Measurements in a Turbine Cascade Flow Under Ultra Low Reynolds Number Conditions

Abstract

With the new generation of gas turbine engines, low Reynolds number flows have become increasingly important. Designers must properly account for transition from laminar to turbulent flow and separation of the flow from the suction surface, which is strongly dependent upon transition. Of interest to industry are Reynolds numbers based upon suction surface length and flow exit velocity below 150,000 and as low as 25,000. In this paper, the extreme low end of this Reynolds number range is documented by way of pressure distributions, loss coefficients, and identification of separation zones. Reynolds numbers of 25,000 and 50,000 and with 1 percent and 8-9 percent turbulence intensity of the approach flow (free-stream turbulence intensity, FSTI) were investigated. At 25,000 Reynolds number and low FSTI, the suction surface displayed a strong and steady separation region. Raising the turbulence intensity resulted in a very unsteady separation region of nearly the same size on the suction surface. Vortex generators were added to the suction surface, but they appeared to do very little at this Reynolds number. At the higher Reynolds number of 50,000, the low-FSTI case was strongly separated on the downstream portion of the suction surface. The separation zone was eliminated when the turbulence level was increased to 8-9 percent. Vortex generators were added to the suction surface of the low-FSTI case. In this instance, the vortices were able to provide the mixing needed to re-establish flow attachment. This paper shows that massive separation at very low Reynolds numbers (25,000) is persistent, in spite of elevated FSTI and added vortices. However, at a higher Reynolds number, there is opportunity for flow reattachment either with elevated free-stream turbulence or with added vortices. This may be the first documentation of flow behavior at such low Reynolds numbers. Although it is undesirable to operate under these conditions, it is important to know what to expect and how performance may be improved if such conditions are unavoidable.