Martin Gariépy

Far-Field Drag Decomposition Applied to the Drag Prediction Workshop 5 Cases

A far-field drag prediction and decomposition method has been applied to the results of the AIAA Drag Prediction Workshop 5 held in Louisiana during the summer of 2012. The method has two principal advantages: it allows the removal of spurious drag inherent to computational fluid dynamics solutions, and it allows the decomposition of drag into viscous, wave, and induced physical drag components. This research shows that accurate drag coefficients can be predicted on coarse grids when the spurious drag is extracted with the far-field method and that these results are closer to experimental values than drag coefficients computed on finer meshes when spurious drag is not extracted. The research also investigated the reasons behind the lift and drag losses found by some participants in the workshop. It is shown that the lift loss is caused by the boundary-layer separation at the wing root, inducing a reduction of 20% of the shock wave drag and a significant change in the wing loading. The initiation of buffet...

Generalization of the Far-Field Drag Decomposition Method to Unsteady Flows

Far-field drag-prediction and decomposition methods are powerful tools that increase the accuracy of the drag coefficient computed from computational fluid dynamics results by removing the spurious drag caused by numerical procedures. Furthermore, these methods allow a physical decomposition of the drag in terms of viscous, wave, and induced drag. However, they are currently limited to steady flows. This paper presents a generalization of the commonly used drag-prediction and decomposition method to unsteady flows. This generalized method, designed for three-dimensional viscous, subsonic, and transonic flows, is defined for both inertial and noninertial coordinate systems and allows drag decomposition to be performed on either static or moving/rotating meshes. This generalization also allows the drag caused by the unsteady fluctuations of the flow to be identified.

Convergence Criterion for a Far-Field Drag Prediction and Decomposition Method

a = speed of sound, m=s Cd = drag coefficient D = drag, N dm = minimal distance, m f = pressure and momentum forces, kPa M = Mach number n = unit normal vector nx; ny; nz P = pressure, kPa R = gas constant, J=kg K S = relative to a surface or a plane, m s = entropy, J=K T = temperature, K or, C v = velocity vector u; v; w , m=s = specific heat ratio H = variation of total enthalpy relative to freestream, J=kg s = variation of entropy relative to freestream, J=K = viscosity, N s=m = density, kg=m = deviatoric stress tensor x; y; z , N=m = domain volume, m

Far-Field Drag Decomposition Method Applied to the DPW-5 Test Case Results

A fareld drag prediction and decomposition method has been applied to the results of AIAA Drag Prediction Workshop 5 (DPW-5) held in Louisiana during the summer of 2012. The method has two principal advantages: it allows the removal of spurious drag inherent to CFD solutions, and it allows the decomposition of drag into viscous, wave, and induced physical drag components. This research shows that accurate drag coe cients can be predicted on coarse grids when the spurious drag is extracted with the fareld method, and that these results are closer to experimental values than drag coe cients computed on ner meshes when spurious drag is not extracted. The research also investigated the reasons behind the lift and drag losses found by some participants in the Workshop. It is shown that the lift loss is caused by the boundary layer separation at the wing root, inducing a reduction of 20% of the shock wave drag and a signi cant change in wing loading. The initiation of bu et is also analyzed. The study shows that mesh re nement is critical to capture the physical e ects of the ow, such as its separation, and provides an explanation of the discrepancies in results observed at DPW-5.

Direct Search Airfoil Optimization Using Far-Field Drag Decomposition Results

For this research project, two airfoils have been optimized using a Direct Search optimization algorithm and a cost function determined from the results of a fareld drag decomposition method. The latter is a powerful tool allowing to breakdown the drag into wave, viscous, induced and spurious drags. The latter type of drag is caused by numerical and truncation errors, as well as by the addition of arti cial viscosity by most solvers to smooth strong gradients. Furthermore, the spurious drag is dependent on the con guration: a blunt body will produce more spurious drag than a slender body. Thus, if an optimization process is based on the total drag it will tend to nd a con guration that reduces among others, the spurious drag which can limit its e ciency. The optimization process in this research used the net drag only, excluding the spurious drag. First, the NACA0012 airfoil in an Euler ow at Ma = 0.85 was optimized. The nal conguration had a at nose shape and an almost constant thickness along the chord. The computed net drag was 74 d.c., an improvement of 393 d.c. An additional control optimization was done, but on the total drag. The optimized con guration was more rounded, which is a direct consequence of including the spurious drag in the objective function. This shows that the spurious drag has a large in uence on the optimum airfoil. Second, the RAE2822 airfoil in viscous ow with a constant lift coe cient of 0.824 and a Mach number of 0.734 was optimized. The nal con guration was thinner than the original airfoil on the rst 50% of the chord length, then got thicker for the rest of the chord length. The con guration also showed a cambered trailing edge typical of supercritical airfoils. The computed net drag value was 104.3 d.c., an improvement of 83 d.c. Most of the improvement had been achieved by the wave drag reduction.

Internal Drag Evaluation for a Through-Flow Nacelle Using a Far-Field Approach

The main objective of this research is to propose a method for decomposing the total drag of a nacelle into external, internal, and wake drag. From a bookkeeping agreement, the internal drag (i.e., the drag generated inside a nacelle) is the engine manufacturer’s responsibility and is not to be included in the aircraft’s total drag. Consequently, computing the internal drag is mandatory for the airframe and engine constructors concerned and can be achieved either experimentally or by computational-fluid-dynamics analysis. Up to now, aerodynamic engineers have used a near-field approach to compute the internal drag using computational-fluid-dynamics analysis, but this method has serious drawbacks, including its dependency on the accurate location of the stagnation line. The new method proposed here has been applied to multiple two- and three-dimensional test cases, and results show that it is independent of the location of the stagnation line and yields accurate results that agree well with experimental an...

Improvements in accuracy and efficiency for a far-field drag prediction and decomposition method

An advanced drag prediction method, based on a volumetric integration and derived from the fareld method, has recently been proposed. This powerful method allows for the extraction of spurious drag introduced by arti cial dissipation from a CFD solution. This method also allows for the breakdown of drag into its physical sources. Until now, this method has required a fully converged CFD solution in order to ensure accurate results. At its rst contribution, this paper states a less restrictive convergence criterion that ensures accurate results. Its second contribution is to render this method compatible with various kinds of solver by suggesting a way to avoid interpolating a gradient, as this interpolation is generally a source of numerical error.

Interpolation of Transonic Flows Using a Proper Orthogonal Decomposition Method

A proper orthogonal decomposition (POD) method is used to interpolate the flow around an airfoil for various Mach numbers and angles of attack in the transonic regime. POD uses a few numerical simulations, called snapshots, to create eigenfunctions. These eigenfunctions are combined using weighting coefficients to create a new solution for different values of the input parameters. Since POD methods are linear, their interpolation capabilities are quite limited when dealing with flow presenting nonlinearities, such as shocks. In order to improve their performance for cases involving shocks, a new method is proposed using variable fidelity. The main idea is to use POD to interpolate the difference between the CFD solution obtained on two different grids, a coarse one and a fine one. Then, for any new input parameter value, a coarse grid solution is computed using CFD and the POD interpolated difference is added to predict the fine grid solution. This allows some nonlinearities associated with the flow to be introduced. Results for various Mach numbers and angles of attack are compared to full CFD results. The variable fidelity-based POD method shows good improvement over the classical approach.

Far-field drag prediction and decomposition method for unsteady flows

Fareld drag prediction and decomposition methods are powerful tools that increase the accuracy of the drag coe cient computed from CFD results by removing the spurious drag caused by numerical procedures. Furthermore, these methods allow a physical decomposition of the drag in terms of viscous, wave and induced drag. However, these methods are currently limited to steady ows. This paper presents a new drag prediction and decomposition method relevant to unsteady ows. This new method is de ned for both inertial or non inertial coordinate systems, hence allowing drag decomposition either on static, or on moving/rotating mesh. This new method also led to the identi cation of a type of drag caused by the unsteady uctuations of the ow. This method is designed for 3D viscous, subsonic or transonic ows.