Reliability and sensitivity analyses of HPT blade-tip radial running clearance using multiply response surface model

Xue Zhai , Cheng-wei Fei , Qing-gang Zhai , Jian-jun Wang

Journal of Central South University ›› 2014, Vol. 21 ›› Issue (11) : 4368 -4377.

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Journal of Central South University ›› 2014, Vol. 21 ›› Issue (11) : 4368 -4377. DOI: 10.1007/s11771-014-2437-y
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Reliability and sensitivity analyses of HPT blade-tip radial running clearance using multiply response surface model

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Abstract

To reasonably design the blade-tip radial running clearance (BTRRC) of high pressure turbine and improve the performance and reliability of gas turbine, the multi-object multi-discipline reliability sensitivity analysis of BTRRC was accomplished from a probabilistic prospective by considering nonlinear material attributes and dynamic loads. Firstly, multiply response surface model (MRSM) was proposed and the mathematical model of this method was established based on quadratic function. Secondly, the BTRRC was decomposed into three sub-components (turbine disk, blade and casing), and then the single response surface functions (SRSFs) of three structures were built in line with the basic idea of MRSM. Thirdly, the response surface function (MRSM) of BTRRC was reshaped by coordinating SRSFs. From the analysis, it is acquired to probabilistic distribution characteristics of input-output variables, failure probabilities of blade-tip clearance under different static blade-tip clearances δ and major factors impacting BTRRC. Considering the reliability and efficiency of gas turbine, δ=1.87 mm is an optimally acceptable option for rational BTRRC. Through the comparison of three analysis methods (Monte Carlo method, traditional response surface method and MRSM), the results show that MRSM has higher accuracy and higher efficiency in reliability sensitivity analysis of BTRRC. These strengths are likely to become more prominent with the increasing times of simulations. The present study offers an effective and promising approach for reliability sensitivity analysis and optimal design of complex dynamic assembly relationship.

Keywords

high pressure turbine / blade-tip radial running clearance / reliability sensitivity analysis / multiply response surface method

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Xue Zhai, Cheng-wei Fei, Qing-gang Zhai, Jian-jun Wang. Reliability and sensitivity analyses of HPT blade-tip radial running clearance using multiply response surface model. Journal of Central South University, 2014, 21(11): 4368-4377 DOI:10.1007/s11771-014-2437-y

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References

[1]

GoleN, KumarA, NarasimhanV. Health risk assessment and prognosis of gas turbine blades by simulation and statistical methods [C]. Canadian Conference on Electrical and Computer Engineering, Niagara Falls, Canada, 20081087-1092

[2]

LattimeS B, SteinetzB M, RobbieM G. Test rig for evaluating active turbine blade tip clearance control concepts [J]. Journal of Propulsion and Power, 2005, 21(3): 552-563

[3]

LattimeS B, SteinetzB M. Turbine engine clearance control systems: Current practices and future directions [J]. Journal of Propulsion and Power, 2004, 20(2): 302-311

[4]

PilidisP, MaccallumN R LModels for predicting tip clearance changes in gas turbines [R], 1983

[5]

KypurosJ A, MelcherK JA reduced model for prediction of thermal and rotational effects on turbine tip clearance [R], 2003

[6]

AnnetteE N, ChristophW M, StehanS. Modeling and validation of the thermal effects on gas turbine transients [J]. Journal of Engineering for Gas Turbines and Power, 2005, 127(3): 564-572

[7]

JiaB-h, ZhangX-dong. Study on effect of rotor vibration on tip clearance variation and fast active control of tip clearance [J]. Advanced Material Research, 2010, 139–141(1): 2469-2472

[8]

ForssellL S. Flight clearance analysis using global nonlinear optimisation-based search algorithms [C]. AIAA Guidance, Navigation, and Control Conference and Exhibit, 2003, Austin, Texas, AIAA: 1-8

[9]

NASA Glenn Research CenterHTP clearance control [R], 2005

[10]

HuD Y, WangR Q, TaoZ. Probabilistic design for turbine disk at high temperature [J]. Aircraft Engineering and Aerospace Technology, 2011, 83(4): 199-207

[11]

LvQ, LowB K. Probabilistic analysis of underground rock excavations using response surface method and SORM [J]. Computers and Geotechnics, 2011, 38(8): 1008-1021

[12]

SungE C. Probabilistic stability analyses of slopes using the ANN-based response surface [J]. Computers and Geotechnics, 2009, 36(5): 787-797

[13]

MuratE K, HasanB B, AlemdarB. Probabilistic nonlinear analysis of CFR dams by MCS using response surface method [J]. Applied Mathematical Modelling, 2011, 35(6): 2752-2770

[14]

FitzpatrickC K, BaldwinM A, RullkoetterP J. Combined probabilistic and principal component analysis approach for multivariate sensitivity evaluation and application to implanted patellofemoral mechanics [J]. Journal of Biomechanics, 2011, 44(1): 13-21

[15]

LiZ X, LiJ J, BaoyinH X. Sensitivity analysis for type of statically stable sailcrafts [J]. Acta Mechanica Sinica, 2012, 28(2): 532-542

[16]

AlessandroZ, MicheleB, AndreaD A. Probabilistic analysis for design assessment of continuous steel-concrete composite girders [J]. Journal of Constructional Steel Research, 2010, 66(27): 897-905

[17]

ToshiyaN, KenjiF. Probabilistic transient thermal analysis of an atmospheric reentry vehicle structure [J]. Aerospace Science and Technology, 2006, 10(4): 346-354

[18]

EomY S, YooK S, ParkJ Y. Reliability-based topology optimization using a standard response surface method for three-dimensional structures [J]. Structural and Multidisciplinary Optimization, 2011, 43(2): 287-295

[19]

LiC, HanXing. Analysis of reliability sensitivity for gear engagement based on response surface method [J]. Journal of Aerospace Power, 2011, 26(3): 711-715

[20]

HuangZ J, WangC G, ChenJ. Optimal design of aeroengine turbine disc based on kriging surrogate models [J]. Computers and Structures, 2011, 89(1): 27-37

[21]

PellissettiM F, SchuellerG I, PradlwarterH J, CalviA, FransenS, KleinM. Reliability analysis of spacecraft structures under static and dynamic loading [J]. Computers & Structures, 2006, 84(21): 1313-1325

[22]

ZhangC-y, BaiG-chen. Extremum response surface method of reliability analysis on twolink flexible robot manipulator [J]. Journal of Central South University, 2012, 19(1): 101-107

[23]

FeiC-w, BaiG-chen. Distributed collaborative extremum response surface method for mechanical dynamic assembly reliability analysis [J]. Journal of Central South University, 2013, 20(9): 2414-2422

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