A probabilistic methodology to quantify the impact of geometric variability on compressor aerodynamic performance is presented. High-fidelity probabilistic models of geometric variability are derived using a principal-component analysis of blade surface measurements. This probabilistic blade geometry model is then combined with a compressible, viscous blade-passage analysis to estimate the impact on the passage loss and turning using a Monte Carlo simulation. Finally, a mean-line multistage compressor model, with probabilistic loss and turning models from the blade-passage analysis, is developed to quantify the impact of the blade variability on overall compressor efficiency and pressure ratio. The methodology is applied to a flank-milled integrally bladed rotor. Results demonstrate that overall compressor efficiency can be reduced by approximately 1% due to blade-passage effects arising from representative manufacturing variability.

This paper considers the aerodynamic design of compressor blade sections for improved performance robustness in the face of geometric uncertainty caused by noisy manufacturing processes. A probabilistic, gradient-based optimization method was used to redesign subsonic and transonic compressor airfoils subjected to geometric variability. Three different design goals were considered: Minimizing the deterministic profile total pressure loss coefficient, minimizing the mean value of loss coefficient, and minimizing the loss variability. In both transonic and subsonic applications, deterministic minimization of loss coefficient produced essentially the same airfoils as the probabilistic minimization of mean loss. However probabilistic minimization of loss variability produced clearly different airfoils which achieved reductions of 20% or more in standard deviation of loss compared to the minimum-loss designs. For the subsonic application, the improved robustness of the minimum variability design was achieved through a reduction in diffusion immediately downstream of the leading edge on the pressure side. This reduction in diffusion resulted in less sensitivity of the boundary layer to geometric variability in the leading edge region. For the transonic application, the robustness improvement was achieved by redesigning the suction side to produce a constant pressure region immediately downstream of the passage shock, which had the effect of desensitizing the boundary layer to variability in shock strength and position. A meanline model was used to assess the impact of probabilistic airfoil section optimization on overall compressor performance. While the mean efficiency was found to be nearly the same for all designs, the robust blade designs produced a decrease in compressor efficiency variability of 50% compared to the minimum-loss designs.

A probabilistic methodology to quantify the impact of geometric variability on compressor aerodynamic performance is presented. High-fidelity probabilistic models of geometric variability are derived using a Principal-Component-Analysis (PCA) of blade surface measurements. This probabilistic blade geometry model is then combined with a compressible, viscous blade-passage analysis to estimate the impact on the passage loss and turning using a Monte Carlo simulation. Finally, a mean-line multi-stage compressor model, with probabilistic loss and turning models from the blade-passage analysis, is developed to quantify the impact of the blade variability on overall compressor efficiency and pressure ratio. The methodology is applied to a flank-milled Integrally-Bladed Rotor (IBR). Results demonstrate that overall compressor efficiency can be reduced by approximately 1% due to blade-passage effects arising from representative manufacturing variability.

Numerical results demonstrating the effect of film-cooling hole placement on turbulator heat transfer effectiveness in internal convective cooling air circuits of turbine blades in high-performance gas turbine engines is presented for a two-dimensional model problem. Of particular interest will be the performance of a new turbulence modeling formalism similar to large-eddy simulation (LES) but employing subgrid-scale models constructed from nonlinear discrete dynamical systems, and not requiring filtering of the resolved-scale governing equations. Computed results for temperature distribution, flow streamlines, pressure coefficient and heat transfer Stanton number are compared for three different cooling hole/turbulator configurations, and turbulence kinetic energy is compared with results from a standard k-ε model.