Modeling, Structural & CFD Analysis and Optimization of UAV
Dr Lazaros Tsioraklidis
Department of Unified Engineering
InterFEA Engineering, Tantalou 7 Thessaloniki GREECE
Next Generation tools for UAV’s
The current paper present the usages of Hyperworks on the design of New ages Aerostructures as UAV's.
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UAV marketplace a moving target
UAVs are now in service in more than 50 countries.
During 2007, these aircraft logged more than 500,000 flight hours, increase by logarithmic rate.
Thousands of different aircraft in various stages of design, development or production.
70 active companies and nearly 200 unique platforms enter production or currently under development.
Top 30 programs accounted for ~3,000 aircraft deliveries during 2008 and will deliver 3,350 more during 2009 — about 93 percent of the delivery total. Over the next five years, the same programs will deliver about 13,000 aircraft. Over our 2009-2018 forecast period, they will account for close to 65 percent of expected UAV deliveries.
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UAV’s Future
“Teal Group's 2010 market study estimates that UAV spending will more than double over the next decade from current worldwide UAV expenditures of $4.9 billion annually to $11.5 billion, totaling just over $80 billion in the next ten years.”
“A new study reflects the rapid growth of interest in the UAV business by increasing the number of companies covered to almost 30 U.S., European and Israeli companies, and reflect the fundamental reshaping of the industrial environment”
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Types of UAV’s
• Target drones — UAVs that simulate enemy missiles or aircraft in the demonstration and testing of antiaircraft and antiship missiles systems. • Radar decoys — Unmanned decoy aircraft deployed from a larger manned aircraft and designed to subvert, confuse or fool enemy radar systems. • Information, surveillance and reconnaissance (ISR) aircraft — UAVs that perform a variety of surveillance, observation and data-relay missions. For combat troops on the ground, small UAVs, including micro-UAVs (handheld/hand launched), provide “over-the-hill” scouting, to avoid ambushes and scare off insurgents. • Unmanned combat aerial vehicles (UCAVs) — Aircraft designed to provide unmanned weapons capabilities and support manned aircraft. Their capabilities include the use of bombs and missiles, electronic warfare equipment and directed-energy weapons.
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Hyperworks A platform for Innovation
Altair Hyperworks is an engineering simulation environment which can use from engineers during all stages of the Design and Optimization of UAV's. From design stage when the engineer tests and validates new Shapes and mechanism and determine correct shapes for the engine inlet, determines optimum composite structure, reduce weight and provide more Payload.
Modern FE Modeling
Robust CFD solver
Motion Dynamic
PA speed up projects
linear and non-linear simulations
Ultimate post processing
Explore, Study, Optimize
Reduce weight
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CFD Analysis & Optimization on UAV
From Design to the Reality of Flow Challenges Low Drag Cd High lift CL Less Noise Eliminate Turbulence
First 3D Design
Modeling for CFD
Shapes for Optimization
Coupling CFD +
Optimization code
Post Processing
Determination of pressure distribution on the surface of the UAV that later on leads to calculations of aerodynamics characteristics of uav such as CL, CD and CM at various angle of attack Visualization of the airflow around the UAV using Post Processing to recognize some critical area with possible vortex reduction in the near future. The analytical of aerodynamics characteristics for various angles of attacks using CFD simulation will be conducted in this final stage
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High Quality meshing for CFD
By using Hypermesh the total cost on human hours from Geometry cleanup to tetra mesh reduced by 60%. Special tools as Layer meshing & Refinement box option provides fast and accurate mesh for CFD analysis.
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CFD Optimization of the Wing shape
The NACA 4412 Airfoil choose as an option for the UAV’s wing, the NACA 4412 profile provides high CL on low speed for subsonic aircrafts. Several shapes (50) created for the optimization of the wing for reducing the CD and increase CL, in the same time several constrains have to be satisfied as volume and turbulence.
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Optimized wing
The optimization of the wing create optimize performance as : Cd reduction = 35% CL increased =5% Turbulence reduction = 21%
Initial
Optimized Cd /Iteration
Cd
Iterations
Optimized
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Optimized wing on several angles of attack
For each wind tunnel airspeed, the value of CL increases as the angle of attack is increased until its maximum value at around α = 35º and decreases afterwards with lower slope. Computational Fluid Dynamics (CFD) results at Mach 0.6 and 0.8 also give the same trend with maximum CL located at α = 39º and α = 35º respectively. It is observed that the value of CLmax increases as the air velocity of the wind tunnel is increased. Hence, the CL max increases with the increase of Reynolds number. This explains the difference of values of CL max between the experiments and the CFD.
Drag Coefficient Analysis
Lift Coefficient Analysis
The variation of drag coefficient (CD) versus angle of attack (α) taken at different air speeds and Mach numbers. It is observed that the variation of drag coefficient is very slow and almost constant at low angle of attacks (below 8º). In that range of α, CD is small, below 0.03 for both experiments and CFD. As explained in the previous section, at low angle of attack, the air flow is still attached to the body and the wing. Above 8º, CD grows at higher rate as α is increased. Within this range, the wing is already in stall condition. Around 35º, a slight deflection occurs on wind tunnel experiment curves. This is where the lift coefficient reaches its maximum value. This deflection is not clearly seen on the CFD curves. Beyond this angle of attack, the drag coefficient continues to increase with almost the same slope as between 8º and 34º, and it is getting slower when α approaches 90º. From the overall curves, it is observed that higher airspeeds (or higher Reynolds number) produce higher drag coefficients.
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Nose Optimization
The optimization of the Nose create optimize performance as : Cd reduction = 18% CL increased =2% Turbulence reduction = 10%
Morph volume & Shapes
Initial
Optimized
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Engine inlet Optimization
The optimization of the Engine Inlet create optimize performance as : Cd reduction = 10% CL increased =2.89% Turbulence reduction = 12%
Morph volume & Shapes
Initial
Optimized
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Conclusions of the CFD & Structural Optimization
CFD Optimization Conclusions CFD Analysis & Optimization Cd Reduction : 51 % CL Increased : 9.89 %
Optimized Turbulence flow
Optimized Inlet for Better Engine Performance
Cd = Fuel Consumption Reduction
CL = Optimized Flight Load
Stabilization Problems Solved
Combat Radius Increased
34%
Max take off load increased
10 %
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Structural Analysis and Optimization
Load transfer from Acusolve to Hypermesh for Linear Analysis and Optimization
Data from: Angles of Attack 00, 50, 150, 200
Aerodynamic loads on the wing from extra external fuel tanks External Devices as cameras etc
Linear
Interpolation
Pressure on the UAV surface Structural model of the UAV
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Structural Analysis of the UAV wing
Analysis 25 Loadcases (strength, pressure) 370.000 Elements 15 Material types 842 Plies 145 Laminates
Aerodynamic Pressure on the wing surface
Composite Structure
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Deformation of the wing at angle of attack 00 Stresses on the wing at angle of attack 00
Structural Analysis of the UAV wing
The UAV Wing is made by CFRP Material, several parts are assembled to create the wing. The deformation of the wing and the stresses have been calculated by using Radioss (Bulk). The traditional design of the CFRP wing provide us a heavy structure
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Optimization of the CFRP wing using Optistruct
The optimization of the composite wing includes the optimization of each part composite - metal Loads : 25 loadcases (same as analysis) Model : 370 000 elements (same as analysis) Objective : Reduce Weight Safety Constrains : Strength, stability, strain Manufacturing Constrains : Thickness, Stacking etc
Optimal Structure
Skin Optimization
Ribs Optimization
Spars Optimization
Metal Parts Optimizaiton
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Optimization of the CFRP wing using Optistruct
Steps of the wing skin optimization using Optistruct
• Free-size optimization is used to identify the optimal ply shapes and locations of patches per ply orientation
• Size optimization is used to identify the optimal thicknesses of each ply bundle
• Shuffling optimization is used to obtain an optimal stacking sequence
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Optimization of the CFRP wing using Optistruct
Free size optimization of the skin 4 Plies with angles 0, 90, 45, -45 Thickness of each ply 4 mm Manufacturing Constrain : 00 & 900 min - 10% , max- 70%
Thickness of the Ply of 450
Thickness of the Ply of -450
• Weight Reduction 32%
Thickness of the Ply of 900
Thickness of the Ply of 00
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Optimization of the CFRP wing using Optistruct
Size optimization In the second design phase, a size optimization is performed to fine tune the thicknesses of the optimized ply bundles from Phase 1. To ensure that the optimization design meets the design requirements, additional performance criteria on natural frequencies and composite strains are incorporated into the problem formulation.
Design variables: Ply thicknesses, which have been defined in the size input deck from Phase 1 Objective: Minimize the total designable volume Constraints: •Natural frequencies (1st ~ 5th) > 0.06 KHz •Composite strains in the wing < 1800 micro-strain •Ply Thicknesses available 0,1 – 0,2- 0,3 – 0,4 mm
Plies of 00 in several point
Thickness 0.1 mm Thickness 0.2 mm
Thickness 0.25 mm Thickness 0.3 mm
Plies of 900 in several point
Thickness 0.1 mm Thickness 0.2 mm
Thickness 0.25 mm Thickness 0.3 mm
• Weight Reduction 32%
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Optimization of the CFRP wing using Optistruct
Shuffling optimization Shuffling optimization is used to obtain an optimal stacking sequence Design variables: Stacking seguence Objective: Optimize the stacking seguence Constraints: 1) The maximum successive number of plies of a particular orientation does not exceed 4 plies. 2) The + 45s and – 45s are reversed paired
• Weight Reduction 32%
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Optimization using Optistruct
Optimization Conclusions Composite Parts Optimization Total Weight Reduction 38 % Stiffness Increased 12% Stresses Decreased 30 % Deformation Decreased 15%
Mainfuseland
Wingstructure
Fuse skinSub
structures
Optimized Initial
39 % 32 %
25 % 22 %
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Optimization of other parts
Overall Structure Optimization 198 Parts Optimized with Optistruct 124 Composite parts 23 Connections simulated and optimized New material and technologies as Nanotubes in composites tested Manufacturing constrains increase manufacturing time more than 30% Thermal loads from the engine was simulated 24 Different maneuvers loads tested Total time for Development reduce by 40% Topology Optimization used for Ribs Topology Optimization used for Internal structure Turbulence loads during take off and landing that would cause issue eliminated at the stages of development
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Optimization using Acusolve & Optistruct
Overall Conclusions
Payload
450 Kg
Payload
260 Kg
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Combat Radius
Increased by 45%
InterFEA Engineering
Innovative Engineering Solutions
Tantalou 7
Thessaloniki
GREECE
Thank you
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