Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.