ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Reliability Analysis for HPT Blade-tip Radial Running Clearance Based on DCRSM
Received date: 2012-10-08
Revised date: 2012-12-25
Online published: 2012-12-27
Supported by
National Natural Science Foundation of China (51175017);Innovation Foundation of BUAA for Ph.D.Graduates;Specialized Research Fund for the Doctoral Program of Higher Education
In order to design more effectively aeroengine high pressure turbine (HPT) blade-tip radial running clearance (BTRRC), a BTRRC reliability analysis is accomplished from a probabilistic perspective in this paper. Distributed collaborative response surface method (DCRSM) with high accuracy and high efficiency is proposed for reliability analysis according to the structural features of BTRRC. The mathematical model of DCRSM is established based on the quadratic response surface function. The DCRSM is applied to the reliability analysis of an aeroengine HPT BTRRC to verify the advantages. The reliability analysis results show that the reliability of BTRRC is 0.996 8 when the static blade-tip clearance δ=1.86 mm, which is appropriate in the BTRRC and aeroengine design for satisfying engineering requirements while considering synthetically the efficiency and reliability of an aeroengine. As demonstrated in the comparison of methods, the DCRSM can not only make a difficult problem easy to resolve, but also improve greatly computation speed, save computing time and ameliorate computational efficiency while keeping calculation accuracy. Therefore, DCRSM is fully verified to be feasible and effective in BTRRC reliability analysis. Meanwhile, the present study provides some useful insight into designing and optimizing more effectively complex machinery reliability schemes in general.
FEI Chengwei , BAI Guangchen . Reliability Analysis for HPT Blade-tip Radial Running Clearance Based on DCRSM[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2013 , 34(9) : 2141 -2149 . DOI: 10.7527/S1000-6893.2013.0342
[1] Lattime S B, Steinetz B M. High pressure turbine engine clearance control systems: current practices and future directions. Journal of Propulsion and Power, 2004, 20(2): 302-311.
[2] Hennecke D K, Trappmann K. Turbine tip clearance control in gas turbine engines. NASA, N83-229254, 1983.
[3] Lee S, Yi C. Statistical tolerance and clearance analysis for assembly. Proceedings of the 1996 IEEE/RSJ International Conference, 1996: 688-695.
[4] Pilidis P, Maccallum N R L. Models for predicting tip clearance changes in gas turbines. NASA, N83-229258, 1983.
[5] NSSA Glenn Research Center. HTP clearance control. NASA, CR-2005-213970, 2005.
[6] Lattime S B, Steinetz B M, Robbie M G. Test rig for evaluating active turbine blade tip clearance control concepts. Journal of Propulsion and Power, 2005, 21(3): 552-563.
[7] Jia B H, Zhang X D. Study on effect of rotor vibration on tip clearance variation and fast active control of tip clearance. Advanced Material Research, 2010, 139-141(1): 2469-2472.
[8] Annette E N, Christoph W M, Stephan S. Modeling and validation of the thermal effects on gas turbine transients. Journal of Engineering for Gas Turbines and Power, 2005, 127(3): 564-572.
[9] Forssell L S. Flight clearance analysis using global nonlinear optimisation-based search algorithms. Proceedings of the AIAA Guidance, Navigation, and Control Conference, 2003: 1-8.
[10] Kypuros J A, Melcher K J. A reduced model for prediction of thermal and rotational effects on turbine tip clearance. NASA-TM-2003-212226, 2003.
[11] Gole N, Kumar A, Narasimhan V. Health risk assessment and prognosis of gas turbine blades by simulation and statistical methods. Proceedings of the Canadian Conference on Electrical and Computer Engineering, 2008: 1087-1092.
[12] Qi W K, Chen W. Tip clearance numerical analysis of aeroengine HPT. Journal of Nanjing University of Aeronautics & Astronautics, 2003, 35 (1): 63-67. (in Chinese) 漆文凯, 陈伟. 某型航空发动机高压涡轮叶尖间隙数值分析. 南京航空航天大学学报, 2003, 35(1): 63-67.
[13] Guo S F, Xu B. Effect of temperature and rotational speed on radial clearance of turbine blade tip. Journal of Propulsion Technology, 2004, 21(4): 51-53. (in Chinese) 郭淑芬, 徐波. 温度与转速对涡轮叶尖径向间隙的影响. 推进技术, 2004, 21(4): 51-53.
[14] Qi X M, Piao Y, Zhu J H, et al. 3-D numerical analysis of the tip clearance of an aero-engine high pressure turbine. Journal of Aerospace Power, 2008, 23(5): 904-908. (in Chinese) 岂兴明, 朴英, 祝剑虹, 等. 某型航空发动机高压涡轮叶顶间隙三维数值分析. 航空动力学报, 2008, 23(5): 904-908.
[15] Gurvich M R, Pipes R B. Probabilistic strength analysis of four-directional laminated composites. Composites Science and Technology, 1996, 56(6): 649-656.
[16] Pugh C E, Bass B R, Dickson T L. Role of probabilistic analysis in integrity assessments of reactor pressure vessels exposed to pressurized thermal-shock conditions. Engineering Failure Analysis, 2007, 14(3): 501-517.
[17] Lu Q, Low B K. Probabilistic analysis of underground rock excavations using response surface method and SORM. Computers and Geotechnics, 2011, 38(8): 1008-1021.
[18] Kartal M E, Basaga H B, Bayraktar A. Probabilistic nonlinear analysis of CFR dams by MCS using response surface method. Applied Mathematical Modelling, 2011, 35(6): 2752-2770.
[19] Liu Z Q. Probability design method of margins of safety for reliability characteristic parameters of space mechanical products. Chinese Space Science and Technology, 2007(4): 34-43. (in Chinese) 刘志全. 航天器机械可靠性特征量裕度的概率设计方法. 中国空间科学技术, 2007(4): 34-43.
[20] Fitzpatrick C K, Baldwin M A, Rullkoetter P J, et al. Combined probabilistic and principal component analysis approach for multivariate sensitivity evaluation and application to implanted patellofemoral mechanics. Journal of Biomechanics, 2011, 44(1): 13-21.
[21] Alessandro Z, Michele B, Andrea D A, et al. Probabilistic analysis for design assessment of continuous steel-concrete composite girders. Journal of Constructional Steel Research, 2010, 66(7): 897-905.
[22] Nakamura T, Fujii K. Probabilistic transient thermal analysis of an atmospheric reentry vehicle structure. Aerospace Science and Technology, 2006, 10(4): 346-354.
[23] Tan X H, Bi W H, Hou X L, et al. Reliability analysis using radial basis function networks and support vector machines. Computers and Geotechnics, 2011, 38(2): 178-186.
[24] Cho S E. Probabilistic stability analyses of slopes using the ANN-based response surface. Computers and Geotechnics, 2009, 36(5): 787-797.
[25] Eom Y S, Yoo K S, Park J Y, et al. Reliability-based topology optimization using a standard response surface method for three-dimensional structures. Structural and Multidisciplinary Optimization, 2011, 43(2): 287-295.
[26] Li C, Han X. Analysis of reliability sensitivity for gear engagement based on response surface method. Journal of Aerospace Power, 2011, 26(3): 711-715. (in Chinese) 李昌, 韩兴. 基于响应面法齿轮啮合传动可靠性灵敏度分析. 航空动力学报, 2011, 26(3): 711-715.
[27] Huang Z J, Wang C G, Chen J, et al. Optimal design of aeroengine turbine disc based on kriging surrogate models. Computers & Structures, 2011, 89(1-2): 27-37.
[28] Cardoso J B, Almeida J R, Dias J M, et al. Structure reliability analysis using Monte Carlo simulation and neural networks. Advances in Engineering Software, 2008, 39(6): 505-513.
[29] Deng J, Gu D S, Li X B, et al. Structural reliability analysis for implicit performance functions using artificial neural network. Structural Safety, 2005, 27(1): 25-48.
/
〈 | 〉 |