公开(公告)号：US20140358500A1

公开(公告)日：2014-12-04

申请号：US14134530

申请日：2013-12-19

Applicant: United Technologies Corporation

Inventor： Robert J. Morris ,  Benjamin D. Hall ,  Lauren Gray ,  Ming-Ta Yang ,  Perry Bowes

IPC: G06F17/50

CPC classification number: G06F17/5086 ,  F01D5/16 ,  F01D21/003 ,  F05D2260/81 ,  F05D2260/961 ,  G06F17/5018 ,  G06F2217/76

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 translation: 公开了一种用于分析燃气轮机发动机设计中的高循环疲劳（HCF）的新概念方法。 该方法可以包括识别用于高循环疲劳分析的燃气涡轮发动机的部件，使用至少一个计算机处理器将组件的预定参数空间的参数数据输入到至少一个计算机处理器中，以构建多个灵活模型 基于所述组件在所述预定参数空间上的参数数据，使用所述至少一个计算机处理器来基于所述多个灵活模型构建所述组件的多个仿真器，并且使用所述至少一个计算机处理器 至少部分地基于组件在预定参数空间和多个仿真器上的参数数据来预测HCF的概率。

公开(公告)号：US20200012749A1

公开(公告)日：2020-01-09

申请号：US16026547

申请日：2018-07-03

Applicant: United Technologies Corporation

Inventor： Daniel A. Snyder ,  David J. Yudichak ,  Kurt R. Heinemann ,  Perry Bowes ,  Evan Selin

IPC: G06F17/50

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. 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.

公开(公告)号：US09483605B2

公开(公告)日：2016-11-01

申请号：US14134530

申请日：2013-12-19

Applicant: UNITED TECHNOLOGIES CORPORATION

Inventor： Robert J. Morris ,  Benjamin D. Hall ,  Lauren Gray ,  Ming-Ta Yang ,  Perry Bowes

IPC: G06F17/50 ,  F01D5/16 ,  F01D21/00

CPC classification number: G06F17/5086 ,  F01D5/16 ,  F01D21/003 ,  F05D2260/81 ,  F05D2260/961 ,  G06F17/5018 ,  G06F2217/76

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 translation: 公开了一种用于分析燃气轮机发动机设计中的高循环疲劳（HCF）的新概念方法。 该方法可以包括识别用于高循环疲劳分析的燃气涡轮发动机的部件，使用至少一个计算机处理器将组件的预定参数空间的参数数据输入到至少一个计算机处理器中，以构建多个灵活模型 基于所述组件在所述预定参数空间上的参数数据，使用所述至少一个计算机处理器来基于所述多个灵活模型构建所述组件的多个仿真器，并且使用所述至少一个计算机处理器 至少部分地基于组件在预定参数空间和多个仿真器上的参数数据来预测HCF的概率。