Predicting the Onset of Cavitation in Automotive Torque Converters—Part II: A Generalized ModelReport as inadecuate

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International Journal of Rotating MachineryVolume 2008 2008, Article ID 312753, 8 pages

Research Article

General Motors Powertrain Group, General Motors Corporation, Pontiac, MI 48340, USA

Department of Mechanical Engineering—Engineering Mechanics, Michigan Technological University, Houghton, MI 49931, USA

Received 10 March 2008; Accepted 9 June 2008

Academic Editor: Yoshinobu Tsujimoto

Copyright © 2008 D. L. Robinette et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The objective of this investigation was to develop a dimensionless model for predicting the onset of cavitation in torque converters applicable to general converter designs. Dimensional analysis was applied to test results from a matrix of torque converters that ranged from populations comprised of strict geometric similitude to those with more relaxed similarities onto inclusion of all the torque converters tested. Stator torque thresholds at the onset of cavitation for the stall operating condition were experimentally determined with a dynamometer test cell using nearfield acoustical measurements. Cavitation torques, design parameters, and operating conditions were resolved into a set of dimensionless quantities for use in the development of dimensionless empirical models. A systematic relaxation of the fundamental principle of dimensional analysis, geometric similitude, was undertaken to present empirical models applicable to torque converter designs of increasingly diverse design parameters. A stepwise linear regression technique coupled with response surface methodology was utilized to produce an empirical model capable of predicting stator torque at the onset of cavitation with less than 7% error for general automotive torque converter designs.

Author: D. L. Robinette, J. M. Schweitzer, D. G. Maddock, C. L. Anderson, J. R. Blough, and M. A. Johnson



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