Transient probabilistic analysis for turbine blade-tip radial clearance with multi-component and multi-physics fields based on DCERSM

被引:31
作者
Fei, Cheng-Wei [1 ,2 ]
Choy, Yat-Sze [1 ]
Hu, Dian -Yin [2 ]
Bai, Guang-Chen [2 ]
Tang, Wen-Zhong [3 ]
机构
[1] Hong Kong Polytech Univ, Dept Mech Engn, Hong Kong, Hong Kong, Peoples R China
[2] Beihang Univ, Sch Energy & Power Engn, Beijing 100191, Peoples R China
[3] Beihang Univ, Sch Comp Engn & Sci, Beijing 100191, Peoples R China
基金
中国国家自然科学基金;
关键词
High pressure turbine; Blade-tip radial running clearance; Dynamic probabilistic analysis; Distributed collaborative extremum response surface method; Multi-object multi-disciplinary; RESPONSE-SURFACE METHOD; SUPPORT VECTOR MACHINE; RELIABILITY-ANALYSIS; OPTIMAL-DESIGN;
D O I
10.1016/j.ast.2015.11.025
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Against the background of the probabilistic analysis for High Pressure Turbine (HPT) Blade-tip Radial Running Clearance (BRRC) to achieve the high-performance and high-reliability of aeroengine, Distributed Collaborative Extremum Response Surface Method (DCERSM) was proposed for the dynamic probabilistic analysis of complex turbomachinery on the foundation of quadratic polynomials response surface model. On the basis of deeply investigating Extremum Response Surface Method (ERSM), the mathematical model of DCERSM was established based on quadratic polynomial function. As illustrated in BRRC transient probabilistic analysis with multiple components and multi-physics fields based on DCERSM, blade-tip radial static clearance delta = 1.82 mm is advisable synthetically considering the reliability and working efficiency of gas turbine. The reliability, distribution characteristics and failure probability of BRRC are obtained. Besides, rotational speed omega and gas temperature T are the most important factors and expansivity coefficients and surface coefficients of heat transfer show also important influence on BRRC variation. Through the comparison of three methods (DCERSM, ERSM, Monte Carlo method), it is demonstrated that DCERSM reshapes the possibility of complex turbomachinery probabilistic analysis and improves computing efficiency while preserving the accuracy. DCERSM offers a useful insight for BRRC dynamic reliability design and optimization with multi-object and multi-discipline. The efforts of this study also enrich the theory and method of mechanical reliability design. (C) 2015 Elsevier Masson SAS. All rights reserved.
引用
收藏
页码:62 / 70
页数:9
相关论文
共 29 条
[1]   Probabilistic stability analyses of slopes using the ANN-based response surface [J].
Cho, Sung Eun .
COMPUTERS AND GEOTECHNICS, 2009, 36 (05) :787-797
[2]   Reliability-based topology optimization using a standard response surface method for three-dimensional structures [J].
Eom, Young-Sop ;
Yoo, Kwang-Sun ;
Park, Jae-Yong ;
Han, Seog-Young .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2011, 43 (02) :287-295
[3]  
Fei C.W., 2015, ASCE J AEROSP ENG, V28
[4]   A dynamic probabilistic design method for blade-tip radial running clearance of aeroengine high-pressure turbine [J].
Fei, Cheng-Wei ;
Tang, Wen-Zhong ;
Bai, Guang-chen ;
Chen, Zhi-Ying .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2015, 229 (10) :1861-1872
[5]   Nonlinear dynamic probabilistic design of turbine disk-radial deformation using extremum response surface method-based support vector machine of regression [J].
Fei, Cheng-Wei ;
Tang, Wen-Zhong ;
Bai, Guang-Chen .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING, 2015, 229 (02) :290-300
[6]   Novel method and model for dynamic reliability optimal design of turbine blade deformation [J].
Fei, Cheng-Wei ;
Tang, Wen-Zhong ;
Bai, Guang-Chen .
AEROSPACE SCIENCE AND TECHNOLOGY, 2014, 39 :588-595
[7]   Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression [J].
Fei, Cheng-Wei ;
Bai, Guang-Chen .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2014, 49 (1-2) :196-208
[8]   Nonlinear Dynamic Probabilistic Analysis for Turbine Casing Radial Deformation Using Extremum Response Surface Method Based on Support Vector Machine [J].
Fei, Chengwei ;
Bai, Guangchen .
JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS, 2013, 8 (04)
[9]   Extremum selection method of random variable for nonlinear dynamic reliability analysis of turbine blade deformation [J].
Fei, Chengwei ;
Bai, Guangchen .
PROPULSION AND POWER RESEARCH, 2012, 1 (01) :58-63
[10]  
Forssell LS, 2003, AIAA GUID NAV CONTR, P1