Computational Analysis of Dual Radius Circulation Control Airfoils

Abstract

I. AbstractThe goal of the work is to use multiple codes and multiple configurations to provide an assessment of the capability of RANS solvers to predict circulation control dual radius airfoil performance and also to identify key issues associated with the computational predictions of these configurations that can result in discrepancies in the predicted solutions. Solutions were obtained for the Georgia Tech Research Institute (GTRI) dual radius circulation control airfoil and the General Aviation Circulation Control (GACC) dual radius airfoil. For the GTRI-DR airfoil, two-dimensional structured and unstructured grid computations predicted the experimental trend in sectional lift variation with blowing coefficient very well. Good code-to-code comparisons between the chordwise surface pressure coefficients and the solution streamtraces also indicated that the detailed flow characteristics were matched between the computations. For the GACC-DR airfoil, two-dimensional structured and unstructured grid computations predicted the sectional lift and chordwise pressure distributions accurately at the no blowing condition. However at a moderate blowing coefficient, although the code-to-code variation was small, the differences between the computations and experiment were significant. Computations were made to investigate the sensitivity of the sectional lift and pressure distributions to some of the experimental and computational parameters, but none of these could entirely account for the differences in the experimental and computational results. Thus, CFD may indeed be adequate as a prediction tool for dual radius CC flows, but limited and difficult to obtain two-dimensional experimental data prevents a confident assessment at this time.

Current trends in modelling research for turbulent aerodynamic flows

“…Lee-Rausch et al 2006;Shmilovich & Yadlin 2006) and over circular trailing edges (e.g. Slomski et al 2006;Swanson & Rumsey 2006).…”

A Jacobian-free Newton–Krylov algorithm for compressible turbulent fluid flows

“…The major NASA flow solvers typify the algorithms that are most popular in the computational aerodynamics community. OVERFLOW [3] and CFL3D [4] are both based on implicit approximate factorization methods, TLNS3D [5] and CART3D [6] utilize multi-stage explicit schemes with multigrid, and FUN3D [7], although it includes a Newton-Krylov option, is usually run using either a point implicit procedure or an implicit line relaxation scheme [8]. All of these approaches are more mature than JFNK methods.…”

Design and Performance of Circulation Control Geometries

“…Several studies had found that computational meshes required much more refinement in the regions of the Coanda surface of the airfoil, along with the shear layer between the jet flow and freestream flow to more accurately capture all of the CC flow interactions. [50][51][52]54,55 With adequate refinement within these areas of complex CC flow features, the same studies saw great improvement towards matching experimental results.…”

“…9,50,51 The over prediction of lift was most commonly caused by the delay in jet separation from the Coanda surface of the airfoil. [51][52][53][54] It was found that simulations of CC airfoil geometries that employed sharp trailing edges (rather than rounded) predicted jet separation better, 51 but still over predicted lift and was not a solution for simulating the actual CC flow. The inability for these simulations to match experimental data had multiple causes, with the most significant causes being mesh refinement and turbulence modeling.…”

“…Addressing the issues experienced with the turbulence modeling of CC flows, a general trend was observed that most models degraded in performance with the increase of momentum coefficient. 52,53,56,57 A more detailed analysis has found that this rapid drop-off in turbulence model performance occurred when the freestream flow around the airfoil was not completely attached and separated flow was present. 53 One of the most significant causes of the inconsistencies with some turbulence models prediction of the flow field has been attributed to the model"s failure to account for curvature effects that are present in the flow.…”