Constrained Design Optimization of Rotor-Tilting Pad Bearing

Design of a rotor-bearing system is a challenging task due to various conflicting design requirements, which should be fulfilled. This study considers an automatic optimization approach for the design of a rotor supported on tilting-pad bearings. A numerical example of a rotor-bearing system is employed to demonstrate the merits of the proposed design approach. The finite element method is used to model the rotor-bearing system, and the dynamic speed-dependent coefficients of the bearing are calculated using a bulk flow code. A number of geometrical characteristics of the rotor simultaneously with the parameters defining the configuration of tilting pad bearings are considered as design variables into the automatic optimization process. The power loss in bearings, stability criteria, and unbalance responses are defined as a set of objective functions and constraints. The complex design optimization problem is solved using heuristic optimization algorithms, such as genetic, and particle-swarm optimization. Whereas both algorithms found better design solutions than the initial design, the genetic algorithms exhibited the fastest convergence. A statistical approach was used to identify the influence of the design variables on the objective function and constraint measures. The bearing clearances, preloads and lengths showed to have the highest influence on the power loss in the chosen design space. The high performance of the best solution obtained in the optimization design suggests that the proposed approach has good potential for improving design of rotor-bearing systems encountered in industrial applications.

[1]  A. Neumaier.  Complete search in continuous global optimization and constraint satisfaction , 2004, Acta Numerica.

[2]  Patrick Keogh,et al.  On LMI-Based Optimization of Vibration and Stability in Rotor System Design , 2006 .

[3]  Edwin K. P. Chong,et al.  An Introduction to Optimization: Chong/An Introduction , 2008 .

[4]  Paul E. Allaire,et al.  Balancing of Flexible Rotors Using Convex Optimization Techniques : Optimum Min-Max LMI Influence Coefficient Balancing , 2008 .

[5]  Liping Wang,et al.  An analytical model for complete dynamical coefficients of a tilting-pad journal bearing , 2010 .

[6]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[7]  Victor J. Rayward-Smith,et al.  Modern Heuristic Search Methods , 1996 .

[8]  Rikard Fredriksson,et al.  Analysis of running child pedestrians impacted by a vehicle using rigid-body models and optimization techniques , 2010 .

[9]  Costin D. Untaroiu,et al.  A numerical investigation of mid-femoral injury tolerance in axial compression and bending loading , 2010 .

[10]  Dara W. Childs,et al.  Turbomachinery Rotordynamics: Phenomena, Modeling, and Analysis , 1993 .

[11]  B.-K. Choi,et al.  Multiobjective Optimum Design of Rotor-Bearing Systems With Dynamic Constraints Using Immune-Genetic Algorithm , 2001 .

[12]  E. Chong,et al.  Introduction to optimization , 1987 .

[13]  Ting-Yu Chen,et al.  Optimum design of rotor-bearing systems with eigenvalue constraints , 1993 .

[14]  Jan-Olov Aidanpää,et al.  Constrained Optimization of Gas Turbine Tilting Pad Bearing Designs , 2006 .

[15]  Michel Fillon,et al.  Analysis of a Tilting Pad Journal Bearing to Avoid Pad Fluttering , 2006 .

[16]  Paul E. Allaire,et al.  Computational Modeling and Experimental Investigation of Static Straight-Through Labyrinth Seals , 2008 .

[17]  Michel Lalanne,et al.  Rotordynamics prediction in engineering , 1998 .

[18]  Byung Gun Choi,et al.  Optimum Shape Design of Rotor Shafts Using Genetic Algorithm , 2000 .

[19]  Paul E. Allaire,et al.  Hole-Pattern Seals: A Three Dimensional CFD Approach for Computing Rotordynamic Coefficient and Leakage Characteristics , 2009 .

[20]  Anders Angantyr,et al.  A Pareto-Based Genetic Algorithm Search Approach to Handle Damped Natural Frequency Constraints in Turbo Generator Rotor System Design , 2004 .

[21]  Sanaz Mostaghim.  Multi-objective evolutionary algorithms: data structures, convergence, and diversity , 2004 .

[22]  Jeffrey Richard Crandall,et al.  A design optimization approach of vehicle hood for pedestrian protection , 2007 .

[23]  M Reyes Sierra,et al.  Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art , 2006 .

[24]  T. N. Shiau,et al.  Optimum Weight Design of a Rotor Bearing System With Dynamic Behavior Constraints , 1990 .

[25]  Jeffrey Richard Crandall,et al.  Crash reconstruction of pedestrian accidents using optimization techniques , 2009 .

[26]  Sheldon M. Ross,et al.  Introduction to Probability and Statistics for Engineers and Scientists , 1987 .