Aerospace Applications and Case Studies Deryl Snyder,...

Aerospace Applications and Case Studies

Deryl Snyder, Ph.D.

Classical / Semi-Empirical / Vortex Methods – Feasibility studies – Determine problem bounds – Perform initial sizing/trades

CFD – Higher fidelity solutions to refine the design – Refined performance estimates – Identify possible trouble areas – Identify flow phenomena – Estimate interference/installation effects – Down-select for wind tunnel testing – Determine expected WT loads

(instrumentation selection) Wind tunnel tests – Final down-select – Final aerodynamic performance

Typical Use of CFD in Aerodynamics

Classical / Semi-Empirical / Vortex Methods – Feasibility studies – Determine problem bounds – Perform initial sizing/trades

CFD – Higher fidelity solutions to refine the design – Refined performance estimates – Identify possible trouble areas – Identify flow phenomena – Estimate interference/installation effects – Down-select for wind tunnel testing – Determine expected WT loads

(instrumentation selection) Wind tunnel tests – Final down-select – Final aerodynamic performance

Typical Use of CFD in Aerodynamics

Expanding CFD in the design process:

- Reduces the time and money spent on rig tests

- Provides insight to improve the design

- Reduces the number of design iterations

- Quickly identifies operation limits

- Shortens the development process

This necessitates:

- Faster turnaround times (initial and subsequent design modifications)

- Accurate physics modeling

STAR-CCM+ Integrated Process

Native CAD Geometry

Geometry Cleanup

Robust Unstructured Meshing

Advanced Physics Solution

Reduce overall CAD-to-solution time while maintaining high-end advanced physics

Aerospace Applications Summary Aerodynamics Case Studies – Rotorcraft Hub Drag – Store Separation

New: Continuity Convergence Accelerator

Outline

Aircraft Systems / Thermal Management – Mechanical Systems

(APU’s, undercowling, etc.) – Ice Protection – Avionics / Electronics Systems – Fuel systems – Heat Exchangers – Blade cooling – Other Conjugate Heat Transfer

Aerospace Application Areas




• Propulsion Systems – Pumps – Rocket Motor, Ramjet, & Scramjet – Fans and Turbines – Combustion, sprays, chemistry – Inlets & ducting – Fuel systems, sloshing – Filters – Engine Integration Thermal – SCRAMJET/RAMJET



Aerodynamics – Subsonic, Transonic, Supersonic,

Hypersonic – Aeroacoustics – Store release & weapons bay analysis – High lift devices – Stage separation – Nozzle/Plume analysis – Engine integration Aerodynamics


• Propulsion Systems – Pumps – Rocket Motor, Ramjet, & Scramjet – Fans and Turbines – Combustion, sprays, chemistry – Inlets & ducting – Fuel systems, sloshing – Filters – Engine Integration Thermal



Outline

Motivation – Hub drag is a large fraction of total helicopter drag and can approach

30% of single rotor aircraft – Prediction of total hub drag and the drag of individual components is

desirable to design for reduced drag – Gridding of very complex geometries has been a challenge in the past –

weeks to months – so CFD is not typically used – Can we affordably use CFD today to predict hub drag?

Rotorcraft Hub Drag

Sikorsky UH-60A Hub Sikorsky S-92A Hub

Surface Wrapper Maintain high geometric fidelity

Surface Preparation / Mesh

Trim Cell Mesh, 14.8M Cells Prism Layers – 10 layers for attached flow, y+ = 1 – 4 layers elsewhere, y+ = 20

Volumetric Refinement – To capture wake and turbulent

eddies Sliding Grid – Around moving hub assembly

CAD-to-Mesh Effort – 16 Engineer Hours

Volume Mesh

Detached Eddy Simulation Time Step = 5 deg rotation – Under-resolved for turbulent eddies, but sufficient for drag

Flowfield Results

Pressure Velocity Magnitude S-92A

UH-60A

S-92A

UH-60A

Uinf = 150kt, Rotation = 500rpm Component Buildup Approach – 6 components for S-92A – 3 components for UH-60A

Worst error is < 7% – Significant improvement over current

(non-CFD) techniques

Drag Results

UH-60A

S-92A



Outline

Aerospace Applications – Parametric Studies – Same bodies at different relative

positions / orientations • Aerodynamic databases

– Bodies with complicated motion pattern

• Control surface deflections • Tube/Silo launches • Transient stores separation

– Pylon / Weapons Bay • Rotorcraft blades

Advantages – Arbitrary unstructured meshes – Implicit grid coupling

Overset Mesh

Geometry – Clipped delta wing with pylon – Standard 4-fin store ~10ft in length

Benchmark wind tunnel data available at Mach 1.2 – Trajectory information – Surface pressure

Benchmark: Store Separation

Unstructured Cartesian Trim Cell – Cells refined in region of expected

store travel – Cell refined around store (nose, tips,

wake) – Minimum of 4 cells across the small

1.4” gap between pylon and store 3.8M Cells Overall – 3.0M Farfield/Wing/Pylon – 0.8M Store

Lateral extents located at approximately 100 diameters

Computational Mesh

Density-based Coupled Solver Inviscid Flow – Previous studies have shown this is sufficient for trajectory calculation

2nd-Order upwind spatial discretization 2nd-Order implicit temporal discretization – Implicitly-coupled 6DOF motion – ∆t = 0.01s nominal, and and 0.002s fine

Solver Settings

Ejector Forces Definition

Modeled as arbitrary point loads – Defined through the GUI – Custom functional relationships to

match ejector force and stroke length Visualize loads real-time – Note that initial motion is dominated by

ejector forces

Results – Qualitative

Eglin Wing/Pylon/Store Case – Mach 1.2, 38,000ft Altitude

Results: Velocity / Angular Rate

Results: Surface Pressure

t = 0.00

t = 0.16

t = 0.37

Aerospace Applications Summary Aerodynamics Case Studies – High-Lift Wing – Rotorcraft Hub Drag – Store Separation


Outline

High-Speed Flow Solution Approach

Density-Based Coupled Solver

Proper numerical formulation for high-speed flows

Improved robustness at initial iterations

Automatic convergence control

Faster convergence

Implicit Formulation AUSM+ invisid flux scheme

MUSCL + Venkata limiter

Grid Sequencing Initialization

Expert Solution Driver

Continuity Convergence Accelerator

Expert Option for the Density-Based Coupled Solver – Sub-solver to accelerate mass conservation

Improves convergence for stiff problems – Temperature-dependent gas properties – Multiple species – Mix of high/low Mach numbers – Combustion – Internal compressible flows

V7.06: Continuity Convergence Accelerator

Supersonic Combustion Converges in < 1/10th iterations Mixing Chamber

Converges in 1/2 iterations

Freestream Mach = 0.6 Pressure Ratio = 10.0 TCombustion = 3000K Steady-State, SST k-ω turbulence model

V7.06: Continuity Convergence Accelerator Rocket Motor / Nozzle

With CCA

Without CCA

V7.06: Continuity Convergence Accelerator Hypersonic Shock/Boundary Layer Interaction

• Freestream Mach = 5.0 • Steady-State, SST k-ω turbulence model • Iterations to fully develop separated region:

– No CCA: 12,500 iterations – With CCA: 3,500 iterations

• With CCA, 67% reduction in wall-clock time

V7.06: Continuity Convergence Accelerator High-Pressure Bleed Line / Butterfly Valve

• Stagnation conditions provided at inlet • Steady-State, SST k-ω turbulence model • Engineering items of interest

– Mass Flow Rate – Outflow Total Pressure

• No CCA = 3500 iterations • CCA = 1250 Iterations

Thank You

Aerospace Applications and Case Studies Deryl Snyder,...

Documents

Transcript of Aerospace Applications and Case Studies Deryl Snyder,...