The effects of a wake generated by a stationary upstream strut on surface heat transfer to turbine blades were measured experimentally. Time-resolved and unsteady heat flux measurements were made with Heat Flux Microsensors (HFM) at three positions on the suction surface and one position on the pressure surface of a turbine blade. The experiments were conducted on a stationary cascade of blades for heated runs at transonic conditions
Methods for determining the adiabatic wall temperature and heat transfer coefficient are presented and the results are compared to computer predictions for these blades. Heat transfer measurements were taken with new HFM-6 insert gages. A strong influence on the heat transfer coefficient was seen from the relative position of the strut with respect to the leading edge of the test blades. As the strut approached the leading edge of the blade the heat transfer increased by 15% at gage location 2 on the suction surface. The largest increase in .the heat transfer coefficient was seen on the pressure surface. Results at this location show a 24% increase in the overall heat transfer coefficient for one of the strut locations. The values obtained for the heat transfer coefficients for the no strut case did not compare well with computer predictions. The results did support the experimental results of other researchers, however. The fast time response of the HFM illustrated graphically an increase in the frequency energy between the 0-10 kHz range when the strut was located near the leading edge of the instrumented blade. The heat flux turbulence intensity (Tuq) was defined as another physical quantity important to turbine blade heat transfer, but no conclusions could be drawn from the results as to how this value compares to the turbulence intensity. / Master of Science
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/44350 |
| Date | 22 August 2008 |
| Creators | Hale, Jamie Harold |
| Contributors | Mechanical Engineering, Schetz, Joseph A., Diller, Thomas E., Ng, Fai |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis, Text |
| Format | xxiii, 249 leaves, BTD, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
| Relation | OCLC# 34923196, LD5655.V855_1996.H354.pdf |
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