
56 PARUSSINI L, PEDIRODA V. Investigation of multi geometric uncertainties by different polynomial chaos methodologies using a fictitious domain solver[J]. Computer Modeling in Engineering and Sciences200823: 29-51.
57 赵轲, 高正红, 黄江涛, 等. 基于PCE方法的翼型不确定性分析及稳健设计[J]. 力学学报201446(1): 10-19.
  ZHAO K, GAO Z H, HUANG J T. Uncertainty quantification and robust design of airfoil based on polynomial chaos technique[J]. Chinese Journal of Theoretical and Applied Mechanics201446(1): 10-19 (in Chinese).
58 WUNSCH D, HIRSCH C, NIGRO R, et al. Quantification of combined operational and geometrical uncertainties in turbo-machinery design: GT2015-43399[R]. Montreal: ASME, 2015.
59 蔡宇桐, 高丽敏, 马驰, 等. 基于NIPC的压气机叶片加工误差不确定性分析[J]. 工程热物理学报201738(3): 490-497.
  CAI Y T, GAO L M, MA C, et al. Uncertainty quantification on compressor blade considering manufacturing error based on NIPC method[J]. Journal of Engineering Thermophysics201738(3): 490-497 (in Chinese).
60 高丽敏, 蔡宇桐, 曾瑞慧, 等. 叶片加工误差对压气机叶栅气动性能的影响[J]. 推进技术201738(3): 525-531.
  GAO L M, CAI Y T, ZENG R H, et al. Effects of blade machining error on compressor cascade aerodynamic performance[J]. Journal of Propulsion Technology201738(3): 525-531 (in Chinese).
61 高丽敏, 蔡宇桐, 徐浩亮, 等. 压气机叶片加工误差影响不确定分析[J]. 航空动力学报201732(9): 2253-2259.
  GAO L M, CAI Y T, XU H L, et al. Uncertainty analysis of machining error influence of compressor blade[J]. Journal of Aerospace Power201732(9): 2253-2259 (in Chinese).
62 TENG X, CHU W L, ZHANG H G, et al. The influence of geometry deformation on a multistage compressor: GT2018-75935[R]. Oslo: ASME, 2018.
63 MA C, GAO L, WANG H, et al. Influence of leading edge with real manufacturing error on aerodynamic performance of high subsonic compressor cascades[J]. Chinese Journal of Aeronautics202134(6): 220-232.
64 LUO J Q, LIU F. Statistical evaluation of performance impact of manufacturing variability by an adjoint method[J]. Aerospace Science and Technology201877: 471-484.
65 DAROCZY L, JANIGA G, THEVENIN D. Analysis of the performance of a H-Darrieus rotor under uncertainty using polynomial chaos expansion[J]. Energy2016113(30): 399-412.
66 MA C, GAO L M, CAI Y T. Robust optimization design of compressor blade considering machining error: GT2017-63157[R]. Charlotte: ASME, 2017.
67 WANG K, CHEN F, YU J Y. Nested sparse-grid stochastic collocation method for uncertainty quantification of blade stagger angle[J]. Energy2020201: 117583.
68 SMOLYAK S. A. Quadrature and interpolation formulas for tensor products of certain classes of functions[J]. Doklady Akademii Nauk SSSR19634(5): 240-243.
69 BLATMAN G, SUDRET B. An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis[J]. Probabilistic Engineering Mechanics201025(2): 183-197.
70 XIA Z H, LUO J Q, LIU F. Performance impact of flow and geometric variations for a turbine blade using an adaptive NIPC method[J]. Aerospace Science and Technology201990: 127-139.
71 LIU Y M, QIN R H, JU Y P, et al. Impact of realistic manufacturing uncertainties on the aerodynamic performance of a transonic centrifugal impeller: GT2020-14784, V02DT38A012[R]. Virtual: ASME, 2020.
72 GUO Z T, CHU W L. Stochastic aerodynamic analysis for compressor blades with manufacturing variability based on a mathematical dimensionality reduction method[J]. Journal of Mechanical Engineering Science2022236(10): 5719-5735.
73 JU Y P, LIU Y M, JIANG W, et al. Aerodynamic analysis and design optimization of a centrifugal compressor impeller considering realistic manufacturing uncertainties[J]. Aerospace Science and Technology2021115: 106787.
74 GUO L, LIU Y L, ZHOU T. Data-driven polynomial chaos expansions: a weighted least-square approximation[J]. Journal of Computational Physics2019381: 129-145.
75 AHLFELD R, MONTOMOLI F. A single formulation for uncertainty propagation in turbomachinery: SAMBA PC[J]. Journal of Turbomachinery2017139(11): 111007.
76 GUO Z T, CHU W L, ZHANG H G. A data-driven non-intrusive polynomial chaos for performance impact of high subsonic compressor cascades with stagger angle and profile errors[J]. Aerospace Science and Technology2022129: 107802.
77 SIVIA D. Data Analysis: A Bayesian Tutorial[M]. Oxford: Oxford University Press, 2006: 153-164.
78 SAYLOR P E, SMOLARSKI D C. Computing the roots of complex orthogonal and kernel polynomials[J]. SIAM Journal on Scientific Computing19889(1): 1-13.
79 LEJON M, ANDERSSON N, ELLBRANT L, et al. The impact of manufacturing variations on performance of a transonic axial compressor rotor[J]. Journal of Turbomachinery2020142(8): 081009.
80 LOU F Y, DOUGLAS R, MATTHEWS, NICHOLAS J, et al. Accounting for circumferential flow nonuniformity in a multistage axial compressor[J]. Journal of Turbomachinery2023145(7): 071016.
81 RATCHEV S, LIU S, HUANG W, et al. Milling error prediction and compensation in machining of low-rigidity parts[J]. International Journal of Machine Tools and Manufacture200444(15): 1629-1641.
82 WAN M, ZHANG W H, QIU K P, et al. Numerical prediction of static form errors in peripheral milling of thin-walled workpieces with irregular meshes[J]. Journal of Manufacturing Science and Engineering2005127: 13-22.
83 LAZOGLU I, MAMEDOV A. Deformation of thin parts in micro milling[J]. CIRP Annals-Manufacturing Technology201665: 117-120.
84 LI Z L, TUYSUZ O, ZHU L M, et al. Surface form error prediction in five-axis flank milling of thin-walled parts[J]. International Journal of Machine Tools and Manufacture2018128: 21-32.
85 ANNONI M, REBAIOLI L, SEMERARO Q. Thin wall geometrical quality improvement in micro milling[J]. The International Journal of Advanced Manufacturing Technology201579: 881-895.
86 CAO L, ZHANG X M, HUANG T, et al. Online monitoring machining errors of thin-walled workpiece: a knowledge embedded sparse Bayesian regression approach[J]. IEEE/ASME Transactions on Mechatronic201924(3): 1259-1270.
87 DITTRICH M A, UHLICH F, DENKENA B. Self-optimizing tool path generation for 5-axis machining processes[J]. CIRP Journal of Manufacturing Science and Technology201924: 49-54.
88 ZHANG Z, QI Y, CHENG Q, et al. Machining accuracy reliability during the peripheral milling process of thin-walled components[J]. Robotics and Computer-Integrated Manufacturing201959: 22234.
89 SUN H, PENG F Y, ZHOU L, et al. A hybrid driven approach to integrate surrogate model and Bayesian framework for the prediction of machining errors of thin-walled parts[J]. International Journal of Mechanical Sciences2021192: 106111.
90 LI R Y, WANG S H, WANG C, et al. Research into dynamic error optimization method of impeller blade machining based on digital-twin technology[J]. Machines202311(7): 697-722.
91 LO C C, HSIAO C Y. A method of tool path compensation for repeated machining process[J]. International Journal of Machine Tools and Manufacture199838(3): 205-213.
92 RAHMAN M, HEIKKALA J, LAPPALAINEN K. Modeling, measurement and error compensation of multi-axis machine tools. Part I: theory[J]. International Journal of Machine Tools and Manufacture200040(10): 1535-1546.
93 BOHEZ E L. Compensating for systematic errors in 5-axis NC machining[J]. Computer-Aided Design200234(5): 391-403.
94 RAKSIRI C, PARNICHKUN M. Geometric and force errors compensation in a 3-axis CNC milling machine[J]. International Journal of Machine Tools and Manufacture200444(12-13): 1283-1291.
95 胡创国. 薄壁件精密切削变形控制与误差补偿技术研究[D]. 西安: 西北工业大学, 2007: 52-64.
  HU C G. Deformation control and error compensation in precision machining of thin-walled parts[D]. Xi’an: Northwestern Polytechnical University, 2007: 52-64 (in Chinese).
96 LAW K M, GEDDAM A. Error compensation in the end milling of pockets: a methodology[J]. Journal of Materials Processing Technology2003139(1-3): 21-27.
97 SUH S H, CHO J H, HASCOET J Y. Incorporation of tool deflection in tool path computation: simulation and analysis[J]. Journal of Manufacturing Systems199615(3): 190-199.
98 HABIBI M. AREZOO B, NOIEDEH M V. Tool deflection and geometrical error compensation by tool path modification[J]. International Journal of Machine Tools and Manufacture201151(6): 439-449.
99 SOORI M, AREZOO B, HABIBI M. Tool deflection error of three-axis computer numerical control milling machines, monitoring and minimizing by a virtual machine system[J]. Journal of Manufacturing Science and Engineering2016138(8): 081005.
100 WAN M, ZHANG W H, QIN G H, et al. Strategies for error prediction and error control in peripheral milling of thin-walled workpiece[J]. International Journal of Machine Tools and Manufacture200848(12-13): 1366-1374.
101 MA W, HE G, ZHU L, et al. Tool deflection error compensation in five-axis ball-end milling of sculptured surface[J]. The International Journal of Advanced Manufacturing Technology201684(5-8): 1421-1430.
102 DU Z, ZHANG D, HOU H, et al. Peripheral milling force induced error compensation using analytical force model and APDL deformation calculation [J]. The International Journal of Advanced Manufacturing Technology201788(9-12): 3405-3417.
103 HUANG N, BI Q, WANG Y, et al. 5-axisAdaptive flank milling of flexible thin-walled parts based on the on-machine measurement[J]. International Journal of Machine Tools and Manufacture201484: 1-8.
104 PONIATOWSKA M. Free-form surface machine error compensation applying 3D CAD machine pattern model[J]. Computer-Aided Design201562: 227-235.
105 PONIATOWSKA M. Deviation model base on method of planning accuracy inspection of free-form surfaces using CMMs[J]. Measurement201245(5): 927-937.
106 WANG M H, SUN Y. Error prediction and compensation based on interference-free toolpaths in blade milling[J]. International Journal of Advanced Manufacturing Technology201471(5-8): 1309-1318.
107 LIM E M, MENG C H. Error compensation for sculptured surface productions by the application of control-surface strategy using predicted machining errors[J]. Journal of Manufacturing Science and Engineering1997119(3): 402-409.
108 GUIASSA R, MAYER J R R. Predictive compliance based model for compensation in multi-pass milling by on-machine probing[J]. CIRP Annals-Manufacturing Technology201160: 391-394.
109 GUIASSA R, MAYER J R R, BALAZINSKI M, et al. Closed door machine error compensation of complex surfaces using the cutting compliance coefficient and on-machine measurement for a milling process[J]. International Journal of Computer Integrated Manufacturing201427(11): 1022-1030.
110 BRISTO W D, THARAYIL M, ALLEYNE A G. A survey of iterative learning control[J]. IEEE Control Systems200626(3): 96-114.
111 CHO M W, SEO T. Machining error compensation using radial basis function network based on CAD/CAM/CAI integration concept[J]. International Journal of Production Research200240(9): 2159-2174.
112 刘佳, 卢晓煜. 计算机辅助加工工件变形分析方法[J]. 北京理工大学学报200222(6): 687-690.
  LIU J, LU X Y. Method of deformation analysis of workpiece in computer aided[J]. Journal of Beijing Institute of Technology200222(6): 687-690 (in Chinese).
113 王立涛, 柯映林, 黄志刚, 等. 基于神经网络的数控铣削变形预测[J]. 机械科学与技术200423(2): 209-211.
  WANG L T, KE Y L, HUANG Z G, et al. Numerical control milling deformation prediction based on neural network[J]. Mechanical Science and Technology for Aerospace Engineering200423(2): 209-211 (in Chinese).
114 YUAN Y, ZHANG H T, WU Y, et al. Bayesian earning-based model-predictive vibration control for thin-walled workpiece machine processes[J]. IEEE/ASME Transactions on Mechatronics201722: 509-520.
115 RAO S S, CHEN L. Determination of optimal machining conditions: a coupled uncertainty model[J]. Journal of Manufacturing Science and Engineering1998122: 206-214.
116 MD M H, JULIUS S. Physics-Informed uncertainty quantification in modeling of machining-induced residual stress[J]. Procedia CIRP2023117: 139-144.
117 YUE X W, WEN Y C, HUNT J H, et al. Surrogate model based control considering uncertainties for composite fuselage assembly[J]. Journal of Manufacturing Science & Engineering2018140(4): 041017.
118 LI X, YANG Y, LI L, et al. Uncertainty quantification in machining deformation based on Bayesian network[J]. Reliability Engineering and System Safety2020203: 107113.
119 SCHMITZ T L, KARANDIKAR J, KIM N H, et al. Uncertainty in machining: workshop summary and contributions[J]. Journal of Manufacturing Science and Engineering2011133(5): 051009.
120 LEE S W, LEE H K. Rule-based cutting condition recommendation system for intelligent machine tools[J]. Journal of Mechanical Science and Technology200923: 1202-1210.
121 PENG C, DU H, LIAO T W. A research on the cutting database system based on machining features and TOPSIS[J]. Robotics and Computer-Integrated Manufacturing201743: 96-104.
122 ZAINAL N, ZAIN A M, RADZI N, et al. Glowworm swarm optimization (GSO) for optimization of machining parameters[J]. Journal of Intelligent Manufacturing201627: 797-804.
123 LI B, TIAN X, ZHANG M. Modeling and multi-objective optimization of cutting parameters in the high-speed milling using RSM and improved TLBO algorithm[J]. International Journal of Advanced Manufacturing Technology2020111: 2323-2335.
124 LI X, LI L, YANG Y, et al. Machining deformation of single-sided component based on finishing allowance optimization[J]. Chinese Journal of Aeronautics202033(9): 2434-2444
125 ZHAO X, ZHENG L, ZHANG Y. Online first-order machining error compensation for thin-walled parts considering time-varying cutting condition[J]. Journal of Manufacturing Science & Engineering2022144(2): 021006.
126 SOORI M, AREZOO B. Minimization of surface roughness and residual stress in grinding operations of Inconel 718[J]. Journal of Materials Engineering and Performance202232: 8185-8194.
127 MOHANRAJ T, SHANKAR S, RAJASEKAR R, et al. Tool condition monitoring techniques in milling process: A review[J]. Journal of Marketing Research20209: 1032-1042.
128 WINTER K, HARTMANN J, JESCHKE P, et al. Experimental and numerical investigation of streamwise surface waviness on axial compressor blades: GT2013-95983, V06AT35A041[R]. San Antonio: ASME, 2013.
129 蓝仁浩, 黄云, 陈贵林, 等. 航空发动机叶片精密自适应砂带磨削技术及试验研究[J]. 航空制造技术201861(15): 16-24.
  LAN R H, HUANG Y, CHEN G L, et al. Self-adaptive belt grinding technology and its experimental research on aeroengine blade[J]. Aeronautical Manufacturing Technology201861(15): 16-24 (in Chinese).
130 高丽敏, 杨光, 王浩浩, 等. 波纹对高亚音叶型气动敏感位置和宽度研究[J]. 工程热物理学报202344(1): 78-85.
  GAO L M, YANG G, WANG H H, et al. Research on the aerodynamic sensitive position and width of waviness on the high subsonic profile[J]. Journal of Engineering Thermophysics202344(1): 78-85 (in Chinese).
131 张军锋, 史耀耀, 蔺小军, 等. 航空发动机叶片前后缘自由式砂带抛光技术[J]. 航空学报201738(3): 242-250.
  ZHNAG J Y, SHI Y Y, LIN X J, et al. Freestyle belt polishing technology for leading and trailing edges of aero-engine blade[J]. Acta Aeronautica et Astronautica Sinica201738(3): 242-250 (in Chinese).
132 赵欢, 姜宗民, 丁汉. 航空发动机叶片叶缘随形磨抛刀路规划[J]. 航空学报202142(10): 524318.
  ZHAO H, JIANG Z M, DING H. Tool path planning for profiling grinding of aero-engine blade edge[J]. Acta Aeronautica et Astronautica Sinica202142(10): 524318 (in Chinese).
133 张明德, 蔡汉水, 谢乐, 等. 航发叶片前后缘数控砂带磨削关键技术研究[J]. 机械科学与技术201837(5): 797-803.
  ZHANG M D, CAI H S, XIE L, et al. Research on key technology of CNC abrasive belt grinding for aircraft engines blade edges[J]. Mechanical Science and Technology for Aerospace Engineering201837(5): 797-803 (in Chinese).
134 ACKERET J. über luftkr?fte bei sehr grossen geschwindigkeiten insbesondere bei ebenen str?mungen[J]. Helvetica Chimica Acta19281: 301-322.
135 SHAPIRO A. The dynamics and thermodynamics of compressible fluid flow, Ⅱ[M]. Cambridge: Cambridge University Press, 1954: 832-846.
136 LIGHTHILL M. On boundary layers and upstream influence. II. Supersonic flows without separation[J]. Proceedings of the Royal Society of London1953217(1131): 478-507.
137 BENJAMIN T. Shearing flow over a wavy boundary[J]. Journal of Fluid Mechanics19596(2): 161-205.
138 LEKOUDIS S, NAYFEH A, SARIC W. Compressible boundary layers over wavy walls[J]. Physics of Fluids197619(4): 514-519.
139 HOSOKAWA I. Transonic flow past a wavy wall[J]. Journal of the Physical Society of Japan196015(11): 2080-2086.
140 ZIEREP J. Die Transsonische umstr?mung der welligen wand mit verdichtungsst?ssen[J]. Applied Mechanics Reviews197217: 721-729.
141 JUNGBLUTH H. Experimente zur schallnahen str?mung l?ngs einer welligen wand[J]. Acta Mechanica197522(3): 171-180.
142 CHERNORAY V, ORE S, LARSSON J. Effect of geometry deviations on the aerodynamic performance of an outlet guide vane cascade: GT2010-22923[R]. Glasgow: ASME, 2010.
143 HARTMANN J, WINTER K, JESCHKE P, et al. Tolerant airfoils-numerische und experimentelle untersuchung des einflusses kleinskaliger geometrievariationen auf die aerodynamik von verdichterschaufeln[J]. Institute of Jet Propulsion and Turbomachinery20111-2: 866-873.
144 HARTMANN J, WINTER K, JESCHKE P. Aerodynamic influence of streamwise surface corrugation on axial compressor blades: RWTH-CONV-202159[R]. Budapest: Chair of Jet Propulsion and Turbomachinery, 2012.
145 KOIKE Y, MATSUBARA A, NISHIWAKI S, et al. Cutting path design to minimize workpiece displacement at cutting point: Milling of thin-walled parts[J]. International Journal of Automation Technology20126(5): 638-647.
146 KOIKE Y, MATSUBARA A, YAMAJI L. Design method of material removal process for minimizing workpiece displacement at cutting point[J]. CIRP Annals-Manufacturing Technology201362: 419-422.
147 WANG J, IBARAKI S, MATSUBARA A. A cutting sequence optimization algorithm to reduce the workpiece deformation in thin-wall machining[J]. Precision Engineering201750: 506-514.
148 YAN Q, LUO M, TANG K. Multi-axis variable depth-of-cut machining of thin-walled workpieces based on the workpiece deflection constraint[J]. Computer-Aided Design2018100: 14-29.
149 LUO M, ZHANG D H, WU B H, et al. Material removal process optimization for milling of flexible workpiece considering machining stability[J]. Journal of Engineering Manufacture2011225(8): 1263-1272.
150 MUNDIM R B, BORILLE A V. An approach for reducing undesired vibrations in milling of low rigidity structures[J]. The International Journal of Advanced Manufacturing Technology201788(1-4): 971-983.
151 TUYSUZ O, ALTINTAS Y. Time-Domain modeling of varying dynamic characteristics in thin-wall machining using perturbation and reduced-order sub structuring methods[J]. Journal of Manufacturing Science and Engineering2018140: 011015.
152 王伟, 允超, 张令. 机器人砂带磨削的曲面路径优化算法[J]. 机械工程学报201147(7): 8-15.
  WANG W, YUN C, ZHANG L. Optimization algorithm for robotic belt surface grinding process[J]. Journal of Mechanical Engineer201147(7): 8-15 (in Chinese).
153 蔺小军, 杨艳, 吴广, 等. 面向叶片型面的五轴联动柔性数控砂带抛光技术[J]. 航空学报201536(6): 2074-2082.
  LIN X J, YANG Y, WU G, et al. Flexible polishing technology of five-axis NC abrasive belt for blade surface[J]. Acta Aeronautica et Astronautica Sinica201536(6): 2074-2082 (in Chinese).
154 YANG J H, ZHANG D H, WU B H, et al. A path planning method for error region grinding of aero-engine blades with free-form surface[J]. The International Journal of Advanced Manufacturing Technology201581(1-4): 717-728.
155 HUANG Z, SONG R, WAN C B, et al. Trajectory planning of abrasive belt grinding for aero-engine blade profile[J]. The international Journal of Advanced Manufacturing Technology2019102: 405-514.
156 LV Y, PENG Z, QU C, et al. An adaptive trajectory planning algorithm for robotic belt grinding of blade leading and trailing edges based on material removal profile model[J]. Robotics and Computer-Integrated Manufacturing202066: 101987.
157 PANDIYAN V, CAESARENDRA W, TJAHJOWIDODO T, et al. Predictive modelling and analysis of process parameters on material removal characteristics in abrasive belt grinding process[J]. Applied Science20177(4): 363-369.
158 ZHE H, JIANYONG L, YUEMING L, et al. Investigating the effects of contact pressure on rail material abrasive belt grinding performance[J]. The International Journal of Advanced Manufacturing Technology20179: 779-786.
159 XIAO G, SONG K, LIU S, et al. Comprehensive investigation into the effects of relative grinding direction on abrasive belt grinding process[J]. Journal of Manufacturing Processes202162: 753-761.
160 HUANG H, GONG Z M, CHEN X Q, et al. Robotic grinding and polishing for turbine-vane overhaul[J]. Journal of Materials Processing Technology2002127(2): 140-145.
161 PANDIYAN V, CAESARENDRA W, GLOWACZ A, et al. Modelling of material removal in abrasive belt grinding process: A regression approach[J]. Symmetry202012: 99-104.
162 GILL S S, SINGH J. An Adaptive Neuro-Fuzzy Inference System modeling for material removal rate in stationary ultrasonic drilling of sillimanite ceramic[J]. Expert Systems with Applications201037(8): 5590-5598.
163 KHALICK M, HONG J, WANG D. Polishing of uneven surfaces using industrial robots based on neural network and genetic algorithm[J]. The International Journal of Advanced Manufacturing Technology201793: 1463-1471.
164 GAO K, CHEN H, ZHANG X, et al. A novel material removal prediction method based on acoustic sensing and ensemble XG-Boost learning algorithm for robotic belt grinding of Inconel 718[J]. The International Journal of Advanced Manufacturing Technology2019105: 217-232.
165 BIXLER G D, BHUSHAN B. Bioinspired rice leaf and butterfly wing surface structures combining shark skin and lotus effects[J]. Soft Matter20128(44): 12139-12143.
166 ATT W, OGAWA T. Biological aging of implant surfaces and their restoration with ultraviolet light treatment: a novel understanding of osseointegration[J]. The International Journal of Oral & Maxillofacial Implants201227(4): 753-761
167 KLOCKE F, FELDHAUS B. Development of an incremental rolling process for the production of defined riblet surface structures[J]. Production Engineering20071: 233-237.
168 WALSH M J. Riblets as a viscous drag reduction technique[J]. AIAA Journal198321(4): 485-486.
169 DEAN B, BHUSHAN B. Shark-skin surfaces for ?uid-drag reduction in turbulent ?ow: A review[J]. Philosophical Transactions of the Royal Society A2010368(1929): 4775-4806.
170 BECHERT D W, BRUSE M, HAGE W, et al. Experiments on drag-reducing surfaces and their optimization with an adjustable geometry[J]. Journal of Fluid Mechanics1997338(10): 59-87.
171 CHOI H, MOIN P, KIM J. Direct numerical simulation of turbulent flow over riblets[J]. Journal of Fluid Mechanics1993255(26): 503-539.
172 ZHANG D Y, LUO Y H, CHEN H W, et al. Exploring drag-reducing grooved internal coating for gas pipelines[J]. Pipeline and Gas Journal2011238(3): 58-61.
173 ZHANG D Y, LI Y Y, HAN X, et al. High-precision bio-replication of synthetic drag reduction shark skin[J]. Chinese Science Bulletin201156(5): 938-944.
174 XIAO G J, HE Y, HUANG Y, et al. Bionic microstructure on titanium alloy blade with belt grinding and its drag reduction performance[J]. Journal of Engineering Manufacture2021235(14): 2230-2239.
175 FISH F E, BATTLE J M. Hydrodynamic Design of the Humpback Whale Flipper[J]. Journal of Morphology1995225: 51-60.
176 ASGHAR A, ALLAN W D E, LA VIOLETTE M, et al. Influence of a novel 3D leading edge geometry on the aerodynamic performance of low pressure turbine blade cascade vanes: GT2014-25899, V02CT38A024[R]. Düsseldorf: ASME, 2014.
177 PEREZ R E, ASGHAR A. Numerical study of the effects of leading edge tubercles on transonic performance of airfoils[R]. Atlanta: AIAA, 2018.
178 张凯. 鼓包前缘叶片对压气机性能和稳定性影响研究[D]. 南京:南京航空航天大学, 2016: 16-34.
  ZHANG K. Study on the effect of the leading edge blade of the drum pack on the performance and stability of the compressor[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2016: 16-34 (in Chinese).
179 张凯, 屠宝锋. 鼓包前缘叶片在环形叶栅中应用的探索[J]. 工程热物理学报201637(3): 514-0518.
  ZHANG K, TU B F. Investigation on Tubercle Leading Edge Blade in Annular Cascade[J]. Journal of Engineering Thermophysics201637(3): 514-0518 (in Chinese).
180 ZHENG T, QIANG X Q, TENG J F, et al. Application of humpback whale flippers in an annular compressor cascade: GT2016-56589, V02AT37A016[R]. Seoul: ASME, 2016.
181 ZHENG T, ZHU M, QIANG X Q, et al. Influence of leading edge tubercles in an annular compressor cascade with different hub-tip ratios and aspect ratios: GT2017-64054, V02AT39A026[R]. Charlotte: ASME, 2017.
182 郑覃. 扩压叶栅前缘结状凸起流动机理研究[D]. 上海:上海交通大学, 2019: 49-72.
  ZHENG T. Study on the flow mechanism of the knotted projection at the leading edge of the diffuser grille[D]. Shanghai: Shanghai Jiao Tong University, 2019: 49-72 (in Chinese).
183 WANG B, WU Y, LIU K. Numerical investigation of passive flow control using wavy blades in a highly-loaded compressor cascade: GT2018-76147, V02AT39A025[R]. Oslo: ASME, 2018.
184 苏丽蓉, 羌晓青. 波纹叶片控制扩压叶栅流动分离的DES数值模拟[J]. 节能技术202038(1): 16-20.
  SU L R, QIANG X Q. DES Investigation on compressor cascade flow control using undulating blade[J]. Energy Conservation Technology202038(1): 16-20 (in Chine-se).
185 BECHERT D W, BARTENWERFER M. The viscous-flow on sur-face with longitudinal ribs[J]. Journal of Fluid Mechanics1989206: 105-129.
186 WALSH M J, LINDEMANN A M. Optimization and application of riblets for turbulent drag reduction: 84-0347[R]. Reno: AIAA, 1984.
187 PAOLO L, FERNANDO M, AMILCARE P. Resistance of groove surface to parallel flow and cross-flow[J]. Journal of Fluid Mechanics1991228: 87-109.
188 OEHLERT K, SEUME J R, SIEGEL F. Exploratory experiments on machined riblets for 2-D compressor blades: IMECE2007-43457[R]. Seattle: ASME, 2007.
189 BECHERT, D, BRUSE, M, HAGE, W, et al. Fluid mechanics of biological surfaces and their technological application[J]. Naturwissenschaften200087: 157-171.
190 SCHOLLE M, RUND A, AKSEL N. Drag reduction and improvement of material transport in creeping films[J]. Archive of Applied Mechanics200675(2-3): 93-112.
191 BECHERT D W, BRUSE M, HAGE W. Experiments with three-dimensional riblets as an idealized model of shark skin[J]. Experiments in Fluids200028(5): 403-412.
192 YU H Y, ZHANG H C, GUO Y G, et al. Thermodynamic analysis of shark skin texture surfaces for microchannel flow[J]. Continuum Mechanics and Thermodynamics201628(5): 1361-1371.
193 SAVILL A M. Effects on turbulent boundary layer structure of longitudinal riblets alone and in combination with outer layer devices[C]∥Proceedings of the fourth international symposium on ?ow visualization. Berlin: Springer, 1986: 303-308.
194 HIRSCHEL E H, THIEDE P, MONNOYER F. Turbulence management-applications aspects[C]∥The AGARD symposium on ?uid dynamics of three-dimensional turbulent shear ?ows and transition. Neuilly-sur-Seine: AGARD, 1988: 1-12.
195 COUSTOLS E, COSTEIX J. Turbulent boundary layer manipulation in zero pressure gradient[C]∥Turbulent Shear Flows 6. Toulouse: ICAS and AIAA, 1988: 999-1013
196 COUSTOLS E. Behavior of internal manipulators: “riblet” models in subsonic and transonic flows[C]∥2nd Shear Flow Conference. Tempe: AIAA, 1989: 1-4.
197 ENYUTIN G V, LASHKOV Y, SAMOILOVA N V, et al. In?uence of downwash on the aerodynamic ef?ciency of fine-ribbed surfaces[J]. Fluid Dynamics199126: 31-35.
198 COUSTOLS E, SAVILL A M. Turbulent skin friction drag reduction by active and passive means-1 and 2[C]∥Special course on skin friction drag reduction. Neuilly-sur-Seine: AGARD, 1992: 1-80.
199 SCHNEIDER M, DINKELACKER A. Drag reduction by means of surface riblets on an inclined body of revolution[C]∥Speziale CG, Launder BE (eds) Near-wall turbulent flows. Amsterdam: Elsevier, 1993: 771-780.
200 KOELTZSCH K, DINKELACKER A, GRUNDMANN R. Flow over convergent and divergent wall riblets[J]. Experiments in Fluids202233(8): 346-350.
201 NUGROHO B, HUTCHINS N, MONTY J P. Large-scale spanwise periodicity in a turbulent boundary layer induced by highly ordered and directional surface roughness[J]. International Journal of Heat and Fluid Flow201340: 90-102.
202 CHEN H, RAO F, SHANG X, et al. Flow over bio-inspired 3d herringbone wall riblets[J]. Experiments in Fluids201455(3): 1-7.
203 LIU Q, ZHONG S, LI L. Effects of bio-inspired micro-scale surface patterns on the profile losses in a linear cascade[J]. Journal of Turbomachinery2019141(12): 121006.
204 LIU Q, ZHONG S, LI L. Investigation of riblet geometry and start locations of herringbone riblets on pressure losses in a linear cascade at low Reynolds numbers[J]. Journal of Turbomachinery2020142(10): 101010.
205 TEJ P, KARALI P. Fabrication of micro-textured surfaces using ball-end micromilling for wettability enhancement of Ti-6Al-4V[J]. Journal of Materials Processing Technology2018262: 168-181.
206 MO Q, LIU L, LI Y. Fabrication of IBAD-MgO and PLD-CeO2 layers for YBCO coated conductors[J]. Chinese Physics Letters201532: 206-209.
207 PATEL D S, JAIN V K, SHRIVASTAVA A, et al. Electrochemical micro texturing on flat and curved surfaces: simulation and experiments[J]. The International Journal of Advanced Manufacturing Technology2019100: 1269-1286.
208 LI X, DENG J, LIU L, et al. Tribological properties of WS2 coatings deposited on textured surfaces by electrohydrodynamic atomization[J]. Surface and Coatings Technology2018352(7): 128-143.
209 MENG Y, DENG J, ZHANG Y, et al. Tribological properties of textured surfaces fabricated on AISI 1045 steels by ultrasonic surface rolling under dry reciprocating sliding[J]. Wear2020460-461: 203488.
210 FANG S, LLANES L, BAEHRE D. Laser surface texturing of a WC-CoNi cemented carbide grade: surface topography design for honing application[J]. Tribology International2018122: 236-245.
211 XIE J, XIE H F, LIU X R, et al. Dry micro-grooving on Si wafer using a coarse diamond grinding[J]. International Journal of Machine Tools and Manufacture201261: 1-8.
212 DENKENA B, KOEHLER J, WANG B. Manufacturing of functional riblet structure by profile grinding[J]. CIRP Journal of Manufacturing Science and Technology20109(3): 14-26.
213 肖贵坚, 贺毅, 黄云, 等. 基于单颗粒模型的航发叶片砂带磨削微观仿生锯齿状表面形成及实验[J]. 航空学报202041(7): 623288.
  XIAO G J, HE Y, HUANG Y, et al. Single particle removal model and experimental study on micro bionic zig-zag surface of aeronautical blade using belt grinding[J]. Acta Aeronautica et Astronautica Sinica202041(7): 623288 (in Chinese).
214 XIAO G J, HE Y, HUANG Y, et al. Shark-skin-inspired micro-riblets forming mechanism of TC17 titanium alloy with belt grinding[J]. IEEE Access20197(107): 635-647.
215 PATEL D S, SINGH A, BALANI K, et al. Topographical effects of laser surface texturing on various time-dependent wetting regimes in Ti6Al4V[J]. Surface and Coatings Technology2018349: 816-829.
216 LIU Y, DENG J, WANG W, et al. Effect of texture parameters on cutting performance of flank-faced textured carbide tools in dry cutting of green Al2O3 [J]. Ceramics International201844(13): 205-217.
217 ARSLAN A, MASJUKI H H, KALAM M A, et al. Surface texture manufacturing techniques and tribological effect of surface texturing on cutting tool performance: a review[J]. Critical Reviews in Solid State and Materials Sciences201641: 447-481.
218 BUTTNER C C, SCHULZ U. Shark skin inspired riblet structures as aerodynamically optimized high temperature coatings for blades of aeroengines[J]. Smart Materials and Structures201120(9): 094016.
219 SCHLIETER A, PFLUMM R, SHAKHVERDOVA I, et al. Mechanical properties of shark-skin like structured surfaces for high-temperature applications[J]. Advanced Engineering Materials201518(5): 688-702.
220 LI X M, DENG J X, ZHANG L L, et al. Effect of surface textures and electrohydrodynamically atomized WS2 films on the friction and wear properties of ZrO2 coatings[J]. Ceramics International201945: 1020-1030.
221 DING L, AXINTE D, BUTLER-SMITH P, et al. Study on the characterisation of the PTFE transfer film and the dimensional designing of surface texturing in a dry-lubricated bearing system[J]. Wear2020448-449: 203238.
222 KUMAR M, RANJAN V, TYAGI R. Effect of Shape, Density, and an array of dimples on the friction and wear performance of laser textured bearing steel under dry sliding[J]. Journal of Materials Engineering and Performance202029: 2827-2838.
223 MULRONEY A T, GUPTA M C. Optically transparent superhydrophobic polydimethylsiloxane by periodic surface micro-texture[J]. Surface and Coatings Technology2017325: 308-317.
224 YUE H Z, DENG J X, GE D L, et al. Effect of surface texturing on tribological performance of sliding guideway under boundary lubrication[J]. Journal of Manufacturing Processes201947: 172-182.
225 YANG J A, GU D D, LIN K J, et al. Laser additive manufacturing of bio-inspired metallic structures[J]. Chinese Journal of Mechanical Engineering: Additive Manufacturing Frontiers20221: 100013.
226 International ISO/ASTM. Additive manufacturing-general principles-terminology: [S].
227 GU D D, SHI X Y, POPRAWE R, et al. Material-structure-performance integrated laser-metal additive manufacturing[J]. Science2021372(6545): 1487-1503.
228 HU K M, LIN K J, GU D D, et al. Mechanical properties and deformation behavior under compressive loading of selective laser melting processed bio-inspired sandwich structures[J]. Materials Science and Engineering: A2019762: 138089.
229 GU D D, DU LEI, DAI D H, et al. Influence of thermal behavior along deposition direction on microstructure and microhardness of laser melting deposited metallic parts[J]. Applied Physics A2015125(7): 455.
230 MATTHEW J H, ADMIR M, HOLTEN-ANDERSEN N, et al. Iron-Clad Fibers: A metal-based biological strategy for hard flexible coatings[J]. Science2010328: 216-220.
231 YAO H M, DAO M, IMHOLT T, et al. Protection mechanisms of the iron-plated armor of a deep-sea hydrothermal vent gastropod[J]. The Proceedings of the National Academy of Sciences2010107(3): 987-992.
232 TODARO C J, EASTON M A, QIU D, et al. Grain structure control during metal 3D printing by high-intensity ultrasound[J]. Nature Communications202011: 142.
233 RONG T, GU D D. Formation of novel graded interface and its function on mechanical properties of WC1-x reinforced Inconel 718 composites processed by selective laser melting[J]. Journal of Alloys and Compounds2016680: 333-342.
234 LAI F, QU S, LEWIS R, et al. The influence of ultrasonic surface rolling on the fatigue and wear properties of 23-8N engine valve steel[J]. International Journal of Fatigue2019125: 299-313.
235 ZHANG Q, HU Z, SU W, et al. Microstructure and surface properties of 17-4PH stainless steel by ultrasonic surface rolling technology[J]. Surface and Coatings Technology2017321: 64-73.
236 QU S, HU X, LU F, et al. Rolling contact fatigue properties of ultrasonic surface rolling treated 25CrNi2MoV steel under different lubricant viscosities[J]. International Journal of Fatigue2020142: 105970.
237 DANG J, ZHANG H, AN Q, et al. Surface integrity and wear behavior of 300M steel subjected to ultrasonic surface rolling process[J]. Surface and Coatings Technology2021421: 127380.
238 ZHANG Y L, LAI F Q, QU S G, et al. Effect of ultrasonic surface rolling on microstructure and rolling contact fatigue behavior of 17Cr2Ni2MoVNb steel[J]. Surface and Coatings Technology2019366: 321-330.
239 ZHANG Y, HUANG L, LU F, et al. Effects of ultrasonic surface rolling on fretting wear behaviors of a novel 25CrNi2MoV steel[J]. Materials Letters2020284(2): 128955.
240 REN Z, LAI F, QU S, et al. Effect of ultrasonic surface rolling on surface layer properties and fretting wear properties of titanium alloy Ti5Al4Mo6V2Nb1Fe[J]. Surface and Coatings Technology2020389: 125612.
241 LIU D, LIU D, GUAGLIANO M, et al. Contribution of ultrasonic surface rolling process to the fatigue properties of TB8 alloy with body-centered cubic structure[J]. Journal of Materials Science and Technology202061: 63-74.
242 LIU Z, GAO C, LIU X, et al. Improved surface integrity of Ti6Al4V fabricated by selective electron beam melting using ultrasonic surface rolling processing[J]. Journal of Materials Processing Technology2021297: 117264.
243 LEI L, ZHAO Q, ZHAO Y, et al. Gradient nanostructure, phase transformation, amorphization and enhanced strength-plasticity synergy of pure titanium manufactured by ultrasonic surface rolling[J]. Journal of Materials Processing Technology2021299: 117322.
244 LI Y, LIAN G, GENG J, et al. Effects of ultrasonic rolling on the surface integrity of in-situ TiB2/2024Al composite[J]. Journal of Materials Processing Technology2021293: 117068.
245 LU L X, SUN J, LI L, et al. Study on surface characteristics of 7050-T7451 aluminum alloy by ultrasonic surface rolling process[J]. The International Journal of Advanced Manufacturing Technology201687: 2533-2539.
246 XU X, LIU D, ZHANG X, et al. Mechanical and corrosion fatigue behaviors of gradient structured 7B50-T7751 aluminum alloy processed via ultrasonic surface rolling[J]. Journal of Materials Science and Technology201940: 88-98.
247 GENG J, YAN Z, ZHANG H, et al. Microstructure and mechanical properties of AZ31B magnesium alloy via ultrasonic surface rolling process[J]. Advanced Engineering Materials202123(9): 1-7.
248 ZHOU M, XU Y, LIU Y, et al. Microstructures and mechanical properties of Mg-15Gd-1Zn-0.4Zr alloys treated by ultrasonic surface rolling process[J]. Materials Science and Engineering2021828: 141881.
249 YE H, SUN X, LIU Y, et al. Effect of ultrasonic surface rolling process on mechanical properties and corrosion resistance of AZ31B Mg alloy[J]. Surface and Coatings Technology2019372: 288-298.
250 YANG J, LIU D, ZHANG X, et al. The effect of ultrasonic surface rolling process on the fretting fatigue property of GH4169 superalloy[J]. International Journal of Fatigue2019133: 105373.
251 WANG T, WANG D, LIU G, et al. Investigations on the nanocrystallization of 40Cr using ultrasonic surface rolling processing[J]. Applied Surface Science2008255: 1824-1829.
252 LIU Z, HE M, ZHAO J. Mechanical machining strengthening mechanism and material processing technology-a review[J]. Chinese Journal of Mechanical Engineering201526: 403-413.
253 CHENG M, ZHANG D, CHEN H, et al. Development of ultrasonic thread root rolling technology for prolonging the fatigue performance of high strength thread[J]. Journal of Materials Processing Technology2014214: 2395-2401.
254 LI G, QU S, PAN Y, et al. Effects of the different frequencies and loads of ultrasonic surface rolling on surface mechanical properties and fretting wear resistance of HIP Ti-6Al-4V alloy[J]. Applied Surface Science2016389: 324-334.
Outlines

/