The Implementation of Probabilistic Methods for Uncertainty Analysis in Computational Fluid Dynamics Simulations of Fluid Flow and Heat Transfer in a Gas Turbine Engine

Abstract

Probabilistic methods have been implemented with a computational fluid dynamics simulation of fluid flow and heat transfer in a gas turbine engine. The simulation models the temperatures in the T-56 series III 1-2 spacer. Three input quantities are treated as random variables. A random sampling method is used to generate the input values from a probability density function. The implemented Monte Carlo method uses a large number of samples of the input variables to calculate results repeatedly for the output variables (i.e. the predicted temperatures). Statistics of the predicted temperatures, such as the mean and variance, are then calculated. The variation in the predicted temperature at one point in the turbine of the T56 engine is seen to be more sensitive to variability in some parameters than in others.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2006
Accession Number
ADA451870

Entities

People

  • John Faragher

Organizations

  • Defence Science and Technology Group

Tags

Communities of Interest

  • Air Platforms
  • Ground and Sea Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aircrafts
  • Boundary Layer
  • Computational Fluid Dynamics
  • Computational Science
  • Engine Components
  • Fluid Dynamics
  • Fluid Flow
  • Fluid Mechanics
  • Gas Turbines
  • Heat Transfer
  • Information Science
  • Mathematical Models
  • Monte Carlo Method
  • Probability Density Functions
  • Propulsion Systems
  • Random Variables
  • Statistical Sampling

Readers

  • Aerodynamics.
  • Computational Modeling and Simulation
  • Thermal Physics or Thermal Science.