Stochastic Field Models for Aircraft Jet Engine Applications
Dan M. Ghiocel
Abstract
Dan M. Ghiocel
Abstract
This paper addresses the stochastic modeling for advanced jet engine applications and also presents an overview of the basic theoretical aspects of different useful stochastic field models and then illustrates their application to practical problems. It is shown that stochastic fields adequately capture key random aspects of engine environment and behavior. The illustrated applications address stochastic modeling issues that are typical for engine structural analysis, such as time-varying operating speed conditions, manufacturing geometry deviations, and engine vibration, that produce highly nonlinear responses. This paper discusses stochastic modeling for two situations often met in practice: (1) stochastic process/field models with known statistics; and (2) stochastic process/field models with unknown statistics. Illustrative examples are used to highlight features of different stochastic field modeling techniques.
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This paper addresses the stochastic modeling for advanced jet engine applications and also presents an overview of the basic theoretical aspects of different useful stochastic field models and then illustrates their application to practical problems. It is shown that stochastic fields adequately capture key random aspects of engine environment and behavior. The illustrated applications address stochastic modeling issues that are typical for engine structural analysis, such as time-varying operating speed conditions, manufacturing geometry deviations, and engine vibration, that produce highly nonlinear responses. This paper discusses stochastic modeling for two situations often met in practice: (1) stochastic process/field models with known statistics; and (2) stochastic process/field models with unknown statistics. Illustrative examples are used to highlight features of different stochastic field modeling techniques.
Key concepts: Stochastic process, Stochastic modelling, Field (mathematics), Jet engine, Computer science, Continuous-time stochastic process, Nonlinear system, Process (computing)