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Validation of a CFD Approach for Gas Turbine Internal Cooling Passage Heat Transfer Prediction

Abstract

dc:description.abstract

<p>This report describes the development and application of a validated Computational Fluid Dynamics (CFD) modelling approach for internal cooling passages in rotating turbomachinery. A CFD Modelling approach and accompanying assumptions are tuned and validated against academically available experimental results for various serpentine passages. Criteria of the CFD modelling approach selected for investigation into advanced internal cooling flows include accuracy, robustness, industry familiarity, and computational cost.</p> <p>Experimental data from NASA HOST (HOt Section Technology), Texas A&M, and University of Manchester tests are compared to RANS CFD results generated using Fluent v14.5 in order to benchmark a CFD modelling approach.</p> <p>Capability of various turbulence models in the representation of cooling physics is evaluated against experimental data. Model sensitivity to boundary conditions and mesh density is also evaluated.</p> <p>The development of a validated computational model of internal turbine cooling channels with bounded error allows for the identification of particular shortcomings of heat transfer correlations and provides a baseline for future CFD based exploration of internal turbine cooling concepts.</p>

Degree

thesis:*
Name thesis:degree_name
MS in Aerospace Engineering
Discipline thesis:degree_discipline
Aerospace Engineering
Year dc:date.available
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Wilde, Daniel G
Contributors dc:contributor
  • David Marshall

Subjects

dc:subject × 7

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:digitalcommons.calpoly.edu:theses-2514

Chain of custody

source
Harvested from
Cal Poly
Base URL
digitalcommons.calpoly.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Wilde, Daniel G. Validation of a CFD Approach for Gas Turbine Internal Cooling Passage Heat Transfer Prediction. 2015. https://digitalcommons.calpoly.edu/theses/1384