A transonic turbine airfoil design is optimized using an artificial intelligence engineering design shell coupled with an inviscid, adaptive grid, CFD solver. The objective of the optimization is to minimize the downstream static pressure variation resulting from the trailing edge shock structure. Cascade test results verify the analytical predictions. Techniques are described which were used to couple the optimization shell to the 2-D turbine airfoil shape to allow the search for optimal designs and indicate the quality of those designs. The emphasis of the discussion is upon the application of these techniques rather than the physical details of the resulting blade design. NOMENCLATURE

Over tip leakage in high-pressure turbines contributes to aerodynamic losses and migration of hot gasses towards the tip resulting in increased thermal distress. Consequently, turbine designers continue to search for improved blade tip concepts that offer the promise of reducing tip leakage. The present paper deals with the computational fluid dynamics analyses of some such tip configurations. The geometries, patented by GE, are variants of a conventional squealer tip and include (i) a pressure side tip shelf with vertical squealer tip wall and (ii) a pressure side tip shelf with an inclined squealer tip wall. It is found that the inclined shelf results in separation of flow leaking over the tip, resulting in reduced leakage and improved efficiency. The inclined shelf also shows a reduced efficiency derivative with clearance.

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In aircraft engine design (and in other applications), small improvements in turbine efficiency may be significant. Since analytical tools for predicting transonic turbine losses are still being developed, experimental efforts are required to evaluate various designs, calibrate design methods, and validate CFD analysis tools. However, these experimental efforts must be very accurate to measure the performance differences to the levels required by the highly competitive aircraft engine market. Due to the sensitivity of transonic and supersonic flow fields, it is often difficult to obtain the desired level of accuracy. In this paper, a statistical approach is applied to the experimental evaluation of transonic turbine airfoils in the VPI & SU transonic cascade facility in order to quantify the differences between three different transonic turbine airfoils. This study determines whether the measured performance differences between the three different airfoils are statistically significant. This study also assesses the degree of confidence in the transonic cascade testing process at VPI & SU.

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