The Aerodynamic Design of the Low Pressure Air Delivery Ducts for a Cooled Cooling Air System

Abstract

As aero gas turbines strive for higher efficiencies and reduced fuel burn, the trend is for engine overall pressure ratio to increase. This means that engine cycle temperatures will increase and that cooling of various engine components, for example the high pressure turbine, is becoming more difficult. One solution is to employ a cooled cooling air system where some of the compressor efflux is diverted for additional cooling in a heat exchanger fed by air sourced from the by-pass duct. Design of the ducting to feed the heat exchangers with coolant air is challenging as it must route the air through the scenery present in the existing engine architecture which leads to a convoluted and highly curved system. Numerical predictions using ANSYS Fluent demonstrated that a baseline design was unsuitable due to large amounts of flow separation in the proximity of the heat exchangers. This paper is mainly concerned with the aerodynamic design of this component of the duct. In order to produce a viable aerodynamic solution a numerical design methodology was developed which significantly enhances and accelerates the design cycle. This used a Design of Experiments approach linked to an interactive design tool which parametrically controlled the duct geometry. Following an iterative process, individually optimized 2D designs were numerically assessed using ANSYS Fluent. These designs were then fed into an interactive 3D model in order to generate a final aerodynamic definition of the ducting. Further CFD predictions were then carried out to confirm the suitability of the design. RANS CFD solutions, generated, using a Reynolds stress turbulence model, suggested that the new design presented significant improvement in terms of diffusion and flow uniformity.

A Multi-Objective Factorial Design Methodology for Aerodynamic Off-Takes and Ducts

“…It will be shown in the next sub-section that nine input variables are needed to geometrically determine this problem. A full factorial of the nine inputs would perhaps be computationally viable if sampling was limited to two levels per input variable (i.e., 2 9 = 512 iterations). However, as mentioned above, more levels are required to directly observe the highly nonlinear effects in this study.…”

“…However, as mentioned above, more levels are required to directly observe the highly nonlinear effects in this study. Even as few as three levels are not computationally affordable (i.e., 3 9 2 × 10 4 iterations). Preliminary sampling of the design space showed that not all input variables interact strongly to one another and suggested that reduction of this full factorial into three fractions is possible without risking the elimination of high value design families.…”

“…With that in mind, the maximum value achievable was N = 7 which results on a total of 3 × 7 3 = 1029 design iterations. The same resolution would require 7 9 4 × 10 7 design iterations, were it not for the fractional approach employed.…”

“…However, approximately 90% of the diffusion will need to be achieved between the strut exit and the HX. In previous work of Spanelis et al [9] this region was comprised of two s-ducts separated by a vane. Their results suggested that flow uniformity at duct exit is maximised for designs which concentrate the aerodynamic loading (both diffusion and curvature) close to the HX.…”

“…al. [9] examined a double s-duct by sequentially exploring eight primary and five secondary design variables. Their findings have fed back to evolve the conceptual design to the current state by introducing new features, such as a significant elongation of the vane that separates the two heat exchangers and an independent diffusing duct segment upstream of the manifold (i.e., diffuser 2).…”