NACA 0012 Low Speed Airfoil
Contents
6.1. NACA 0012 Low Speed Airfoil#
6.1.1. Introduction#
The purpose of this case study is to verify and validate the functionality of the Flow360 solver and the implementation of the SpalartAllmaras (SA) and Menter’s \(k  \omega\) shear stress transport (SST) turbulence models, with respect to the NACA 0012 low speed airfoil validation case. This is one of the cases originally provided by the NASA Langley Turbulence Modeling Resource database with accurate and uptodate information on widelyused turbulence models, as also described by the ONERAelsA website. Recent highaccuracy numerical investigations on asymptotic grid convergence behaviors over three families of nested grids are described on this NASALaRCTMR webpage. Similar validation results from OVERFLOW were documented by Jespersen et al.
In this study, Reynoldsaveraged NavierStokes (RANS) simulations utilizing the SA and the SST turbulence models were performed at the same operating conditions as given on those webpages. According to these major conclusions: 1st, the trailing edge streamwise spacing has profound influence on the airfoil lift and moment results, and the grid of Family II yields the most accurate results; 2nd, numerical schemes incorporated with 2ndorder accuracy for turbulence advection are desirable for better asymptotic grid convergence; in the current validation cases, the grid of Family II at Level4 and 2ndorder accuracy for turbulence model equation were utilized. This grid resolution is comparable to that used in the reference validation cases. Current numerical results were validated with respect to available experimental data, as well as other CFD results where appropriate.
6.1.2. Mesh and Flow Configuration#
From the three series of nested grids with varying trailing edge streamwise spacing, available from this NASA webpage, we used the grid of Family II at Level4 (FMLY2GL4, with a grid resolution of 897 x 2 x 257) for this validation. The geometry and the mesh of this quasi3D CFD model are shown in Fig. 6.1.1. As seen, the grid has a Ctype topology, wrapping around the airfoil from the downstream farfield, around the lower surface to the upper, then back to the downstream farfield again. Also, in the wake region, the grid connects to itself in a pointmatched manner. The chord length is scaled to unity, and the grid unit is taken to be meter. The origin of the grid coordinates is at the leading edge of the airfoil. The xaxis is in alignment with the chord line. Also, the grid is stretched for one spanwise cell in the negative y direction with the grid spacing of one unit length. For this validation case, the original NASA grids are converted from ADF to HDF5 data format and are available here.
As suggested by NASALaRCTMR and ONERAelsA, for this essentially incompressible flow, the freestream Mach number is \(M_{\infty} = 0.15\), the Reynolds number per chord length is \(Re_{c} = 6 \times 10^6\), and the reference temperature is \(T_{ref} = 300 K\). The turbulent flow past the airfoil was simulated at each of three angles of attack, i.e. \(\alpha = 0^o\), \(10^o\) and \(15^o\). Table 6.1.1 summarizes the key flow configuration parameters for Flow360. Detailed descriptions about the nondimensional inputs and the model configurations are given in those sections of this online documentation.
Parameters 
Units 
Values 
Notes 

\(L_{gridUnit}\) 
\(m\) 
\(1\) 
Grid unit length 
\(Re_{L_{gridUnit}}\) 
\(6 \times 10^6\) 
Reynolds number 

\(M_{\infty}\) 
\(0.15\) 
Freestream Mach number 

\(T_{ref}\) 
\(K\) 
\(300\) 
Reference temperature 
\(\frac{\mu_{t}}{\mu_{\infty}}\) 
Freestream turbulent viscosity ratio 

\(0.210438\) 
default for SA model within Flow360 

\(0.009\) 
the default value is \(0.01\) for SST model within Flow360 

\(\alpha\) 
\(deg\) 
\(0, 10, 15\) 
Angle of attack 
\(\text{CFL}\) 
\(100\) 
CFL number 

\(\text{AbsTol(NS)}\) 
\(\text{1E12}\) 
Residual convergence tolerance for NS equations 

\(\text{AbsTol(SA/SSTm)}\) 
\(\text{1E10}\) 
Residual convergence tolerance for SA/SST(m) equations 

The “NoSlipWall” boundary condition is applied to the adiabatic viscous surface of the airfoil, and “SlipWall” is used as the symmetry condition in the spanwise direction. The “Freestream” boundary condition is utilized in the farfield, together with the default value of the freestream “turbulentViscosityRatio”, i.e. \(\frac{\mu_t}{\mu_{\infty}} = 0.210438\) for the SA model. This is equivalent to the boundary value based on the SA approximate turbulent kinematic viscosity \(\tilde{\nu}\), i.e. \(\frac{\tilde{\nu}}{\nu_{\infty}} = 3\), as used in the CFL3D predictions. More descriptions about these freestream turbulence boundary conditions can be found from this NASA webpage on the SpalartAllmaras turbulence model.
Similarly, for the SST model, the value of \(0.009\) is used for the freestream “turbulentViscosityRatio”, i.e. \(\frac{\mu_t}{\mu_{\infty}} = 0.009\). The same value is used in the reference results, such as those CFL3D predictions, where a freestream turbulence intensity, i.e. \(T_u = \frac{u_{rms}}{U_{\infty}} = 0.052\%\) was also specified. More descriptions about these freestream turbulence boundary conditions can be found from this NASA webpage on Menter’s SST turbulence model. Notably, a modified version of the SST turbulence model was incorporated into CFL3D. This is denoted as the SST(m) in Table 6.1.1 and the following. As described on the NASA webpage, this simplified version is exact for incompressible flows and is considered typically a very good approximation, except perhaps for very high Mach numbers. This is also the version implemented in Flow360.
Steadystate solutions were computed iteratively, utilizing 2ndorder schemes for both the time averaged NavierStokes and the turbulence model equations. For the former, the CFL number was gradually ramped up to 100. Typically, the values of the absolute nonlinear residual convergence tolerances were set to be \(1 \times 10^{12}\) and \(1 \times 10^{10}\) for the RANS and the turbulence model equations, respectively. Detailed Flow360 solver and mesh configuration files, Flow360.json and Flow360Mesh.json, are given here as an example for the case utilizing the SA model with a Rotation/Curvature (R/C) correction at \(\alpha = 15^o\). For the same case with the SST(m) model, the solver configuration file is available here. The definitions of the angle of attack \(\alpha\) and the sideslip angle \(\beta\), with respect to the grid coordinates, are given as Eq.(8.1.8) in the nondimensional inputs knowledge base.
6.1.3. SA/SARC Model Results#
Twodimensional steady viscous mean flows past the NACA 0012 airfoil were simulated at the aforementioned operating conditions. Aerodynamic characteristics were visualized through contour plots of Mach number and turbulent viscosity ratio on the longitudinal cutplane at \(y = 0.5\). The results of the RANS simulations based on the SA model with the R/C correction are shown in Fig. 6.1.2, Fig. 6.1.3 and Fig. 6.1.4 for the three angles of attack, respectively.
As seen from the above figure, for the zero lift condition at \(\alpha = 0^o\), symmetric flow patterns are established along the chord line at \(z = 0\).
For a relatively high lift condition at \(\alpha = 10^o\), a large wake region trailing down from the airfoil is observed.
Also, as expected, at a higher angle of attack \(\alpha = 15^o\) towards the operating condition for \(C_{L,max}\), the flow starts to separate from the upper surface near the trailing edge. This is shown in the above figure where detachment of the contour line of \(M = 0\) occurs at a more detailed level.
For these operating conditions, surface distributions of pressure and skin friction coefficients, i.e. \(C_p = \frac{p  p_{\infty}}{0.5 \cdot \rho_{\infty} \cdot U^2_{ref}}\) and \(C_f = \frac{\tau_w}{0.5 \cdot \rho_{\infty} \cdot U^2_{ref}}\), are examined in Fig. 6.1.5, Fig. 6.1.6 and Fig. 6.1.7, with respect to reference data. In these figures, Flow360 results are indicated as the red solid and the green dashed lines for the SA model without and with the R/C correction, respectively. The corresponding CFL3D results are shown as the blue dashed and dashdot lines. Experimental data are given as symbols. Notably, these measurements of \(C_p\) were made at a lower Reynolds number \(Re_c = 2.88 \times 10^6\) by Gregory and O’Reilly.
As seen from the above figures, at all the three distinct lift conditions, Flow360 predictions accurately capture the experimental data, and closely match the counterparts of the reference numerical results. Notably, as shown in Fig. 6.1.7 associated with \(\alpha = 15^o\), the \(C_f\) value of the current result with the SA model approaches zero around \(x/c = 0.9078\) on the upper surface of the airfoil near the trailing edge. This indicates separated mean flow occurs as observed from the previous Fig. 6.1.4. For the current result with the SARC model, the separation point emerges around \(x/c = 0.8992\). These locations are at the upstream bounds of the suggested intervals as given on the NASA webpages. For the same operating condition, CFL3D predicted that the separation point emerged around \(x/c = 0.9163\) or \(0.9046\) for the cases with the SA or the SARC models, respectively.
The integrated \(C_L\) and \(C_D\) values of the current predictions are summarized in Table 6.1.2, Table 6.1.3 and Table 6.1.4 for \(\alpha = 0^o\), \(10^o\) and \(15^o\), respectively, together with available reference CFD data. As seen, for all the tested operating conditions, the accuracy of Flow360 results are comparable.
Codes 
Turb Mdl 
\(\alpha (deg)\) 
\(C_L\) 
\(C_D\) 
\(C_{D,v}\) 
\(C_{D,p}\) 

CFL3D 
SA 
0 
0.685E05 
0.00819 

FUN3D 
SA 
0 
\(\simeq 0\) 
0.00812 

NTS 
SA 
0 
\(\simeq 0\) 
0.00813 

JOE 
SA 
0 
\(\simeq 0\) 
0.00812 

SUMB 
SA 
0 
\(\simeq 0\) 
0.00813 

TURNS 
SA 
0 
\(\simeq 0\) 
0.00830 

GGNS 
SA 
0 
\(\simeq 0\) 
0.00817 

OVERFLOW 
SA 
0 
\(\simeq 0\) 
0.00838 

FLOW360 
SA 
0 
8.648E07 
0.00808 
0.006811 
0.001267 
CFL3D 
SARC 
0 
0.717E05 
0.00793 

FUN3D 
SARC 
0 
\(\simeq 0\) 
0.00790 

NTS 
SARC 
0 
\(\simeq 0\) 
0.00792 

FLOW360 
SARC 
0 
7.960E07 
0.00787 
0.006611 
0.001256 
It is noted that, for some of these representative aerodynamic quantities, the results of Flow360 are at either the upper or the lower bounds of the reference intervals. It is suspected that this is due to the differences in the discretization, such as nodecentered or cellcentered schemes, as well as convergence criteria, at least as seen from the \(C_L\) values at \(\alpha = 0^o\). It is also noted that the reference data such as those CFL3D results were computed with the farfield point vortex (PV) correction based on inviscid characteristic methods as given by Thomas and Salas. At the current accuracy level for validation with farfield boundaries about 500 chords away, its effects would be inappreciable.
Codes 
Turb Mdl 
\(\alpha (deg)\) 
\(C_L\) 
\(C_D\) 
\(C_{D,v}\) 
\(C_{D,p}\) 

CFL3D 
SA 
10 
1.0909 
0.01231 

FUN3D 
SA 
10 
1.0983 
0.01242 

NTS 
SA 
10 
1.0891 
0.01243 

JOE 
SA 
10 
1.0918 
0.01245 

SUMB 
SA 
10 
1.0904 
0.01233 

TURNS 
SA 
10 
1.1000 
0.01230 

GGNS 
SA 
10 
1.0941 
0.01225 

OVERFLOW 
SA 
10 
1.0990 
0.01251 

FLOW360 
SA 
10 
1.0889 
0.01244 
0.006148 
0.006292 
CFL3D 
SARC 
10 
1.0947 
0.01179 

FUN3D 
SARC 
10 
1.1020 
0.01191 

NTS 
SARC 
10 
1.0933 
0.01193 

FLOW360 
SARC 
10 
1.0917 
0.01193 
0.005851 
0.006079 
CFL3D(TMNA, noPV) 
SA 
10 
1.0896 
0.01240 
0.006203 
0.006200 
FUN3D(TMNA, noPV) 
SA 
10 
1.0910 
0.01239 
0.006206 
0.006179 
TAU(TMNA, noPV) 
SA 
10 
1.0905 
0.01233 
0.006216 
0.006117 
Importantly, a different computational grid with substantially finer trailing edge streamwise spacing is used for the current cases. As described on the NASA webpage, before June 23, 2014, there was a typo in the slightly scaled version of the formula that was used to generate the NACA 0012 airfoil profile. This caused a slight nonclosure of the order of \(1 \times 10^{8}\) at the trailing edge, and affected the earlier grid files, as well as the corresponding numerical results as refered to here. This issue would not have significant influence at the accuracy level required for validation purpose. However, it has been shown that the trailing edge streamwise spacing has profound influence on the airfoil lift and moment results, as analysed by Diskin et al and Atkins.
Since the typo discovered, thorough highaccuracy numerical analysis had been performed to reveal scenarios such as grid convergence, etc. Details of these updated investigations are given on this turbulence model numerical analysis (TMNA) webpage of NASA, as well as the ONERAelsA webpage. These updated data of \(C_L\) and \(C_D\) computed on the same grid as used in this study without the farfield PV correction, available only at \(\alpha = 10^o\), are also given in Table 6.1.3. These are at the bottom of the table and denoted by (TMNA, noPV). As seen, the agreement of Flow360 results with respect to these updates are closer.
Codes 
Turb Mdl 
\(\alpha (deg)\) 
\(C_L\) 
\(C_D\) 
\(C_{D,v}\) 
\(C_{D,p}\) 

CFL3D 
SA 
15 
1.5461 
0.02124 

FUN3D 
SA 
15 
1.5547 
0.02159 

NTS 
SA 
15 
1.5461 
0.02105 

JOE 
SA 
15 
1.5490 
0.02148 

SUMB 
SA 
15 
1.5446 
0.02141 

TURNS 
SA 
15 
1.5642 
0.02140 

GGNS 
SA 
15 
1.5576 
0.02073 

OVERFLOW 
SA 
15 
1.5576 
0.02149 

FLOW360 
SA 
15 
1.5381 
0.02158 
0.005112 
0.016473 
CFL3D 
SARC 
15 
1.5560 
0.02066 

FUN3D 
SARC 
15 
1.5651 
0.02099 

NTS 
SARC 
15 
1.5562 
0.02043 

FLOW360 
SARC 
15 
1.5467 
0.02100 
0.004707 
0.016288 
The corresponding \(C_L\) and \(C_D\) data given in the above tables are also displayed in Fig. 6.1.8, together with the experimental data measured by Ladson. Notably, in this figure, at lowtomoderate angles of attack, linear variation of \(C_L\) with the best fit lift slope provided by McCroskey is also shown. As seen, the current results agree well with these references. More discussions about the experimental data compared in this and the above figures are given on this NASALaRCTMR webpage.
6.1.4. SST(m) Model Results#
Similar to the above subsection, Flow360 results computed with the SST(m) model are examined in this subsection. Aerodynamic characteristics were visualized through contour plots of Mach number and turbulent viscosity ratio on the longitudinal cutplane at \(y = 0.5\). Typical results are shown in Fig. 6.1.9, Fig. 6.1.10 and Fig. 6.1.11 for the three angles of attack, respectively. Similar flow characteristics as discussed earlier are observed.
For these operating conditions, surface distributions of pressure and skin friction coefficients are examined in Fig. 6.1.12, Fig. 6.1.13 and Fig. 6.1.14, with respect to reference data. In these figures, Flow360 results are indicated as the red solid lines. The corresponding CFL3D results are shown as the blue dashed lines. Also, in these figures, experimental data are given as symbols. These are the same measurements of \(C_p\) made by Gregory and O’Reilly as previously given in Fig. 6.1.5, etc.
As seen from the above figures, at all the three distinct lift conditions, Flow360 predictions accurately capture the experimental data, and closely match CFL3D results. Notably, as shown in Fig. 6.1.14 associated with \(\alpha = 15^o\), the \(C_f\) value of the current result with the SST(m) model approaches zero around \(x/c = 0.9834\) on the upper surface of the airfoil near the trailing edge. This indicates separated mean flow occurs as observed from Fig. 6.1.11. For the same operating condition, CFL3D predicted that the separation point emerged around \(x/c = 0.9868\). Similarly, this is located at around \(x/c = 0.9882\) as predicted by OVERFLOW.
The integrated \(C_L\) and \(C_D\) values of the current predictions are summarized in Table 6.1.5, together with available reference CFD data. As seen, for all the tested operating conditions, the accuracy of Flow360 results are comparable. The discrepancies are perhaps attributed to the same aspects as discussed in the previous section.
Codes 
Turb Mdl 
\(\alpha (^o)\) 
\(C_L\) 
\(C_D\) 
\(C_{D,v}\) 
\(C_{D,p}\) 

CFL3D 
SST(m) 
0 
0.763E05 
0.00809 

FUN3D 
SST(m) 
0 
\(\simeq\) 0 
0.00808 

NTS 
SST(m) 
0 
\(\simeq\) 0 
0.00809 

OVERFLOW 
SST 
0 
\(\simeq\) 0 
0.00821 

FLOW360 
SST(m) 
0 
8.704E06 
0.00803 
0.006724 
0.001301 
CFL3D 
SST(m) 
10 
1.0778 
0.01236 

FUN3D 
SST(m) 
10 
1.0840 
0.01253 

NTS 
SST(m) 
10 
1.0765 
0.01251 

OVERFLOW 
SST 
10 
1.0847 
0.01262 

FLOW360 
SST(m) 
10 
1.0800 
0.01256 
0.006141 
0.006417 
CFL3D 
SST(m) 
15 
1.5068 
0.02219 

FUN3D 
SST(m) 
15 
1.5109 
0.02275 

NTS 
SST(m) 
15 
1.5100 
0.02187 

OVERFLOW 
SST 
15 
1.5094 
0.02288 

FLOW360 
SST(m) 
15 
1.5022 
0.02300 
0.005222 
0.017777 
The corresponding \(C_L\) and \(C_D\) data given in the above table are also displayed in Fig. 6.1.15, together with the experimental data measured by Ladson. Notably, in this figure, at lowtomoderate angles of attack, linear variation of \(C_L\) with the best fit lift slope provided by McCroskey is also shown. As seen, the current results agree well with these references.
6.1.5. Remarks#
Through this validation study, the flow field, the surface data and the representative aerodynamic quantities predicted by Flow360 were carefully examined. With respect to the latest reference numerical results computed on the same grid as used here, the available agreement on \(C_L\) and \(C_D\) reaches the third significant digit. For the cases with the SA model, the solver version is release22.1.3.0; where with the SST(m), the same implementation was used as incorporated in the solver of release22.2.3.0.