TY - GEN
T1 - Effect of uncertainties in the estimation of dynamic coefficients on tilting pad journal bearings
AU - Ruiz, Rafael O.
AU - Diaz, Sergio E.
N1 - Publisher Copyright:
Copyright © 2016 by ASME.
PY - 2016
Y1 - 2016
N2 - It has been identified that small variations in the pad clearance and preload of a Tilting Pad Journal Bearing lead to important variations in their dynamic coefficients. Although this variation trend is already identified, a more robust statistical analysis is required in order to identify more general tendencies and quantify it. This work presents a framework that helps to identify the relation between the manufacturing tolerance of the bearing (reflected in the pad clearance and preload) and the expected variations on the dynamic coefficients. The procedure underlies the adoption of a surrogate model (based on Kriging interpolation) trained by any deterministic model available to predict dynamic coefficients. The pad clearance and preload are considered uncertain parameters defined by a proper probability density function. All statistical quantities are obtained using stochastic simulation, specifically adopting a Monte Carlo simulation employing the surrogate model. The framework is illustrated through the study of a five pad bearing.
AB - It has been identified that small variations in the pad clearance and preload of a Tilting Pad Journal Bearing lead to important variations in their dynamic coefficients. Although this variation trend is already identified, a more robust statistical analysis is required in order to identify more general tendencies and quantify it. This work presents a framework that helps to identify the relation between the manufacturing tolerance of the bearing (reflected in the pad clearance and preload) and the expected variations on the dynamic coefficients. The procedure underlies the adoption of a surrogate model (based on Kriging interpolation) trained by any deterministic model available to predict dynamic coefficients. The pad clearance and preload are considered uncertain parameters defined by a proper probability density function. All statistical quantities are obtained using stochastic simulation, specifically adopting a Monte Carlo simulation employing the surrogate model. The framework is illustrated through the study of a five pad bearing.
UR - https://www.scopus.com/pages/publications/85032179017
U2 - 10.1115/IMECE201667252
DO - 10.1115/IMECE201667252
M3 - Conference contribution
AN - SCOPUS:85032179017
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
BT - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2016 International Mechanical Engineering Congress and Exposition, IMECE 2016
Y2 - 11 November 2016 through 17 November 2016
ER -