United Technologies Corporation

Rtx Corporation

Raytheon Technologies Corporation

Perry Bowes

Robert J Morris

Daniel A Snyder

Kurt R Heinemann

Sue-Li Chuang

Evan Selin

Ming-Ta Yang

Steven R Haggerty

Benjamin D Hall

David J Yudichak

Lauren Gray

A qualification system for gas turbine engine components includes a computer system configured to receive a set of measured parameters for each gas turbine engine component in a plurality of substantially identical gas turbine engine components, and determine a variation model based on the set of measured parameters. The computer system includes at least one simulated engine model configured to determine a predicted operation of each gas turbine engine component in the plurality of substantially identical gas turbine engine components, a correlation system configured to correlate variations in the set of parameters for each of the gas turbine engine components with a set of the predicted operations of each gas turbine engine, thereby generating a predictive model based on the variations. The computer system also includes a qualification module configured to generate a qualification formula based on the predictive model. The qualification formula is configured to receive a set of measured parameters of an as-manufactured gas turbine engine component and determine when the as manufactured gas turbine engine component is qualified for inclusion in at least one engine.

Aircraft component qualification system and process

A novel probabilistic method for analyzing high cycle fatigue (HCF) in a design of a gas turbine engine is disclosed. The method may comprise identifying a component of the gas turbine engine for high cycle fatigue analysis, inputting parametric data of the component over a predetermined parameter space into at least one computer processor, using the at least one computer processor to build a plurality of flexible models of the component based on the parametric data of the component over the predetermined parameter space, using the at least one computer processor to build a plurality of emulators of the component based on the plurality of flexible models, and using the at least one computer processor to predict a probability of HCF based at least in part on the parametric data of the component over the predetermined parameter space and the plurality of emulators.

Probabilistic high cycle fatigue (HCF) design optimization process

Systems and methods involving surface fitting are provided. In this regard, a representative method includes: receiving information corresponding to discrete data points of a portion of a surface; determining curvature estimates associated with the data points prior to performing curve fitting with respect to the data points; identifying curvature shock based on the curvature estimates, the curvature shock being defined as a curvature threshold corresponding to an absolute value of curvature between adjacent data points; breaking C2 continuity between adjacent data points exhibiting curvature shock; and performing surface fitting with respect to the data points to generate Non-Uniform Rational B-Splines (NURBS) data such that breaks in the C2 continuity associated with curvature shock are maintained in the NURBS data.

Systems and methods involving surface fitting

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Manchester, CT, United States of America

Perry Bowes