航空轴流涡轮的多级气动优化设计及气动性能研究
|
摘要
涡轮作为航空发动机的重要部件,其性能的改进对发动机整体性能的提高有着至关重要的影响。气动设计是涡轮设计的核心,没有高水平的气动设计就没有高水平的涡轮性能。过去大量采用传统的准三维设计方法,随着数值模拟技术的不断成熟,近年来,基于优化理论的气动设计方法逐渐兴起,并且吸引了国内外同行学者的研究兴趣。但是将现代优化设计与准三维设计这两种方法联合起来对涡轮进行气动优化设计的研究,目前还很少见到。本文的主要工作就是研究联合应用准三维设计和现代自动优化设计对多级涡轮进行气动优化的设计方法。
本文首先通过比较包括现代自动优化设计方法的涡轮气动现代设计体系的优缺点,提出将现代自动优化设计方法与传统设计方法有机结合能有效地进行涡轮叶型的气动优化设计。采用四级轴流试验涡轮的试验数据,验证了应用Numeca商用软件模拟不同工况下多级涡轮内部流场的数值结果的可靠性。
为了实现准三维设计与自动优化设计的有机结合,本文编制了多级轴流涡轮气动优化设计流程,此流程包括准三维设计过程和多级局部优化设计过程。准三维设计主要是S2流面正问题计算,通过准三维设计进行初步设计,初步提高性能,确定总体参数,为下一步的优化设计打下基础。然后采用多级局部优化设计,通过提高局部性能来提高总体性能。局部优化过程联合采用人工神经网络和遗传算法,流场计算采用全三维粘性流N-S方程求解。局部优化设计有三个特点:(1).针对每列叶栅的气动特性进行局部优化;(2).各列叶栅反复多次优化;(3).粗细网格交替使用进行流场计算。总的来说,此设计流程可以发挥两种设计方法的优点,在不需要较多人力和时间的情况下完成设计。应用此设计流程分别对气冷涡轮级、三级涡轮和四级高负荷低压涡轮进行气动优化设计,总体性能均获得了不同程度的提高。
通过分析近年来的典型涡轮损失模型,找到了影响各种损失主要因素的相关参数。在优化设计时,合理调整这些参数能够较大幅度地降低总流动损失,在此基础上,本文提出了局部优化的组合优化参数群的概念。组合优化参数群分别由叶型优化参数组、子午流道优化参数组、积叠规律优化参数组以及优化参数组的组合构成。本文给出了各参数组的建立方法、适用条件以及如何通过流场诊断采用组合优化参数群进行局部优化设计。
最后,本文分析了优化设计中的两个难点问题,它们分别是高负荷低压涡轮的优化设计和多工况优化设计。在进行高负荷低压涡轮优化设计时要使用适当细的网格。此外,调整各级的功率、级负荷系数以及各级的静、动叶切向升力系数,使它们在各级中的分布尽量均匀,有利于提高涡轮的总体性能。多工况优化设计是多目标优化设计,在涡轮设计中是否采用,应该根据对具体情况的分析而定。对于各工况下性能相似的涡轮,应采用单工况为主的设计方法。对于各工况下性能差别较大的涡轮,必须采用多工况优化设计。
Turbine is an important component of aero engine. The improvements of its performance are of significant meaning to enhance the whole performance level of engine. Aerodynamic design plays a core role in the design of turbine since no high level performance can be achieved without high level aerodynamic design. In past, traditional quasi-three dimensional design (Q3D) methods were widely adopted. However, in recent years, with the incessant maturity of numerical simulation technology, aerodynamic design method based on optimization theory has gradually become prevailing and attracts great interest of researchers in this field of the whole world. However, few studies can be found at present in relation to combining modern optimization design methods and Q3D methods to perform the aerodynamic optimization design of turbine. Based on this point, the main task of this article is to study the design method of combining modern automatic optimization design methods and Q3D methods so as to achieve aerodynamic optimization of the multistage turbine.
First of all, through analysis of the advantages and shortcomings of the modern aerodynamic design system of turbine (including modern automatic optimization design methods), the paper brings forward that the aerodynamic optimization design of turbine blade profile can be effectively achieved by organically combining modern automatic optimization design methods and traditional design methods. The reliability of applying commercial software of NUMECA to simulate the internal flow field of multistage turbine at different work conditions is validated by adopting the test data of four-stage axial test turbine.
In this paper, an aerodynamic optimization design process of multistage axial turbine is compiled to implement the organic combination of Q3D and automatic optimization design. The design process is composed of Q3D design course and multistage local optimization design course. Q3D methods mainly refer to S2 stream surface direct problem calculation. Applying Q3D to conduct preliminary design can elementarily improve the total performance and fix on the total parameter so as to establish a base for the optimization design in the next step. Then adopting multistage local optimization design further improves the total performance through improving local performance. Local optimization course jointly applies genetic algorithm and artificial neural network. Flow computation applies three-dimensional viscosity Navier–Stokes equation solver. Such local optimization process has three features: (i) local optimization based on aerodynamic performance of every cascade; (ii) several times of optimizations being performed to every cascade; and (iii) alternate use of coarse grid and fine grid to compute flow field. In general, the design process may make full use of these two design methods and complete design in the condition of without huge expenditure of manpower and calculation time. Such process was applied to the aerodynamic optimization design of an air-cooled turbine stage, a three-stage turbine and a four-stage high load low pressure turbine. The total performance of these three turbines is improved in some degree.
Through analysis of the typical turbine loss model of recent years, correlative parameters that influence the main factors of all sorts of losses have been found out. In optimization design, the total flow loss can be reduced in a great extent by reasonably adjusting these parameters. On such basis, this paper brings forward the concept of combination optimization parameter group of local optimization. Combination optimization parameter group are composed of blade profile optimization parameter team, meridional channel optimization parameter team, stacking law optimization parameter team and the combination of optimization parameter team. The setting up methods, application condition of every parameter team and how to implement local optimization design by adopting parameter team through flow field diagnosis are presented in this paper.
Finally, two difficult problems in optimization design are analyzed in this paper. The two problems are the optimization design of high load low pressure turbine and the optimization design under multiple work conditions. The optimization design of high load low pressure turbine should apply proper fine calculation grid. Furthermore, adjusting the power and the stage load coefficient of every stage and the tangential lift coefficient of every stator and rotor so as to distribute more uniform in every stage is beneficial to improve total performance of turbine. The optimization design under multiple work conditions is multi-objective optimization design. Whether or not applying optimization design under multiple work conditions in turbine design should be decided according to the concrete conditions. The turbine with similar performance under every work condition should adopt the design method of mainly focusing on single work condition while the turbine with very different performance under every work condition should be designed by adopting optimization design under multiple work conditions.
本文首先通过比较包括现代自动优化设计方法的涡轮气动现代设计体系的优缺点,提出将现代自动优化设计方法与传统设计方法有机结合能有效地进行涡轮叶型的气动优化设计。采用四级轴流试验涡轮的试验数据,验证了应用Numeca商用软件模拟不同工况下多级涡轮内部流场的数值结果的可靠性。
为了实现准三维设计与自动优化设计的有机结合,本文编制了多级轴流涡轮气动优化设计流程,此流程包括准三维设计过程和多级局部优化设计过程。准三维设计主要是S2流面正问题计算,通过准三维设计进行初步设计,初步提高性能,确定总体参数,为下一步的优化设计打下基础。然后采用多级局部优化设计,通过提高局部性能来提高总体性能。局部优化过程联合采用人工神经网络和遗传算法,流场计算采用全三维粘性流N-S方程求解。局部优化设计有三个特点:(1).针对每列叶栅的气动特性进行局部优化;(2).各列叶栅反复多次优化;(3).粗细网格交替使用进行流场计算。总的来说,此设计流程可以发挥两种设计方法的优点,在不需要较多人力和时间的情况下完成设计。应用此设计流程分别对气冷涡轮级、三级涡轮和四级高负荷低压涡轮进行气动优化设计,总体性能均获得了不同程度的提高。
通过分析近年来的典型涡轮损失模型,找到了影响各种损失主要因素的相关参数。在优化设计时,合理调整这些参数能够较大幅度地降低总流动损失,在此基础上,本文提出了局部优化的组合优化参数群的概念。组合优化参数群分别由叶型优化参数组、子午流道优化参数组、积叠规律优化参数组以及优化参数组的组合构成。本文给出了各参数组的建立方法、适用条件以及如何通过流场诊断采用组合优化参数群进行局部优化设计。
最后,本文分析了优化设计中的两个难点问题,它们分别是高负荷低压涡轮的优化设计和多工况优化设计。在进行高负荷低压涡轮优化设计时要使用适当细的网格。此外,调整各级的功率、级负荷系数以及各级的静、动叶切向升力系数,使它们在各级中的分布尽量均匀,有利于提高涡轮的总体性能。多工况优化设计是多目标优化设计,在涡轮设计中是否采用,应该根据对具体情况的分析而定。对于各工况下性能相似的涡轮,应采用单工况为主的设计方法。对于各工况下性能差别较大的涡轮,必须采用多工况优化设计。
Turbine is an important component of aero engine. The improvements of its performance are of significant meaning to enhance the whole performance level of engine. Aerodynamic design plays a core role in the design of turbine since no high level performance can be achieved without high level aerodynamic design. In past, traditional quasi-three dimensional design (Q3D) methods were widely adopted. However, in recent years, with the incessant maturity of numerical simulation technology, aerodynamic design method based on optimization theory has gradually become prevailing and attracts great interest of researchers in this field of the whole world. However, few studies can be found at present in relation to combining modern optimization design methods and Q3D methods to perform the aerodynamic optimization design of turbine. Based on this point, the main task of this article is to study the design method of combining modern automatic optimization design methods and Q3D methods so as to achieve aerodynamic optimization of the multistage turbine.
First of all, through analysis of the advantages and shortcomings of the modern aerodynamic design system of turbine (including modern automatic optimization design methods), the paper brings forward that the aerodynamic optimization design of turbine blade profile can be effectively achieved by organically combining modern automatic optimization design methods and traditional design methods. The reliability of applying commercial software of NUMECA to simulate the internal flow field of multistage turbine at different work conditions is validated by adopting the test data of four-stage axial test turbine.
In this paper, an aerodynamic optimization design process of multistage axial turbine is compiled to implement the organic combination of Q3D and automatic optimization design. The design process is composed of Q3D design course and multistage local optimization design course. Q3D methods mainly refer to S2 stream surface direct problem calculation. Applying Q3D to conduct preliminary design can elementarily improve the total performance and fix on the total parameter so as to establish a base for the optimization design in the next step. Then adopting multistage local optimization design further improves the total performance through improving local performance. Local optimization course jointly applies genetic algorithm and artificial neural network. Flow computation applies three-dimensional viscosity Navier–Stokes equation solver. Such local optimization process has three features: (i) local optimization based on aerodynamic performance of every cascade; (ii) several times of optimizations being performed to every cascade; and (iii) alternate use of coarse grid and fine grid to compute flow field. In general, the design process may make full use of these two design methods and complete design in the condition of without huge expenditure of manpower and calculation time. Such process was applied to the aerodynamic optimization design of an air-cooled turbine stage, a three-stage turbine and a four-stage high load low pressure turbine. The total performance of these three turbines is improved in some degree.
Through analysis of the typical turbine loss model of recent years, correlative parameters that influence the main factors of all sorts of losses have been found out. In optimization design, the total flow loss can be reduced in a great extent by reasonably adjusting these parameters. On such basis, this paper brings forward the concept of combination optimization parameter group of local optimization. Combination optimization parameter group are composed of blade profile optimization parameter team, meridional channel optimization parameter team, stacking law optimization parameter team and the combination of optimization parameter team. The setting up methods, application condition of every parameter team and how to implement local optimization design by adopting parameter team through flow field diagnosis are presented in this paper.
Finally, two difficult problems in optimization design are analyzed in this paper. The two problems are the optimization design of high load low pressure turbine and the optimization design under multiple work conditions. The optimization design of high load low pressure turbine should apply proper fine calculation grid. Furthermore, adjusting the power and the stage load coefficient of every stage and the tangential lift coefficient of every stator and rotor so as to distribute more uniform in every stage is beneficial to improve total performance of turbine. The optimization design under multiple work conditions is multi-objective optimization design. Whether or not applying optimization design under multiple work conditions in turbine design should be decided according to the concrete conditions. The turbine with similar performance under every work condition should adopt the design method of mainly focusing on single work condition while the turbine with very different performance under every work condition should be designed by adopting optimization design under multiple work conditions.
引文
1 刘大响. 航空动力发展的历史性机遇. 航空发动机. 2005,31( 2) :1~3
2 C. H. Wu. A General Theory of Three Dimensional Flow in Subsonic and Supersonic Turbomachine in Radial, Axial and Mixed Flow Types. NASA TN-2604, 1952
3 I. A. Johnson, R. O. Bullock. Aerodynamic Design of Axial-Flow Compressors. NASA SP-36, 1965
4 J. H. Horlock, J. D. Denton. A Review of Some Early Design Practice using CFD and A Current Perspective. ASME paper GT2003-38973, 2003
5 A. J. Wennerstrom, G. R. Frost. Design of a 1500ft/sec, Transonic, High-Through-Flow, Single-Stage Axial-Flow Compressor with Low Hub/Tip Ratio. AFARL TR 76-59, 1976
6 黄洪雁,冯国泰,王仲奇,马云翔,林志鸿,闻雪友. 适用于舰用汽轮机的准三维设计体系. 热能动力工程. 1999,总第 80 期(14):119~121
7 J. D. Denton. The Calculation of Three Dimensional Viscous Flow Through Multistage Turbomachines. ASME paper 90-GT-19, 1990
8 R. H. Ni. Prediction of 3D Multi-Stage Turbine Flow Field Using a Multiple-Grid Euler Solver. AIAA paper 89-0203, 1989
9 W. N. Dawes. Towards Improved Through Flow Capability: The Use of 3D Viscous Flow Solvers in a Multistage Environment. ASME paper 90-GT-18, 1990
10 C. M. Rhie. Development and Application of a Multistage Navier-Stokes Solver, Part I: Multistage Modeling Using Body-Forces and Deterministic Stresses. ASME paper 95-GT-342, 1995
11 J. J. Adamczyk. Model Equation for Simulating Flows in Multistage Turbomachinery. ASME paper 85-GT-226, 1985
12 J. F. Thompson, N. P. Weatherill. Aspects of Numerical Grid Generation: Current and Art. AIAA Paper 93-3539, 1993
13 J. Dunham. CFD Validation for Propulsion System Components. AGARD-AR-355, 1998
14 S. K. Godunov. A Finite Diference Method for Numerical Computation of Discontinuous Solution of the Equations of Fluid Dynamics. Sov., Math., Sb.. 1959, 47:271~306
15 J. L. Steger, R. F. Warming. Flux Vector Splitting of the Inviscid Gasdynamic Equations with Application to Finite Diference Methods. Journal of Computational Physics.1981, 40:263~293
16 B. V. Leer. Flux Vector Spliting for the Euler Equations. Lecture Notes in Physics. 1982, 170:507-~512
17 P. L. Roe. Approximate Riemann Solvers, Parameter Vectors, and DiferenceSchemes. Journal of Computational Physics. 1981, 43:357~372
18 S. Osher, F. Solomon. Upwind Diference Schemes for Hyperbolic Systems of Conservation Laws. Math. Comp. 1982, 38: 285~292
19 A. Harten, P. D. Lax. Random Choice Finite Difference Schemes. SIAM Journal of Numerical Analysis. 1981, 18:289~315
20 B. V. Leer. Flux-Vector Spliting for the 1990s. NASA CP-3078, 1991
21 M. S. Liou, C. J. Stefen. A New Flux Spliting Scheme. Journal of Computational Physics. 1993, 107(1):23~39
22 Y. Wada, M. S. Liou. A Flux Spliting Scheme with High-Resolution and Robustness for Discontinuities. AIAA Paper 94-0083, 1994
23 M. S. Liou. A Sequel to AUSM: AUSM`. Journal of Computational Physics. 1996, 129( 1):364~382
24 K. H. Kim, J. H. Lee, O. H. Rho. An Improvement of AUSM Schemes by Introducing the Pressure-Based Weight Functions. Computers & Fluids. 1998, 27(1):311~346
25 A. S. Jameson, E. Turkel. Numerical Solutions of the Euler Equations by Finite Volume Methods with Runge-Kutta Time Stepping Schemes. AIAA Paper 81-1259, 1918
26 R. C. Swanson, E. Turkel. Artificial Dissipation and Central Diference Schemes for the Euler and N-S Equations. AIAA Paper 87-1107,1987
27 V. N. Vatsa, B. W. Wedan. Development of a Multigrid Code for 3-D Navier-Stokes Equations and its Application to a Grid Refinement Study. Computers & Fluids. 1990, 18(1):391~403
28 R. C. Swanson, E. Turkel. On Central Diference and Upwind Schemes. Journal of Computational Physics. 1992, 101( l):292~306
29 D. C. Wisler, J. D. Denton. Rotor 37 Blind Test Case. Presentation at ASME/IGTI International Gas Turbine Conference, Hague, The Netherlands, 1994
30 J. D. Denton. Lessons form Rotor 37. 3rd International Symposium on Experimental and Computational Aerothermodynamics of Internal Flows (ISAIF), Beijing, China, 1996
31 J. G. Marvin, G. P. Huang. Status and Future Directions for Turbulence Modeling. Proceeding of 7th ACFM, India, 1997
32 J. D. Denton. Loss Mechanisms in Turbomachines. ASME Paper 93-GT-435,1993
33 D. G. Ainley. The Performance of Axial Flow Turbines. Proe. Institution of Mechanical Engineers. 1948, 159:230~237
34 J. H. Horlock. Axial Flow Turbines. Butterworths Press, London, 1966
35 B. Lakshminarayana, J. G. Horlock. Review: Secondary Flows and Losses in Cascades and Axial-Flow Turbomachines. International Journal of Mechanical Sciences, 1963, 5: 397~409
36 J. A. Hesketh, H. Tritthard, P. Aubry. Modernization of Steam Turbines for Improved Performance. Symposium on Steam Turbines and Generaors,Monaco, GEC ALSTHOM, 1994
37 A. F. Carter, M. Platt, F. K. Lenherr. Analysis of Geometry and Design Point Performance of Axial Flow Turbines. I-Development of the Analysis Method and the Loss Coefficient Correlation. NASA CR-1181, 1968.
38 O. E. Bailje, R. L. Binsley. Axial Turbine Performance Evaluation: Part A-Loss-Geometry Relationships. Gas Turbines Power, 1968, 90:341~348.
39 H. R. M. Craig, H. J. A. Cox. Performance Estimation of Axial Flow Turbine. Proc. Instn. Mech. Engrs. 1970: 407~424
40 F. Martelli, A. Boretti. Development of an Experimental Correlation for Transonic Turbine Flow. ASME Paper 86-GT-108, 1986
41 H. W. Prust. Effect of Trailing Edge Geometry and Thickness on the Performance of Certain Turbine Stator Blading. NASA TN D6637, 1972
42 T. P. Moffitt, S. M. Nosek, R. J. Roelke. Turbine Aerodynamic Considerations for Advanced Turbine. NASA SP259, 1971
43 H. H. Hebbel. Uber den Einfluss den Machzahl und Reynadds-Zahl auf die Aerodynamischen Beiwerte Von Turbinenschaufelgittern. VDI Forschhft, 1960
44 M. E. Deich, G. A. Filoppor, L. Y. Lazarer. A Loss of Turbine Blade Cascades. G.E.G.B. Trans. 1965: 4563~4564
45 E. E. Flagg. Analytical Procedure and Computer Program for Determining the Off-Design Performance of Axial-Flow Turbines. NASA CR710, 1967
46 J. Hournouziadis, F. Buckl, P. Bergmann. The Development of the Profile Boundary layer in a Turbine Environment. ASME J. Turbomachinery. 1987, 109(2): 286~295.
47 P. Pucher, R. Goehl. Experimental Investigation of Boundary Layer Separation with Heated Thin-Film Sensor. ASME J. of Turbomachinery. 1987, 109(2): 303~309
48 J. Costa, T. Arts. Boundary Layer Transition under the Pressure of Discrete Frequencies in the Free stream Turbulence Spectrum. ASME paper 91-GT-355, 1991
49 H. D. Joslyn, R. P. Dring. Negative Incidence Flow over A Turbine Rotor Blade. ASME Paper 82-GT-23, 1982
50 R. P. Dring, H. D .Joslyn, L. W. Hardin, J. H. Wagner. Research on Turbine Rotor Stator Interaction and Rotor Negative Incidence Stall. AFWAL-TR-81-2114 (ADA116341), 1981
51 B. Lakshminarayana. Methods of Predicting the tip Clearance Effects in Axial Flow Turbomachinery. ASME Journal of Basic Engineering. 1970, 92: 467~482.
52 T. L. Sharma, Butler. Predictions of Endwall losses and Secondary Flows in Axial Flow Turbine Cascade. ASME Journal of Turbomachinery, 1987, 109:229~236
53 C. H. Sieverding, P. V. Bosch. The Use of Coloured Smoke to Visualize Secondary Flows in a Turbine-Blade Cascade. Journal of Fluid Mechanics.1983, 134:85~89
54 叶大均, 王仲奇. 叶轮机械真实流动损失机理及控制方法的研究., 国家自然科学基金会重大项目, 工程热物理中关键性问题的研究,第一部分—学术研究总结. 1992
55 A. Yamamoto, R. Yanagi. Production and Development of Secondary Flows and Losses within a Three-dimensional Turbine Stator Cascade. ASME Paper 85-GT-217, 1985
56 A. Yamamoto. Production and Development of Secondary Flows and Losses within Two Type of Straight Turbine Cascades, Part I: A Stator Case. ASME Paper 86-GT-184, 1986
57 J. Moore, A. Ransmary. Flow in a Turbine Cascade, Part I: Losses and Leading Edge Effects. ASME Paper 83-GT-68, 1983
58 W. R. Hawthrone. The Application of Secondary Flow Analysis to the Solution of Internal Flow Problems. Fluid Mechanics of Internal Flow, Elsevier, G. Sovran. 1974: 391~401
59 A. Klein. Untersuchungen uber die Einfluss der Zustr?mgrenzschicht auf die Sekund?rstr?mung in den Beschaufelungen von Axialturbinen. Forsch. Ing., 1966, Ba 32, Nr.6.
60 L. S. Langston. Cross Flow in a Turbine Cascade Passage. ASME Journal of Engineering for Power. 1980, 102: 866~874
61 H. P. Wang. Flow Visualization in a Linear Turbine Cascade of High Performance Turbine Blade. ASME Paper 95-GT-7, 1995
62 O. P. Sharma, T. L. Butler. Prediction of End Wall Losses and Secondary Flows in Axial Flow Turbine Cascade. ASME Journal of Turbomachinery. 1987, 109: 229~236
63 R. J. Goldstein, R. A. Spores. Turbulent Transport on the End Wall in the Region between Adjacent Turbine Blades. ASME Journal of Heat Transfer. 1988, 110: 862~869
64 J. D. Denton. Loss Mechanisms in Turbomachines Part II: Loss Generation in Turbomachines. Turbomachinery Blade Design Systems. Von Karman Institute for Fluid Dynamics. Belgium, 1999
65 J. Dunham, P. M. Came. Improvements to the Ainley & Mathieson Method of Turbine Performance Prediction. ASME J. of Eng. for Power. 1970, 92(3): 252~256
66 李喜宏,吴国华,彭泽涛. 压气机叶栅端壁流控制的实验研究. 航空动力学报. 1993,8(2): 143~147
67 W. D. Armstrong. The Secondary Flow in a Cascade of Turbines. R&M 2979. 1985
68 J. R. Turner. An Investigation of the End-Wall Boundary Layer of a Turbine Nozzle Cascade. Transactions of ASME 1957, 79:1801~1806.
69 H. Wolf. Die Randverluste in Geraden Schaufelgittern. Wiss. I. Tech. Hochsch. Dresden. 1961, 10(2):353~364.
70 S. Shahpar, L. Lapworth, T. Depablos, M. Taylor. A linear approach to the Multiparameter Design of Three-Dimensional Turbomachinery Blades. AIAA 99-0363, 37th AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, 1999
71 K. C. Giannakoglou. Designing Turbomaehinery Blades Using Evolutionary Methods. ASME Paper 99-GT-181, 1999
72 王正明,贾希诚. 正反问题数值解法相结合三维叶片的优化设计. 工程热物理学报. 2000, 21(5):567~569.
73 L. A. Catalano, A. Dadone. Progressive Optimization for the Efficient Design of 3D Cascades. AIAA Paper 2001-2578, 2001
74 W. T. Tiou, K. F. C. Yiu, M. Zangeneh. Application of Simulated Annealing to Inverse Design of Transonic Turbomachinery Cascades. Journal of Power and Energy. 2002, 216(1):59~73
75 曹志鹏,靳军,刘波,刘景新,王掩刚. 基于优化设计技术的叶型反方法改进设计. 航空动力学报. 2004,19(4):484~489.
76 刘仪,刘斌,向一敏,曹春丽. 十个参数的透平叶栅几何模型. 汽轮机技术. 1995,37 (4):196~198
77 祈明旭,刘斌,陈铁,刘万琨,赵萍. 一种新的轴流式透平叶栅叶型生成方法. 汽轮机技术. 1999,4(1):12~15
78 S. Goel, J.I. Cofer, H. Singh. Turbine airfoil design optimization. ASME Paper 96-GT-158, 1996
79 S. Pierret, R. A. Braembussehe. Turbomaehinery Blade Design Using A Navier-Stokes Solver And Artificial Neural Network. ASME Paper 98-GT-4,1998
80 S. Y. Lee, K.Y. Kim. Design Optimization of Axial Flow Compressor Blades with Three Dimensional Navier Stokes Solver. ASME Paper 2000-GT-0488, 2000
81 J. Chung, J. Shim, K. D. Lee. 3D Transonic Compressor Design Optimization with Quasi-3D Flow Physics. ASME 2000, FEDSM00-11075, 2000
82 A. Jameson. Aerodynamic Design via Control Theory. Technical Report 88-64, ICASE, 1988
83 J. Reuther, A. Jameson. Aerodynamic Shape Optimization of Wing and Wing-body Configurations Using Control Theory. AIAA Paper 95-0123, 1995
84 A. Jameson, N. A. Pierce, L. Martinelli. Optimum Aerodynamic Design Using the Navier-Stokes Equations. AIAA Paper 97-0101, 1997
85 J. H. Holland. Adaptive plants optimal for payoff-only environments. Proceeding of the Second Hawaii International Conference on System Sciences, 1969
86 J. H. Holland. Adaptation in Natural and Aritificial Systems. Ann Abor, The University of Michigan Press, 1975
87 L. J. Fogel, A. J. Owens, M. J. Walsh. Artificial Intelligence Through Simulated Evolution. New York, John Wiley, 1966
88 I. R. Evolitionsstrategie. Optimierung Technisher Systeme nach Prinzipien der Biologischen Evolution. Stuttgart, Fromman Holzboog Verlag, 1973.
89 H. P. Schwefel. Numerical Optimization of Computer Models. Chichester. Wiley, 1981.
90 K. D. Jong. Learning with genetic algorithms: an overview. Machiner Learning. 1988, 3: 121~138
91 A.Corana, M.Marchest, C.Martini, S.Ridella. Minimizing Multimodal Functions of Continuous Variables with the Simulated Annealing Algorithm. ACM Transactions on Mathematical Software. 1987, 13(3):262~280
92 W. W. McCulloch, W. Pitts. A Logic Calculus of the Ideas Imminent in Neurons Activity. Bulletin of Mathematical Biophysics.1943, 5: 495~500
93 F. Rosenblatt. The Perception: A Perceiving and Recognizing Automation. Cornell Aeronautical Laboratory Report, 85-406-1,1959
94 B. Widrow. An Adaptive Adaline Neuron Using Chemical Memistors. Stanford Electronics Laboratory Technical Report, 1960
95 J. J. Hopfield. Neural Networks and Physical Systems with Emergent Collective Computational Abilities. Proc Natl Acad Sci. USA. 1982, 79: 2552~2558.
96 J. J. Hopfield. Neurons with Graded Response Have Collective Computational Properties Like Those of Two-State Neuron. Proc Natl Acad Sci. USA. 1984, 81: 3088~3092
97 J. J. Hopfield, D. W. Tank. Neural Computation of Decision in Optimization Problem. Biol Cybern. 1982, 52: 141~152
98 史海秋,邓家禔. 涡轮叶片一维气动方案多学科优化设计. 制造业自动化. 2006,28(6):20~24
99 李军,丰镇平,沈祖达,常建忠. 透平跨音速叶栅的优化设计. 航空动力学报. 1997,12(3):287~290.
100 S.Pierret, R.A.V. Braembussche. Turbomachinery Blade Design Using a Navier-Stokes Solver and Artificial Neural Network. Journal of Turbomachinery. 1999, 121:326-332
101 B. H. Dennis, G.. S. Dulikravieh, Z. X. Han, Constrained Shape Optimization of Airfoil Cascades using a Navier-Stokes Solver and a Genetic/SQP Algorithm. ASME Paper 99-GT-441, 1999
102 M. Vascellari, R. Denos, R. V. Braembussche. Design of a Transonic High-pressure Turbine Stage 2D Section with Reduced Rotor/Stator Interaction. ASME Paper GT2004-53520., 2004
103 S. S. Talya, J. N. Rajadas, A. Chattopadhyay. Multidisciplinary Optimization of Gas Turbine Blade Design. AIAA Paper 98-4864, 1998
104 B. Buche, G. Guidati, P. Stoll. Automated Design Optimization of Compressor Blades for Stationary, Large-scale Turbomachinery. ASMEPaper GT-2003-38421, 2003
105 T. Sonoda, T. Arima, M. Olhofer. A study of advanced high loaded transonic turbine airfoils. ASME GT2004-53773, 2004
106 S. Pierret. Three-dimensional Blade Design by Means of an Artificial Neural Network and Navier-Stokes solver. Von Karman Institute Lecture Series on Turbomachinery Blade Design Systems, 1999
107 D. S. Shahpar. A Comparative Study of Optimization Methods for Aerodynamic Design of Turbomachinery blades. ASME Paper 2000-GT-523, 2000
108 W. Egartner. Working Range Optimization for Turbine and Compressor Bladeing. Journal of Computational and Applied Mathematics. 2000, 120: 59~65.
109 S. Shahpar. Three Dimensional Design and Optimisation of Turbomachinery Blades using the Navier-Stokes Equations. ISABE 2001-1053, 2001
110 N. Papila, W. Shyy, L. Griffin, D. J. Dorney. Shape Optimization of Supersonic Turbines Using Response Surface and Neural Network Methods. AIAA Paper 2001-1065, 2001
111 A. Oyama, M. S. Liou, S. Obayashi. Transonic Axial Flow Blade Shape Optimizatin Using Evolutionary Algorithm and Three-dimensional Navier-Stokes Solver. AIAA Paper 2002-5642, 2002
112 S. Kammerer, J. F. Mayer, M. Paffrath. Three-dimensional optimization of turbomachinery bladings using sensitivity analysis. ASME Paper GT2003-38037, 2003
113 S. Burguburu, A. L. Pape. Improved aerodynamic design of turbomachinery bladings by numerical optimization. Aerospace Science Technology. 2003, 7: 277~287
114 A. Demeulenaere, A. Ligout, C. Hirsch. Application of Multipoint Optimization to the Design of Turbomachinery Blades. ASME Paper 2004-GT-53110, 2004
115 A. Arnone, D. Bonaiuti, A. Focacci. Parametric optimization of a high-lift turbine vane. ASME Paper GT2004-54308, 2004
116 L. Moroz, Y. Govoruschenko, P. Pagur. Axial Turbine Stages Design: 1D/2D/3D Simulation, Experiment, Optimization-Design of Single Stage Test Air Turbine Models and Validation of 1D/2D/3D Aerodynamic Computation Results against Test Data. ASME Paper GT2005-68614, 2005
117 M. Hasenjager, B. Sendhoff, T. Sonoda, T. Arima. Three Dimensional Aerodynamic Optimization for an Ultra-low Aspect Ratio Transonic Turbine Stator Blade. ASME Paper GT2005-68680, 2005
118 Y. Y. Lai, X. Yuan. Blade Design With Three-Dimensional Viscous Analysis and Hybrid Optimization Approch. AIAA Paper 2002-5658, 2002
119 赖宇阳,袁新. 基于遗传算法和逐次序列二次规划的叶栅基迭优化. 工程热物理学报. 2003, 24(1):52~54.
120 虞跨海, 李立州, 王婧超, 岳珠峰. 涡轮叶片三维气动优化设计. 机械设计. 2005, 22(11):31~35
121 林智荣,石板浩一,袁新. 燃气透平末级及扩压器的联合优化. 工程热物理学报. 2005, 26( 1):47~50.
122 吴立强, 尹泽勇, 蔡显新. 航空发动机涡轮叶片的多学科设计优化. 航空动力学报. 2005, 20( 10):795~800
123 赵洪雷,王松涛,李东平,韩万金. 某型其冷涡轮级的三维优化设计. 热能动力工程. 2006,21(5):450~455.
124 王婧超, 李立州, 岳珠峰. 涡轮叶片的多学科设计优化系统. 航空动力学报. 2007,22(1):23~29.
125 冯国泰, 顾中华, 王松涛. 具有弯扭掠叶片流场结构分析能力的燃气涡轮三维设计体系——弯扭掠叶片设计体系与设计思想研究之一. 航空发动机. 2002 , 3:4~8.
126 G. Groschup. Stromungstechnische Unterscuhungeiner Axialturbinenstufeim Vergleichzum Verhalten der ebenen Gitterihrer Beschaufelung. Doktor Ingenieur Dissertation Technical University of Hannover, 1977.
127 L. Fottner. Test Cases f or Computation of Internal Flows in Aero Engine Components. AGARD-AR-275, 1990.
128 P. R. Spalart, S. R. Allmaras. A One-Equation Turbulence Model for Aerodynamic Flows. AIAA Paper 92-0439, 1992
129 袁宁,张振家,顾中华,冯国泰. 应用 S2 流面准三元计算程序分析小型发动机的跨音压气机气动特性. 推进技术,1996,17(6):6~11
130 黄家骅,于廷臣,冯国泰. 某小型涡扇发动机全流道准三维数值解法. 航空发动机. 2005,31( 2):42~45.
131 J. X. Su, G. T. Fengi, K. Hu. A Direct problem Method on S2 Stream Surface For Transonic Compressor In Aeroengine. Corpus of the Second Sino-Soviet Space Navigation Proseminar,1992.
132 S. Ito, E. R. G. Eckert, R. J. Goldstein. Aerodynamic Loss in a Gas Turbine Stage with Film Cooling. Journal of Engineering for Power. 1980, 102:1~7
133 B. Lakshminarayana. Fluid Dynamics and Heat. Transfer of Turbimachinery. 1996, 4: 672~679
134 N. Wei,S. Svensdotter. Investigation of the Flow Trough an Axial Turbine Stage, Licentiate Thesis Chair of Heat and Power Technology. KTH, ISRN KTH/KRV/R-95/1-SE, 1995.
135 D. G.. Ainley,G.. C. R. Mathieson, A method of Performance Estimation for Axial-Flow Turbines, British Aeronautical Research Council, R&M 2974 , 1951.
136 S. C. Kacker, U. Okapuu, A Mean Line Prediction Method for Axial Flow Turbine Efficiency, ASME 81-GT-58, 1981
137 J. D. Denton. Axial Turbine Aerodynamic Design. Leture Note for an Advanced Course on Turbomachinery Aerodynamic, University of Cambridge, UK, 1994.
138 W. L. Stewart, W. J. Whitney, R. Y. Wong. A study of Boundary-Layer Characteristics of Turbomachine Blade Rows and Their Relation to Over-All Blade Loss. Transactions of the ASME, 1960, 82: 580~592
139 P. Zehner. Calculation of four-Quadrant Characteristics of Turbines, ASME 80-GT-2, 1980
140 王仲奇,秦仁. 透平机械原理,机械工业出版社,1979 : 79~85
141 Z. Q. Wang, S. K. Lai, W. Y. Xu. Aerodynamic Calculation of Turbine Stator Cascades with Curvilinear Leaned Blades and Some Experimental Results. Symposium paper of 5-ty ISABE, India, 1981
142 W. J. Han, Z. Q. Wang. Experimental Studies on the Mechanism and Control of Secondary Flow Losses in Turbine Cascades. Journal of Thermal Science. 1992,4(1):218~231
143 Z. Q. Wang, W. J. Han. Effect of Leaning and Curving of Blades with High Turning Angles on the Aerodynamics Characteristics of Turbine Rectangular Cascade. Journal of Turbomachinery. 1994, 116:417~424
144 R. Vazquez, D. Cadrecha, D. Torre. High Stage Loading Low Pressure Turbines. A New Proposal for an Efficiency Chart. ASME Paper GT2003-38374, 2003
145 J. Q. Zhu, S. Sjolander. Improved Profile Loss and Deviation Correlation for Axial Turbine Blade Rows. ASME Paper GT2005-69077, 2005
146 I. Vlizar, P. Gonzalez. Aerodynamic Design of a New Five Stage Low Pressure Turbine for the Rolls Royce Trent 500 Turbofan. ASME Paper 2001- GT-0440, 2001.
147 R. T. Howell, H. P. Hodson, V. Schulte, H. P. Schiffer, F. Haselbach, N. W. Harley. Boundary Layer Development in the BR710 and BR715 LP Turbines — the Implementation of High Lift and Ultra High Lift Concepts. ASME Paper 2001- GT-0441, 2001
148 X. F. Zhang, M. Vera, H. Hodson. Separation and Transition Control on an Aft-loaded Ultra-high-lift LP Turbine Blade at Low Reynolds Numbers: Low-speed Investigation., ASME Paper GT 2005- 68892,2005
149 M. Vera, X. F. Zhang, H. Hodson, N. Harvey. Separation and Transition Control on an Aft-Loaded Ultra-High-Lift LP Turbine Blade at Low Reynolds Numbers: High-Speed Validation. ASME Paper GT2005-68893, 2005
150 R. Houtermans, T. Coton, T. Arts. Aerodynamic Performance of a Very High Lift LP Turbine Blade With Emphasis on Separation Prediction. ASMEPaper GT2003-38802, 2004
151 A. J. Glassman. Turbine Design and Application: Chapter 2, Basic Turbine Concept. NASA SP-290. 1994: 21~68
152 O. Zweifel. The Spacing of Turbo-Machine Blading, Especially with Large Angular Deflection. Brown Boveri Rev. 1945, 32(12): 436~444
153 周明,孙树栋,遗传算法原理及应用,北京: 国防工业出版社,1999: 130~138
2 C. H. Wu. A General Theory of Three Dimensional Flow in Subsonic and Supersonic Turbomachine in Radial, Axial and Mixed Flow Types. NASA TN-2604, 1952
3 I. A. Johnson, R. O. Bullock. Aerodynamic Design of Axial-Flow Compressors. NASA SP-36, 1965
4 J. H. Horlock, J. D. Denton. A Review of Some Early Design Practice using CFD and A Current Perspective. ASME paper GT2003-38973, 2003
5 A. J. Wennerstrom, G. R. Frost. Design of a 1500ft/sec, Transonic, High-Through-Flow, Single-Stage Axial-Flow Compressor with Low Hub/Tip Ratio. AFARL TR 76-59, 1976
6 黄洪雁,冯国泰,王仲奇,马云翔,林志鸿,闻雪友. 适用于舰用汽轮机的准三维设计体系. 热能动力工程. 1999,总第 80 期(14):119~121
7 J. D. Denton. The Calculation of Three Dimensional Viscous Flow Through Multistage Turbomachines. ASME paper 90-GT-19, 1990
8 R. H. Ni. Prediction of 3D Multi-Stage Turbine Flow Field Using a Multiple-Grid Euler Solver. AIAA paper 89-0203, 1989
9 W. N. Dawes. Towards Improved Through Flow Capability: The Use of 3D Viscous Flow Solvers in a Multistage Environment. ASME paper 90-GT-18, 1990
10 C. M. Rhie. Development and Application of a Multistage Navier-Stokes Solver, Part I: Multistage Modeling Using Body-Forces and Deterministic Stresses. ASME paper 95-GT-342, 1995
11 J. J. Adamczyk. Model Equation for Simulating Flows in Multistage Turbomachinery. ASME paper 85-GT-226, 1985
12 J. F. Thompson, N. P. Weatherill. Aspects of Numerical Grid Generation: Current and Art. AIAA Paper 93-3539, 1993
13 J. Dunham. CFD Validation for Propulsion System Components. AGARD-AR-355, 1998
14 S. K. Godunov. A Finite Diference Method for Numerical Computation of Discontinuous Solution of the Equations of Fluid Dynamics. Sov., Math., Sb.. 1959, 47:271~306
15 J. L. Steger, R. F. Warming. Flux Vector Splitting of the Inviscid Gasdynamic Equations with Application to Finite Diference Methods. Journal of Computational Physics.1981, 40:263~293
16 B. V. Leer. Flux Vector Spliting for the Euler Equations. Lecture Notes in Physics. 1982, 170:507-~512
17 P. L. Roe. Approximate Riemann Solvers, Parameter Vectors, and DiferenceSchemes. Journal of Computational Physics. 1981, 43:357~372
18 S. Osher, F. Solomon. Upwind Diference Schemes for Hyperbolic Systems of Conservation Laws. Math. Comp. 1982, 38: 285~292
19 A. Harten, P. D. Lax. Random Choice Finite Difference Schemes. SIAM Journal of Numerical Analysis. 1981, 18:289~315
20 B. V. Leer. Flux-Vector Spliting for the 1990s. NASA CP-3078, 1991
21 M. S. Liou, C. J. Stefen. A New Flux Spliting Scheme. Journal of Computational Physics. 1993, 107(1):23~39
22 Y. Wada, M. S. Liou. A Flux Spliting Scheme with High-Resolution and Robustness for Discontinuities. AIAA Paper 94-0083, 1994
23 M. S. Liou. A Sequel to AUSM: AUSM`. Journal of Computational Physics. 1996, 129( 1):364~382
24 K. H. Kim, J. H. Lee, O. H. Rho. An Improvement of AUSM Schemes by Introducing the Pressure-Based Weight Functions. Computers & Fluids. 1998, 27(1):311~346
25 A. S. Jameson, E. Turkel. Numerical Solutions of the Euler Equations by Finite Volume Methods with Runge-Kutta Time Stepping Schemes. AIAA Paper 81-1259, 1918
26 R. C. Swanson, E. Turkel. Artificial Dissipation and Central Diference Schemes for the Euler and N-S Equations. AIAA Paper 87-1107,1987
27 V. N. Vatsa, B. W. Wedan. Development of a Multigrid Code for 3-D Navier-Stokes Equations and its Application to a Grid Refinement Study. Computers & Fluids. 1990, 18(1):391~403
28 R. C. Swanson, E. Turkel. On Central Diference and Upwind Schemes. Journal of Computational Physics. 1992, 101( l):292~306
29 D. C. Wisler, J. D. Denton. Rotor 37 Blind Test Case. Presentation at ASME/IGTI International Gas Turbine Conference, Hague, The Netherlands, 1994
30 J. D. Denton. Lessons form Rotor 37. 3rd International Symposium on Experimental and Computational Aerothermodynamics of Internal Flows (ISAIF), Beijing, China, 1996
31 J. G. Marvin, G. P. Huang. Status and Future Directions for Turbulence Modeling. Proceeding of 7th ACFM, India, 1997
32 J. D. Denton. Loss Mechanisms in Turbomachines. ASME Paper 93-GT-435,1993
33 D. G. Ainley. The Performance of Axial Flow Turbines. Proe. Institution of Mechanical Engineers. 1948, 159:230~237
34 J. H. Horlock. Axial Flow Turbines. Butterworths Press, London, 1966
35 B. Lakshminarayana, J. G. Horlock. Review: Secondary Flows and Losses in Cascades and Axial-Flow Turbomachines. International Journal of Mechanical Sciences, 1963, 5: 397~409
36 J. A. Hesketh, H. Tritthard, P. Aubry. Modernization of Steam Turbines for Improved Performance. Symposium on Steam Turbines and Generaors,Monaco, GEC ALSTHOM, 1994
37 A. F. Carter, M. Platt, F. K. Lenherr. Analysis of Geometry and Design Point Performance of Axial Flow Turbines. I-Development of the Analysis Method and the Loss Coefficient Correlation. NASA CR-1181, 1968.
38 O. E. Bailje, R. L. Binsley. Axial Turbine Performance Evaluation: Part A-Loss-Geometry Relationships. Gas Turbines Power, 1968, 90:341~348.
39 H. R. M. Craig, H. J. A. Cox. Performance Estimation of Axial Flow Turbine. Proc. Instn. Mech. Engrs. 1970: 407~424
40 F. Martelli, A. Boretti. Development of an Experimental Correlation for Transonic Turbine Flow. ASME Paper 86-GT-108, 1986
41 H. W. Prust. Effect of Trailing Edge Geometry and Thickness on the Performance of Certain Turbine Stator Blading. NASA TN D6637, 1972
42 T. P. Moffitt, S. M. Nosek, R. J. Roelke. Turbine Aerodynamic Considerations for Advanced Turbine. NASA SP259, 1971
43 H. H. Hebbel. Uber den Einfluss den Machzahl und Reynadds-Zahl auf die Aerodynamischen Beiwerte Von Turbinenschaufelgittern. VDI Forschhft, 1960
44 M. E. Deich, G. A. Filoppor, L. Y. Lazarer. A Loss of Turbine Blade Cascades. G.E.G.B. Trans. 1965: 4563~4564
45 E. E. Flagg. Analytical Procedure and Computer Program for Determining the Off-Design Performance of Axial-Flow Turbines. NASA CR710, 1967
46 J. Hournouziadis, F. Buckl, P. Bergmann. The Development of the Profile Boundary layer in a Turbine Environment. ASME J. Turbomachinery. 1987, 109(2): 286~295.
47 P. Pucher, R. Goehl. Experimental Investigation of Boundary Layer Separation with Heated Thin-Film Sensor. ASME J. of Turbomachinery. 1987, 109(2): 303~309
48 J. Costa, T. Arts. Boundary Layer Transition under the Pressure of Discrete Frequencies in the Free stream Turbulence Spectrum. ASME paper 91-GT-355, 1991
49 H. D. Joslyn, R. P. Dring. Negative Incidence Flow over A Turbine Rotor Blade. ASME Paper 82-GT-23, 1982
50 R. P. Dring, H. D .Joslyn, L. W. Hardin, J. H. Wagner. Research on Turbine Rotor Stator Interaction and Rotor Negative Incidence Stall. AFWAL-TR-81-2114 (ADA116341), 1981
51 B. Lakshminarayana. Methods of Predicting the tip Clearance Effects in Axial Flow Turbomachinery. ASME Journal of Basic Engineering. 1970, 92: 467~482.
52 T. L. Sharma, Butler. Predictions of Endwall losses and Secondary Flows in Axial Flow Turbine Cascade. ASME Journal of Turbomachinery, 1987, 109:229~236
53 C. H. Sieverding, P. V. Bosch. The Use of Coloured Smoke to Visualize Secondary Flows in a Turbine-Blade Cascade. Journal of Fluid Mechanics.1983, 134:85~89
54 叶大均, 王仲奇. 叶轮机械真实流动损失机理及控制方法的研究., 国家自然科学基金会重大项目, 工程热物理中关键性问题的研究,第一部分—学术研究总结. 1992
55 A. Yamamoto, R. Yanagi. Production and Development of Secondary Flows and Losses within a Three-dimensional Turbine Stator Cascade. ASME Paper 85-GT-217, 1985
56 A. Yamamoto. Production and Development of Secondary Flows and Losses within Two Type of Straight Turbine Cascades, Part I: A Stator Case. ASME Paper 86-GT-184, 1986
57 J. Moore, A. Ransmary. Flow in a Turbine Cascade, Part I: Losses and Leading Edge Effects. ASME Paper 83-GT-68, 1983
58 W. R. Hawthrone. The Application of Secondary Flow Analysis to the Solution of Internal Flow Problems. Fluid Mechanics of Internal Flow, Elsevier, G. Sovran. 1974: 391~401
59 A. Klein. Untersuchungen uber die Einfluss der Zustr?mgrenzschicht auf die Sekund?rstr?mung in den Beschaufelungen von Axialturbinen. Forsch. Ing., 1966, Ba 32, Nr.6.
60 L. S. Langston. Cross Flow in a Turbine Cascade Passage. ASME Journal of Engineering for Power. 1980, 102: 866~874
61 H. P. Wang. Flow Visualization in a Linear Turbine Cascade of High Performance Turbine Blade. ASME Paper 95-GT-7, 1995
62 O. P. Sharma, T. L. Butler. Prediction of End Wall Losses and Secondary Flows in Axial Flow Turbine Cascade. ASME Journal of Turbomachinery. 1987, 109: 229~236
63 R. J. Goldstein, R. A. Spores. Turbulent Transport on the End Wall in the Region between Adjacent Turbine Blades. ASME Journal of Heat Transfer. 1988, 110: 862~869
64 J. D. Denton. Loss Mechanisms in Turbomachines Part II: Loss Generation in Turbomachines. Turbomachinery Blade Design Systems. Von Karman Institute for Fluid Dynamics. Belgium, 1999
65 J. Dunham, P. M. Came. Improvements to the Ainley & Mathieson Method of Turbine Performance Prediction. ASME J. of Eng. for Power. 1970, 92(3): 252~256
66 李喜宏,吴国华,彭泽涛. 压气机叶栅端壁流控制的实验研究. 航空动力学报. 1993,8(2): 143~147
67 W. D. Armstrong. The Secondary Flow in a Cascade of Turbines. R&M 2979. 1985
68 J. R. Turner. An Investigation of the End-Wall Boundary Layer of a Turbine Nozzle Cascade. Transactions of ASME 1957, 79:1801~1806.
69 H. Wolf. Die Randverluste in Geraden Schaufelgittern. Wiss. I. Tech. Hochsch. Dresden. 1961, 10(2):353~364.
70 S. Shahpar, L. Lapworth, T. Depablos, M. Taylor. A linear approach to the Multiparameter Design of Three-Dimensional Turbomachinery Blades. AIAA 99-0363, 37th AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, 1999
71 K. C. Giannakoglou. Designing Turbomaehinery Blades Using Evolutionary Methods. ASME Paper 99-GT-181, 1999
72 王正明,贾希诚. 正反问题数值解法相结合三维叶片的优化设计. 工程热物理学报. 2000, 21(5):567~569.
73 L. A. Catalano, A. Dadone. Progressive Optimization for the Efficient Design of 3D Cascades. AIAA Paper 2001-2578, 2001
74 W. T. Tiou, K. F. C. Yiu, M. Zangeneh. Application of Simulated Annealing to Inverse Design of Transonic Turbomachinery Cascades. Journal of Power and Energy. 2002, 216(1):59~73
75 曹志鹏,靳军,刘波,刘景新,王掩刚. 基于优化设计技术的叶型反方法改进设计. 航空动力学报. 2004,19(4):484~489.
76 刘仪,刘斌,向一敏,曹春丽. 十个参数的透平叶栅几何模型. 汽轮机技术. 1995,37 (4):196~198
77 祈明旭,刘斌,陈铁,刘万琨,赵萍. 一种新的轴流式透平叶栅叶型生成方法. 汽轮机技术. 1999,4(1):12~15
78 S. Goel, J.I. Cofer, H. Singh. Turbine airfoil design optimization. ASME Paper 96-GT-158, 1996
79 S. Pierret, R. A. Braembussehe. Turbomaehinery Blade Design Using A Navier-Stokes Solver And Artificial Neural Network. ASME Paper 98-GT-4,1998
80 S. Y. Lee, K.Y. Kim. Design Optimization of Axial Flow Compressor Blades with Three Dimensional Navier Stokes Solver. ASME Paper 2000-GT-0488, 2000
81 J. Chung, J. Shim, K. D. Lee. 3D Transonic Compressor Design Optimization with Quasi-3D Flow Physics. ASME 2000, FEDSM00-11075, 2000
82 A. Jameson. Aerodynamic Design via Control Theory. Technical Report 88-64, ICASE, 1988
83 J. Reuther, A. Jameson. Aerodynamic Shape Optimization of Wing and Wing-body Configurations Using Control Theory. AIAA Paper 95-0123, 1995
84 A. Jameson, N. A. Pierce, L. Martinelli. Optimum Aerodynamic Design Using the Navier-Stokes Equations. AIAA Paper 97-0101, 1997
85 J. H. Holland. Adaptive plants optimal for payoff-only environments. Proceeding of the Second Hawaii International Conference on System Sciences, 1969
86 J. H. Holland. Adaptation in Natural and Aritificial Systems. Ann Abor, The University of Michigan Press, 1975
87 L. J. Fogel, A. J. Owens, M. J. Walsh. Artificial Intelligence Through Simulated Evolution. New York, John Wiley, 1966
88 I. R. Evolitionsstrategie. Optimierung Technisher Systeme nach Prinzipien der Biologischen Evolution. Stuttgart, Fromman Holzboog Verlag, 1973.
89 H. P. Schwefel. Numerical Optimization of Computer Models. Chichester. Wiley, 1981.
90 K. D. Jong. Learning with genetic algorithms: an overview. Machiner Learning. 1988, 3: 121~138
91 A.Corana, M.Marchest, C.Martini, S.Ridella. Minimizing Multimodal Functions of Continuous Variables with the Simulated Annealing Algorithm. ACM Transactions on Mathematical Software. 1987, 13(3):262~280
92 W. W. McCulloch, W. Pitts. A Logic Calculus of the Ideas Imminent in Neurons Activity. Bulletin of Mathematical Biophysics.1943, 5: 495~500
93 F. Rosenblatt. The Perception: A Perceiving and Recognizing Automation. Cornell Aeronautical Laboratory Report, 85-406-1,1959
94 B. Widrow. An Adaptive Adaline Neuron Using Chemical Memistors. Stanford Electronics Laboratory Technical Report, 1960
95 J. J. Hopfield. Neural Networks and Physical Systems with Emergent Collective Computational Abilities. Proc Natl Acad Sci. USA. 1982, 79: 2552~2558.
96 J. J. Hopfield. Neurons with Graded Response Have Collective Computational Properties Like Those of Two-State Neuron. Proc Natl Acad Sci. USA. 1984, 81: 3088~3092
97 J. J. Hopfield, D. W. Tank. Neural Computation of Decision in Optimization Problem. Biol Cybern. 1982, 52: 141~152
98 史海秋,邓家禔. 涡轮叶片一维气动方案多学科优化设计. 制造业自动化. 2006,28(6):20~24
99 李军,丰镇平,沈祖达,常建忠. 透平跨音速叶栅的优化设计. 航空动力学报. 1997,12(3):287~290.
100 S.Pierret, R.A.V. Braembussche. Turbomachinery Blade Design Using a Navier-Stokes Solver and Artificial Neural Network. Journal of Turbomachinery. 1999, 121:326-332
101 B. H. Dennis, G.. S. Dulikravieh, Z. X. Han, Constrained Shape Optimization of Airfoil Cascades using a Navier-Stokes Solver and a Genetic/SQP Algorithm. ASME Paper 99-GT-441, 1999
102 M. Vascellari, R. Denos, R. V. Braembussche. Design of a Transonic High-pressure Turbine Stage 2D Section with Reduced Rotor/Stator Interaction. ASME Paper GT2004-53520., 2004
103 S. S. Talya, J. N. Rajadas, A. Chattopadhyay. Multidisciplinary Optimization of Gas Turbine Blade Design. AIAA Paper 98-4864, 1998
104 B. Buche, G. Guidati, P. Stoll. Automated Design Optimization of Compressor Blades for Stationary, Large-scale Turbomachinery. ASMEPaper GT-2003-38421, 2003
105 T. Sonoda, T. Arima, M. Olhofer. A study of advanced high loaded transonic turbine airfoils. ASME GT2004-53773, 2004
106 S. Pierret. Three-dimensional Blade Design by Means of an Artificial Neural Network and Navier-Stokes solver. Von Karman Institute Lecture Series on Turbomachinery Blade Design Systems, 1999
107 D. S. Shahpar. A Comparative Study of Optimization Methods for Aerodynamic Design of Turbomachinery blades. ASME Paper 2000-GT-523, 2000
108 W. Egartner. Working Range Optimization for Turbine and Compressor Bladeing. Journal of Computational and Applied Mathematics. 2000, 120: 59~65.
109 S. Shahpar. Three Dimensional Design and Optimisation of Turbomachinery Blades using the Navier-Stokes Equations. ISABE 2001-1053, 2001
110 N. Papila, W. Shyy, L. Griffin, D. J. Dorney. Shape Optimization of Supersonic Turbines Using Response Surface and Neural Network Methods. AIAA Paper 2001-1065, 2001
111 A. Oyama, M. S. Liou, S. Obayashi. Transonic Axial Flow Blade Shape Optimizatin Using Evolutionary Algorithm and Three-dimensional Navier-Stokes Solver. AIAA Paper 2002-5642, 2002
112 S. Kammerer, J. F. Mayer, M. Paffrath. Three-dimensional optimization of turbomachinery bladings using sensitivity analysis. ASME Paper GT2003-38037, 2003
113 S. Burguburu, A. L. Pape. Improved aerodynamic design of turbomachinery bladings by numerical optimization. Aerospace Science Technology. 2003, 7: 277~287
114 A. Demeulenaere, A. Ligout, C. Hirsch. Application of Multipoint Optimization to the Design of Turbomachinery Blades. ASME Paper 2004-GT-53110, 2004
115 A. Arnone, D. Bonaiuti, A. Focacci. Parametric optimization of a high-lift turbine vane. ASME Paper GT2004-54308, 2004
116 L. Moroz, Y. Govoruschenko, P. Pagur. Axial Turbine Stages Design: 1D/2D/3D Simulation, Experiment, Optimization-Design of Single Stage Test Air Turbine Models and Validation of 1D/2D/3D Aerodynamic Computation Results against Test Data. ASME Paper GT2005-68614, 2005
117 M. Hasenjager, B. Sendhoff, T. Sonoda, T. Arima. Three Dimensional Aerodynamic Optimization for an Ultra-low Aspect Ratio Transonic Turbine Stator Blade. ASME Paper GT2005-68680, 2005
118 Y. Y. Lai, X. Yuan. Blade Design With Three-Dimensional Viscous Analysis and Hybrid Optimization Approch. AIAA Paper 2002-5658, 2002
119 赖宇阳,袁新. 基于遗传算法和逐次序列二次规划的叶栅基迭优化. 工程热物理学报. 2003, 24(1):52~54.
120 虞跨海, 李立州, 王婧超, 岳珠峰. 涡轮叶片三维气动优化设计. 机械设计. 2005, 22(11):31~35
121 林智荣,石板浩一,袁新. 燃气透平末级及扩压器的联合优化. 工程热物理学报. 2005, 26( 1):47~50.
122 吴立强, 尹泽勇, 蔡显新. 航空发动机涡轮叶片的多学科设计优化. 航空动力学报. 2005, 20( 10):795~800
123 赵洪雷,王松涛,李东平,韩万金. 某型其冷涡轮级的三维优化设计. 热能动力工程. 2006,21(5):450~455.
124 王婧超, 李立州, 岳珠峰. 涡轮叶片的多学科设计优化系统. 航空动力学报. 2007,22(1):23~29.
125 冯国泰, 顾中华, 王松涛. 具有弯扭掠叶片流场结构分析能力的燃气涡轮三维设计体系——弯扭掠叶片设计体系与设计思想研究之一. 航空发动机. 2002 , 3:4~8.
126 G. Groschup. Stromungstechnische Unterscuhungeiner Axialturbinenstufeim Vergleichzum Verhalten der ebenen Gitterihrer Beschaufelung. Doktor Ingenieur Dissertation Technical University of Hannover, 1977.
127 L. Fottner. Test Cases f or Computation of Internal Flows in Aero Engine Components. AGARD-AR-275, 1990.
128 P. R. Spalart, S. R. Allmaras. A One-Equation Turbulence Model for Aerodynamic Flows. AIAA Paper 92-0439, 1992
129 袁宁,张振家,顾中华,冯国泰. 应用 S2 流面准三元计算程序分析小型发动机的跨音压气机气动特性. 推进技术,1996,17(6):6~11
130 黄家骅,于廷臣,冯国泰. 某小型涡扇发动机全流道准三维数值解法. 航空发动机. 2005,31( 2):42~45.
131 J. X. Su, G. T. Fengi, K. Hu. A Direct problem Method on S2 Stream Surface For Transonic Compressor In Aeroengine. Corpus of the Second Sino-Soviet Space Navigation Proseminar,1992.
132 S. Ito, E. R. G. Eckert, R. J. Goldstein. Aerodynamic Loss in a Gas Turbine Stage with Film Cooling. Journal of Engineering for Power. 1980, 102:1~7
133 B. Lakshminarayana. Fluid Dynamics and Heat. Transfer of Turbimachinery. 1996, 4: 672~679
134 N. Wei,S. Svensdotter. Investigation of the Flow Trough an Axial Turbine Stage, Licentiate Thesis Chair of Heat and Power Technology. KTH, ISRN KTH/KRV/R-95/1-SE, 1995.
135 D. G.. Ainley,G.. C. R. Mathieson, A method of Performance Estimation for Axial-Flow Turbines, British Aeronautical Research Council, R&M 2974 , 1951.
136 S. C. Kacker, U. Okapuu, A Mean Line Prediction Method for Axial Flow Turbine Efficiency, ASME 81-GT-58, 1981
137 J. D. Denton. Axial Turbine Aerodynamic Design. Leture Note for an Advanced Course on Turbomachinery Aerodynamic, University of Cambridge, UK, 1994.
138 W. L. Stewart, W. J. Whitney, R. Y. Wong. A study of Boundary-Layer Characteristics of Turbomachine Blade Rows and Their Relation to Over-All Blade Loss. Transactions of the ASME, 1960, 82: 580~592
139 P. Zehner. Calculation of four-Quadrant Characteristics of Turbines, ASME 80-GT-2, 1980
140 王仲奇,秦仁. 透平机械原理,机械工业出版社,1979 : 79~85
141 Z. Q. Wang, S. K. Lai, W. Y. Xu. Aerodynamic Calculation of Turbine Stator Cascades with Curvilinear Leaned Blades and Some Experimental Results. Symposium paper of 5-ty ISABE, India, 1981
142 W. J. Han, Z. Q. Wang. Experimental Studies on the Mechanism and Control of Secondary Flow Losses in Turbine Cascades. Journal of Thermal Science. 1992,4(1):218~231
143 Z. Q. Wang, W. J. Han. Effect of Leaning and Curving of Blades with High Turning Angles on the Aerodynamics Characteristics of Turbine Rectangular Cascade. Journal of Turbomachinery. 1994, 116:417~424
144 R. Vazquez, D. Cadrecha, D. Torre. High Stage Loading Low Pressure Turbines. A New Proposal for an Efficiency Chart. ASME Paper GT2003-38374, 2003
145 J. Q. Zhu, S. Sjolander. Improved Profile Loss and Deviation Correlation for Axial Turbine Blade Rows. ASME Paper GT2005-69077, 2005
146 I. Vlizar, P. Gonzalez. Aerodynamic Design of a New Five Stage Low Pressure Turbine for the Rolls Royce Trent 500 Turbofan. ASME Paper 2001- GT-0440, 2001.
147 R. T. Howell, H. P. Hodson, V. Schulte, H. P. Schiffer, F. Haselbach, N. W. Harley. Boundary Layer Development in the BR710 and BR715 LP Turbines — the Implementation of High Lift and Ultra High Lift Concepts. ASME Paper 2001- GT-0441, 2001
148 X. F. Zhang, M. Vera, H. Hodson. Separation and Transition Control on an Aft-loaded Ultra-high-lift LP Turbine Blade at Low Reynolds Numbers: Low-speed Investigation., ASME Paper GT 2005- 68892,2005
149 M. Vera, X. F. Zhang, H. Hodson, N. Harvey. Separation and Transition Control on an Aft-Loaded Ultra-High-Lift LP Turbine Blade at Low Reynolds Numbers: High-Speed Validation. ASME Paper GT2005-68893, 2005
150 R. Houtermans, T. Coton, T. Arts. Aerodynamic Performance of a Very High Lift LP Turbine Blade With Emphasis on Separation Prediction. ASMEPaper GT2003-38802, 2004
151 A. J. Glassman. Turbine Design and Application: Chapter 2, Basic Turbine Concept. NASA SP-290. 1994: 21~68
152 O. Zweifel. The Spacing of Turbo-Machine Blading, Especially with Large Angular Deflection. Brown Boveri Rev. 1945, 32(12): 436~444
153 周明,孙树栋,遗传算法原理及应用,北京: 国防工业出版社,1999: 130~138