Research Papers: Gas Turbines: Structures and Dynamics

Multivariate Response Rotordynamic Modeling and Sensitivity Analysis of Tilting Pad Bearings

[+] Author and Article Information
Leonardo Urbiola-Soto

Faculty of Engineering,
Center for Advanced Technology,
Universidad Nacional Autónoma
de México (UNAM),
Boulevard Juriquilla 3001,
Queretaro, MX 76230
e-mail: leourbiola@gmail.com

Contributed by the Structures and Dynamics Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received January 3, 2017; final manuscript received October 12, 2017; published online April 10, 2018. Assoc. Editor: Jerzy T. Sawicki.

J. Eng. Gas Turbines Power 140(7), 072502 (Apr 10, 2018) (10 pages) Paper No: GTP-17-1003; doi: 10.1115/1.4038549 History: Received January 03, 2017; Revised October 12, 2017

Achieving an optimal design of journal bearings is a very challenging effort due to the many input and output variables involved, including rotordynamic and tribological responses. This paper demonstrates the use of a multivariate response modeling approach based on response surface design of experiments (RSDOE) to design tilting pad bearings. It is shown that an optimal configuration can be achieved in the early stages of the design process while substantially reducing the amount of calculations. To refine the multivariate response model, statistical significance of the factors was assessed by examining the test's p-value. The effect coefficient calculation complemented the statistical hypothesis testing as an overall quantitative measure of the strength of factors, namely; main effects, quadratic effects, and interactions between variables. This provided insight into the potential nonlinearity of the phenomena. Once arriving at an optimized design, a sensitivity analysis was performed to identify the input variables whose variabilities have the greatest influence on the mean of a given response. Finally, an analysis of percent contribution of each input variable standard deviation to the actual response standard deviation was performed.

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Fig. 1

Compressor rotor: geometry (top) and rotordynamic model (bottom)

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Fig. 2

Four tilting pad-LBP bearing

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Fig. 3

Response variables

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Fig. 4

Effects of significant factors on response variables, coded units

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Fig. 5

Response surface of the threshold speed of instability versus Cp and m, uncoded units

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Fig. 6

Contour plots of the threshold speed of instability versus (a) Cp and m and (b) m and T, uncoded units

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Fig. 7

Optimization output of the RSDOE, uncoded units

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Fig. 8

Overlaid contour plot, optimum solution depicted by ⊕, uncoded units



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