### Applications

- Transonic Aerodynamics
- External Aircraft Component Design

### Models active in this Validation Case

- Compressible flow
- Energy models
- Ideal gases
- Double Precision

### Objective

To profile the accuracy and performance of Envenio’s EXN/AERO manycore CFD solver on a challenging transonic aerospace test case.

### Reference Case Description – ARA-M100 Wingbody

The ARA M100 wing body geometry is based on a scale wind tunnel model and is referenced by NASA as a validation case for CFD codes with compressible / transonic flow capability. The configuration of the model is similar to what is seen in civil and military transport aviation and features a finite wing, a realistic wing root and a fuselage. Dimensions are shown in Figure 1.

Figure 1: ARA M100 general dimensions. Image source referenced in bibliography.

### Mesh Description

#### Surface Mesh:

The surface mesh used to create the CFD grid is available on the nasa.gov site (link in bibliography). General dimensions are shown in Figure 1

#### Coordinates & Domain Size

X direction Roll axis, positive streamwise

Y direction Pitch axis, positive to starboard

Z direction Yaw axis, positive to top of aircraft

X dimension ~41m

Y dimension ~21.75

Z-dimension ~41m

#### Position of model:

Upwind face relative to inlet: ~20.5 m

Y position Centred

Z position Attached to symmetry plane

#### Mesh Resolution in the vicinity of the Ahmed Body:

This 3D wing/body test case is at Ma.=0.803 and chord Reynolds number Rec = 13.1 × 106. The mesh has a distribution as follows:

The mesh generator was instructed to use a wall function over the fuselage and direct solve-to-wall was employed on the wing. Freestream turbulence levels used as mesh generator inputs are Tu = 0.5% and µt/µ = 25.

#### Total Mesh Size: ~28.1 Million

### Simulation Completion Criteria

The simulation should be run for at least two ‘wash throughs’ of initial conditions in order to obtain accurate surface pressure values. For cases where far-field values are constant and equal to the initial conditions it is appropriate to use body length (i.e. wing chord) as the reference length. The number of iterations N for a washthrough is calculated using the equation below:

where c is fuselage length, is the mean velocity magnitude and is the time step duration. After time step N is reached, the engineer monitored the total body forces and stopped the simulation when the cumulative average force reached a statistically steady value in time.

### Simulation Setup

#### Solver Control

Time Step 2e-6 seconds

EXN GPU Allocation 3 Nvidia K80

EXN CPU Allocation 3 Intel Xeon 2.6GHz

X-axis orientation Positive downstream

Y-axis orientation Positive to the left of the body, looking downstream

Z-axis orientation Positive upward, normal to ground plane

#### Boundary Conditions

Kinetic Energy 0.0001

K Dissipation 0.0003

Wall model Smooth wall

Outlet Zero Pressure

Initial Velocity [257.1, 0, 12.9]

Angle of Attack 2.870 deg

Mach Number 0.803

Initial Kinetic Energy 0.0001

Initial K Dissipation 0.0003

Temperature 255 Kelvin

Pressure 315.98 kPa

#### Fluid Settings

Initial Velocity [257.1, 0, 12.9]

Initial Kinetic Energy 0.0001

Initial K Dissipation 0.0003

Turbulence Model Unsteady RANS, k-omega

Flow type Compressible

Precision Double in all mesh blocks

Constant Density 1.3864 kg/m^{3}

Constant Viscosity 1.715 x 10^{-5}

#### Other notes

Wash through time 0.0024 seconds (1200 time steps)

Total simulated time 0.013 seconds (17890 time steps, 2.5 washthroughs)

Mesh Topology Structured multiblock, one-to-one connections at block interfaces, data written as structured arrays in CGNS format

### Simulation Outcomes, Timing, and External Factors

The pressure coefficient profiles at different spanwise locations along the wing, namely at span-normalized cross section y/B = 0.123, y/B = 0.231, y/b = 0.325, y/B = 0.455, y/B = 0.633 and y/B = 0.817 are presented in Figures 2 thru 7. The pressure distribution across upper wing surface and fuselage is shown graphically in Figure 8. Table 1 shows simulation performance outcomes and Table 2 shows approximate simulation cost information.

Table 1: Simulation performance outcomes

Reporting Item |
EXN/Aero |

Time to 1st wash-through | Simulated time of 0.013 sec requires 6520 time steps.
This is equivalent to real-time |

Time to completion | Simulated time of 0.036 sec requires 1780 time steps
This is equivalent to real time |

Real time per time step | 38sec |

CPU type | Intel Xeon @ 2.6GHz |

CPU cores | 4 |

GPU type | NVIDIA Tesla K80 |

GPU cores | 3 x 2496 CUDA core per card |

Available Memory | 128GB system, 24GB each K80 card |

Table 2: Simulation cost information, assuming an owned system and a single license of EXN/Aero, operating year-round; figures in US dollars.

Line Item |
Value |

Capital & Operating / hour | $1.52 |

License / hour | $3.42 |

Compute Cost / hour | $4.95 |

Timesteps | 17,980 |

Timesteps / hr | 94.7 |

MSM (timestep / $) | 19.16 |

Total Simulation Cost | $938.64 |

Figure 2: Comparison of EXN/Aero simulation and experimental results at y/B=0.123

Figure 3: Comparison of EXN/Aero simulation and experimental results at y/B=0.231

Figure 4: Comparison of EXN/Aero simulation and experimental results at y/B=0.325

Figure 5: Comparison of EXN/Aero simulation and experimental results at y/B=0.455

Figure 6: Comparison of EXN/Aero simulation and experimental results at y/B=0.633

Figure 7: Comparison of EXN/Aero simulation and experimental results at y/B=0.817

Figure 8: Pressure coefficient contours at the cross section

The comparison of pressure coefficient profiles with the experimental profiles reveals that our model matches closely with the experiments in subsonic regions of the wing. For the two outboard wing sections (y/B 0.633) the Cp distribution is accurately represented by simulation data. For inboard sections (y/B < 0.633) the drop in Cp is delayed and smoother than the experimental data. Inset images from a Cobalt simulation using the Spalart-Almaras RANS model show an early drop in Cp on inboard sections. It is expected that mesh refinement in the vicinity of the shocks will bring EXN/Aero results more in line with experimental data sets; this work is planned as part of Enveino’s QA process and will be updated regularly on Envenio’s wiki site (accessible on envenio.ca).

### Keywords

- External Flow
- SST-RANS
- Compressibility
- Energy Models
- Double Precision
- Integrated Boundary Values
- External Flow
- Lift & Drag
- Vehicle Maneuvering
- Transonic Flow

### References

- Wing geometry available from https://cfl3d.larc.nasa.gov
- /Cfl3dv6/cfl3dv6_testcases.html
- ARAA-M100 Diagrams (Figure 1) http://www.memoireonline.com/05/12/5815/m_Calcul-des-performances-aerodynamiques-de-la-configuration-aile-fuselage-Ara-M100-par-maillage-hybr27.html