| [1] Cao Z, Gao X, Liu B. Control mechanisms of endwall profiling and its comparison with bowed blading on flow field and performance of a highly-loaded compressor cas-cade[J]. Aerospace Science and Technology 2019; 95:105472.[2] 刘佳鑫, 于贤君, 孟德君, 等. 高压压气机出口级叶型加工偏差特征及其影响[J]. 航空学报. 2021; 42(02):348-64.Liu J, Yu X, Meng D, et al. State and effect of manufacture deviations of compressor blade in high-pressure compressor outlet stage[J]. Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica 2021; 42(2).[3] Xia Z, Luo J, Liu F. Performance impact of flow and geometric variations for a turbine blade using an adaptive NIPC method[J]. Aerospace Science and Technology 2019; 90:127-39.[4] Goodhand MN, Miller RJ, Hang WL. The Impact of Geometric Variation on Compressor Two-Dimensional In-cidence Range[J]. Journal of Turbomachinery; 137(2):021007.1-.7.[5] 郑新前, 王钧莹, 黄维娜, 等. 航空发动机不确定性设计体系探讨[J]. 航空学报.2022; 1-19.Zheng X, Wang J, Huang W, et la. Discussion on uncer-tainty-based design system for aeroengines[J]. Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica 2022; 1-19.[6] 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 Aeronautics 2021; 34(6):220-32.[7] Schnell R, Lengyel-Kampmann T, Nicke E. On the Impact of Geometric Variability on Fan Aerodynamic Per-formance, Unsteady Blade Row Interaction, and Its Me-chanical Characteristics [J]. Journal of Turbomachinery 2014; 136(9).[8] Wang J, Zheng X. Review of Geometric Uncertainty Quantification in Gas Turbines[J]. Journal of Engineering for Gas Turbines and Power 2020; 142(7).[9] Garzon VE, Darmofal DL. Impact of Geometric Varia-bility on Axial Compressor Performance[J]. Journal of Tur-bomachinery 2003; 125(4):692-703.[10] Luo J, Liu F. Statistical evaluation of performance impact of manufacturing variability by an adjoint meth-od[J]. Aerospace Science and Technology 2018; 77:471-84.[11] Xiu D, Karniadakis GE. The Wiener--Askey Polynomi-al Chaos for Stochastic Differential Equations[J]. SIAM Journal on Scientific Computing 2002; 24(2):619-44.[12] Wunsch D, Hirsch C, Nigro R, et al. Quantification of Combined Operational and Geometrical Uncertainties in Turbo-Machinery Design[C]. ASME Turbo Expo 2015: Turbine Technical Conference and Exposition. 2015.[13] WANG T, HE X, WANG J, et al. Detail fatigue rating method based on bimodal Weibull distribution for DED Ti-6.5Al-2Zr-1Mo-1V titanium alloy[J]. Chinese Journal of Aeronautics 2022; 35(04):281-91.[14] Kiureghian AD, Liu PL. Structural Reliability under Incomplete Probability Information[J]. Journal of Engineer-ing Mechanics 1986; 112(1):85-104.[15] Oladyshkin S, Nowak W. Incomplete statistical infor-mation limits the utility of high-order polynomial chaos expansions[J]. Reliability Engineering & System Safety 2018; 169:137-48.[16] Oladyshkin S, Class H, Helmig R, et al. A concept for data-driven uncertainty quantification and its application to carbon dioxide storage in geological formations[J]. Advanc-es in Water Resources 2011; 34(11):1508-18.[17] Oladyshkin S, Schr?der P, Class H, et al. Chaos Expan-sion based Bootstrap Filter to Calibrate CO2 Injection Models[J]. Energy Procedia 2013; 40:398-407.[18] Wang F, Xiong F, Jiang H, et al. An enhanced data-driven polynomial chaos method for uncertainty propaga-tion[J]. Engineering Optimization 2018; 50(2):273-92.[19] Ahlfeld R, Belkouchi B, Montomoli F. SAMBA: Sparse Approximation of Moment-Based Arbitrary Polyno-mial Chaos[J]. Journal of Computational Physics 2016; 320:1-16.[20] Wang X, Liu RP, Wang X, et al. A Data-Driven Uncer-tainty Quantification Method for Stochastic Econom-ic Dispatch[J]. IEEE Transactions on Power Systems 2022; 37(1):812-5.[21] Guo L, Liu Y, Zhou T. Data-driven polynomial chaos expansions: A weighted least-square approximation[J]. Journal of Computational Physics 2019; 381:129-45.[22] Wiener N. The Homogeneous Chaos[J]. Journal of Computational Physics 1938; 60(4):897-936.[23] Hosder S, Walters R, Balch M. Efficient Sampling for Non-Intrusive Polynomial Chaos Applications with Multi-ple Uncertain Input Variables[C]. 48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dy-namics, and Materials Conference: American Institute of Aeronautics and Astronautics, 2007.[24] Chuang-Stein C. Sample size and the probability of a successful trial[J]. Pharmaceutical statistics 2006; 5(4):305-9.[25] Razali NM, Wah YB. Power comparisons of shapiro-wilk, kolmogorov-smirnov, lilliefors and anderson-darling tests[J]. Journal of statistical modeling and analytics 2011; 2(1):21-33.[26] 蔡明, 高丽敏, 刘哲, 等. 不同条件下平面叶栅风洞流场品质的实验研究[J]. 推进技术 2021; 42(05):1162-70.Cai M, Gao L, Liu Z, et al. Experimental Study on Flow Field Quality of Linear Cascade Wind Tunnel under Different Conditions[J]. Tuijin Jishu/Journal of Propulsion Technology 2021; 42(5):1162-70.[27] 蔡明, 高丽敏, 刘哲, 等. 基于抽吸的亚声速平面叶栅风洞流场品质控制研究[J]. 推进技术 2021; 42(09):1985-92.Cai M, Gao L, Liu Z, et al. Flow Field Quality Control of Subsonic Linear Cascade Wind Tunnel Based on Suction[J]. Tuijin Jishu/Journal of Propulsion Technology 2021; 42(9):1985-92.[28] Ruiyu L, Limin G, Lei Z, et al. Dominating Unsteadi-ness Flow Structures in Corner Separation Under High Mach Number[J]. AIAA Journal 2019; 57(7):2923-32.[29] Goodhand MN, Miller RJ. Compressor Leading Edge Spikes: A New Performance Criterion[J]. Journal of Tur-bomachinery 2010; 133(2). |
CJA
