Rolls-royce Corporation

Sean Warrenburg

Joseph A Swift

Michael George Glavicic

Kyle Hassler

Mark Winely

Chong M Cha

Kevin Mock

Weizhou Li

Kyle A Hassler

In general, various aspects of the techniques enable predictive modeling for forged components. A computing device comprising a memory and a processor may be configured to perform the techniques. The memory may store a trained machine learning model that associates training features extracted from data representative of a plurality of training forged components to a plurality of training model results. The memory may also store data representative of a target forged component. The processor may perform a geometrical analysis with respect to the data representative of the target forged component to extract target features, and apply the trained machine learning model to the target features to obtain predicted model results for the target forged component. The processor may also output the predicted model results.

Predictive modeling for forged components

An exemplary cone brake device includes a brake drum and a thermal sprayed coating deposited and bonded to the outer surface. The thermal sprayed coating is configured to engage a friction lining when one of the brake drum and the friction element is moved toward the other of the brake drum and the friction element, so as to decrease the speed of an aerospace propeller.

Cone brake friction surface coating

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Avon, IN, United States of America

Sean Warrenburg