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Integrated Design Optimization of Wind Turbines:
Challenges, Methods, Applications
Carlo L. BottassoTechnische Universität München
Funktionsleichtbau für die Windkenergie – Anforderungen, Möglichkeiten, Nutzen DLR, Braunschweig, 20 September 2016
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Motivation: the Need for Design Tools
Size
Weig
ht (C
ost)
Cubic law of growth
Technological innovation
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Motivation: the Need for Design Tools
Active and passive load
reduction techniques
(source: Timber Tower)
(source: Alstom)
Electromechanical conversionRotor aerodynamics
Materials and structural design
Sensing &
advanced controls
Construction technology
(source: Risø-DTU)
Each innovation will come with pros and cons
Crucial role of design -the final judge-: “Nice idea, but does it reduce the CoE?”
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Pitch-torque control laws:- Regulating the machine at different set points depending on wind conditions- Reacting to gusts- Reacting to wind turbulence- Keeping actuator duty-cycleswithin admissible limits- Handling transients: run-up, normal and emergency shut-down procedures- …
- Annual Energy Production (AEP)- Noise- Transportability-…
- Loads: envelopecomputed from large number of Design Load Cases (DLCs, IEC-61400) - Fatigue (25 year life), Damage Equivalent Loads (DELs)- Maximum blade tip deflections - Placement of natural frequencies wrt rev harmonics- Stability: flutter, LCOs, low damping of certain modes, local buckling- Complex couplingsamong rotor/drive-train/tower/foundations (off-shore: hydro loads, floating & moored platforms)- Weight: massive size, composite materials (but shear quantity is an issue, fiberglass, wood, clever use of carbon fiber)- Manufacturingtechnology, constraints
- Generator (RPM, weight, torque, drive-train, …)- Pitch and yaw actuators- Brakes- …
GE wind turbine (from inhabitat.com)
Wind Turbine Design
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Pitch-torque control laws:- Regulating the machine at different set points depending on wind conditions- Reacting to gusts- Reacting to wind turbulence- Keeping actuator duty-cycleswithin admissible limits- Handling transients: run-up, normal and emergency shut-down procedures- …
- Annual Energy Production (AEP)- Noise- Transportability-…
- Loads: envelopecomputed from large number of Design Load Cases (DLCs, IEC-61400) - Fatigue (25 year life), Damage Equivalent Loads (DELs)- Maximum blade tip deflections - Placement of natural frequencies wrt rev harmonics- Stability: flutter, LCOs, low damping of certain modes, local buckling- Complex couplingsamong rotor/drive-train/tower/foundations (off-shore: hydro loads, floating & moored platforms)- Weight: massive size, composite materials (but shear quantity is an issue, fiberglass, wood, clever use of carbon fiber)- Manufacturingtechnology, constraints
- Generator (RPM, weight, torque, drive-train, …)- Pitch and yaw actuators- Brakes- …
GE wind turbine (from inhabitat.com)
Wind Turbine Design
One load assessment:107÷108 time steps
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Holistic Design of Wind Turbines
There is a need for multi-disciplinary optimization tools, which must:• Be fast (hours/days) (on standard hardware!)
• Provide workable solutions in all areas (aerodynamics, structures, controls) for specialists to refine/verify
• Account ab-initio for all complex couplings (no fixes a posteriori)
• Use fully-integrated tools (no manual intervention)
They will never replace the experienced designer! … but would greatly speed-up design, improve exploration/knowledge of design space
Current approach to design: discipline-oriented specialist groups
Different simulation modelsLengthy loops to satisfy all requirements/constraints
(months)
Data transfer/compatibility among groups
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Motivation: the Need for Combined Aero-Structural Design
Cost model (Fingersh at al., 2006):
𝑪𝒐𝑬 =𝑭𝒊𝒙𝒆𝒅𝑪𝒉𝒂𝒏𝒈𝒆𝑹𝒂𝒕𝒆 ∗ 𝑰𝒏𝒊𝒕𝒊𝒂𝒍𝑪𝒂𝒑𝒊𝒕𝒂𝒍𝑪𝒐𝒔𝒕 𝒑
𝑨𝑬𝑷 𝒑+ 𝑨𝒏𝒏𝒖𝒂𝒍𝑶𝒑𝒆𝒓𝒂𝒕𝒊𝒏𝒈𝑬𝒙𝒑𝒆𝒏𝒔𝒆𝒔 𝒑
where 𝒑 = design parameters
Strong couplings between aerodynamic shape (AEP) and structural sizing (blade cost)
Example:
Spar cap thickness ⇧
Blade thickness ⇩
Reduce solidity to increase efficiency (AEP ⇧)
Consequence: effect on weight ⇧
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Increase solidity
Consequence: effect on weight ⇧
Motivation: the Need for Combined Aero-Structural Design
Cost model (Fingersh at al., 2006):
𝑪𝒐𝑬 =𝑭𝒊𝒙𝒆𝒅𝑪𝒉𝒂𝒏𝒈𝒆𝑹𝒂𝒕𝒆 ∗ 𝑰𝒏𝒊𝒕𝒊𝒂𝒍𝑪𝒂𝒑𝒊𝒕𝒂𝒍𝑪𝒐𝒔𝒕 𝒑
𝑨𝑬𝑷 𝒑+ 𝑨𝒏𝒏𝒖𝒂𝒍𝑶𝒑𝒆𝒓𝒂𝒕𝒊𝒏𝒈𝑬𝒙𝒑𝒆𝒏𝒔𝒆𝒔 𝒑
where 𝒑 = design parameters
Strong couplings between aerodynamic shape (AEP) and structural sizing (blade cost)
Example:
Skin buckling critical load ⇩
Skin core thickness ⇧
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Motivation: the Need for Combined Aero-Structural Design
Example: INNWIND 10 MW HAWT (class 1A, D=178.3, H=119m)
Baseline design by INNWIND consortium
1. Perform purely aerodynamic optimization for max(AEP)
2. Follow with structural optimization for minimum weight
Dramatic reduction in solidity to improve AEP leads to large increase in weight
⇨ CoE increases (+2.6%)
Spar cap ▼Chord ▼
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Cp-Max Rotor Design Environment
First release: 2007, improved and expanded since then
Applications: academic research and industrial blade design
Cost:AEPAerodynamic parameters:chord, twist
Cost:Blade weight (or cost model if available)Structural parameters:thickness of shell and spar caps, width and location of shear webs
Cost:Physics-based CoEParameters:Aerodynamic and structural
Controls:model-based (self-adjusting to changing design)
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inesCp-Lambda highlights:
• IEC 61400 compliant (DLCs, wind models)
• Geometrically exact composite-ready beam models
• Generic topology (Cartesian coordinates+Lagrange multipliers)
• Dynamic wake model (Peters-He, yawed flow conditions)
• Efficient large-scale DAE solver with index 3 pre-conditioning
• Non-linearly stable time integrator₋ Energy decaying/preserving scheme₋ Zero-work constraints
• Rigid body
• Geometrically exact beam
• Revolute joint
• Flexible joint
• Actuator
Multibody Dynamics Technology
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• Rigid body
• Geometrically exact beam
• Revolute joint
• Flexible joint
• Actuator
ANBA (Anisotropic Beam Analysis) cross sectional model (Giavotto et al., 1983):• Evaluation of cross sectional stiffness (6 by 6 fully populated) • Recovery of sectional stresses and strains
Compute cross sectional stresses and strains
Compute sectional stiffness of equivalent
beam model
Sectional Analysis
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Some Blades Designed with Cp-Max
16 m ▶
45 m ▶
◀ 24 m
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Design Environment
Aero-Structural
Optimization
Structural
Optimization +
Controls
Aerodynamic
Optimization
• Variables: chord, twist and airfoil positioning
• Merit figure: max AEP
• Constraints on max chord, tip speed, geometry
• Variables: blade components thickness, tower structure
• Merit figure: min ICC
• Load freezing for reduced computational time and handling of solution space roughness
• Multi-level coarse-fine iterations
• Variables: rotor diameter, hub height, nacelle uptilt, rotor cone, blade aero-structure
• Merit figure: min CoE
• Complexity/cost trade-offs
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Cp-Max
Aero-Structural
Optimization
Structural
Optimization +
Controls
Aerodynamic
Optimization
• Variables: chord, twist and airfoil positioning
• Merit figure: max AEP
• Constraints on max chord, tip speed, geometry
• Variables: blade components thickness, tower structure
• Merit figure: min ICC
• Load freezing for reduced computational time and handling of solution space roughness
• Multi-level coarse-fine iterations
• Variables: rotor diameter, hub height, nacelle uptilt, rotor cone, blade aero-structure
• Merit figure: min CoE
• Complexity/cost trade-offs
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“Fin
e”
level: 3
D F
EM
“Coars
e”
level: 2
D F
EM
secti
on &
beam
mod
els
Update complete HAWT Cp-Lambda multibody model- DLCs simulation- Campbell diagram- AEP
DLC post-processing: load envelope, DELs, Markov, max tip deflection
Blade: - Geometrically exact beam model- Span-wise interpolation
Blade: - ANBA 2D FEM sectional analysis- Computation of 6x6 stiffness matrices
Blade: definition of aerodynamic & structural design parameters
Cost function:- Min initial capital cost ICC
Automatic 3D CAD model generation
Automatic 3D FEM meshing
Update of blade mass (cost)
Analyses:- Max tip deflection- Max stress/strain- Fatigue- Buckling
Verification of design constraints
Constr
ain
t/m
odel up
date
heuri
sti
c (to
rep
air
constr
ain
t vio
lati
ons)
When SQP converged
Tower: definition of structural design parameters
Tower: - Geom. exact beam model- Height-wise interpolation
Tower:- Computation of stiffness matrix
Constraints:- Max tip deflection- Natural frequencies- Max stresses and strains- Fatigue (ANBA)- Tower buckling- Manufacturing constraints
SQP optimizer
min ICC subject to constraints
Automatic 3D FEM meshing Root detailed analysis:Geometry parameterization
Sizing of bolted joint and blade root laminate
- Bolt preload calculation- Max stress/strain- Fatigue
Root analysis
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The Importance of Multi-Level Blade Design
Stress/strain/fatigue/frequency/max TD:- Constraints not satisfied at first
iteration on 3D FEM model- Modify constraints based on 3D
FEM analysis- Converged at 2nd iteration
Fatigue damage constraint satisfied
Buckling:- Buckling constraint not satisfied at first iteration- Update skin core thickness- Update trailing edge reinforcement strip - Converged at 2nd iteration
Peak stress on initial model
Increased trailing edge strip
ITERATION 1
ITERATION 0
ITERATION 1
ITERATION 0
ITERATION 1
ITERATION 0
ITERATION 1
ITERATION 0
No
rmalized s
tress
Fati
gu
e d
am
ag
e in
dex
Th
ickness
Tra
ilin
g e
dg
e s
trip
th
ickness
Increased skin core thickness
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Cp-Max
Aero-Structural
Optimization
Structural
Optimization +
Controls
Aerodynamic
Optimization
• Variables: chord, twist and airfoil positioning
• Merit figure: max AEP
• Constraints on max chord, tip speed, geometry
• Variables: blade components thickness, tower structure
• Merit figure: min ICC
• Load freezing for reduced computational time and handling of solution space roughness
• Multi-level coarse-fine iterations
• Variables: rotor diameter, hub height, nacelle uptilt, rotor cone, blade aero-structure
• Merit figure: min CoE
• Complexity/cost trade-offs
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Integrated Preliminary-Detailed Design
Preliminary design:
- Overall size (rotor radius, hub height)
- Other macro parameters (uptilt, cone-prebend)
Detailed design:
- Aerodynamic shape
- Structural sizing
- Tower (diameters, thicknesses)
- Systems and components
Strong couplings:
Combined preliminary-detailed design (Wind Energy Science, Bortolotti et al. 2016)
𝐻
𝑅
𝜑
𝛾
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Definition of global parameters:
- Rotor radius R- Hub height H- Cone angle ϒ- Uptilt angle φ- Solidity σc,t
- Tapering τc,t
- Pitch offset δ
Static and turbulent AEPwithaeroelasticeffects
Cost function:Min cost of energy CoE
Constraints:- Ultimate & fatigue loads- Manufacturing constraints
SQP optimizer
min CoE subject to constraints
CoE models
NREL
INNWIND(offshore)
SANDIA(blade cost)
Blade: - Geom. exact beam model- Span-wise interpolation
Blade:- ANBA 2D FEM sectional analysis- Compute 6x6 stiffness matrices
Blade: definition of structural design parameters
Tower: - Geom. exact beam model- Height-wise interpolation
Tower:Compute stiffness matrices
Tower: definition of structural design parameters
CompleteCp-Lambda multibody model
Blade: definition of aero designparameters Cost function:
- Max AEP
Constraints:- Max chord- Max tip speed- σ / τ - Blade geom.- ...
SQP optimizer
max AEP subject to constraints
Parametrization:- Chord- Twist- Thickness
Aerodynamic optimization
“Fin
e”
level: 3
D F
EM
“Coars
e”
level: 2
D F
EM
secti
on &
beam
mod
elsStructural
optimizationBlade: - ANBA 2D FEM sectional analysis- 6x6 stiffness matrices
Blade: definition of aero & structural design parameters
Tower: definition of structural design parameters
Tower:- Computation of stiffness matrix
Update complete HAWTCp-Lambda multibody model- DLCs simulation- Campbell diagram- AEP
DLC post-processing: load envelope, DELs, Markov, max tip deflection
Blade: - Geom. exact beam model- Span-wise interpolation
Tower: - Geom. exact beam model- Height-wise interp.
Automatic 3D FEM shell element meshing
Load application and FE solver
Post processing:- Max tip deflection- Max stress/strain- Fatigue- BucklingVerification of design constraints
Automatic 3D FEM meshing
Root detailed analysis:geometry parameterization
Sizing of bolted joint and blade root laminate- Bolt preload calculation- Max stress/strain- Fatigue
Cost function:- Min ICC
Constraints:- Max tip deflection- Natural frequencies- Max stress and strain- Fatigue- Tower buckling- Manufacturing constr.
SQP optimizer
min ICC subject to constraints
Constr
ain
t/m
od
el
up
date
heuri
sti
c (
to r
ep
air
constr
ain
t vio
lati
ons)
R
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Applications
10 MW – 1A INNWIND Cp-Max Opt Difference
P rated 10 MW 10 MW --
Rotor Diameter 178.3 m 223.2 m + 25.2 %
Hub Height 119.0 m 138.3 m + 16.2 %
Rotor Cone 4.65 deg 5.51 deg + 18.5 %
Nacelle Uptilt 5.00 deg 5.25 deg + 5.0 %
Rotor Solidity 4.66 % 4.08 % - 12.3 %
Blade Tapering 0.43 0.40 - 7.0 %
Blade Mass 42.5 ton 75.6 ton + 77.9 %
Blade Cost 316 k$ 544 k$ + 72.2 %
Tower Mass 597 ton 886 ton + 43.6 %
Tower Cost 2.0 M€ 2.94 M€ +44.1 %
AEP 48.8 GWh 57.2 GWh +17.2 %
TCC 9.1 M€ 12.2 M€ +34.2 %
ICC 30.0 M€ 34.3 M€ +14.3 %
Cost of Energy 70.73 €/MWh 65.79 €/MWh - 7.0 %
INNWIND 10 MW HAWT (class 1A, D=178.3, H=119m)
Baseline design by INNWIND consortium
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IEA Task 37International Energy Agency (IAE) Wind Agreement:
Founded in 1977, it sponsors the cooperation in the research, development, and deployment of wind energy systems
Task 37:
Wind Energy Systems Engineering: Integrated research, design and development (RD&D)
Work Packages
• WP0: Management and Coordination
• WP1: Guidelines for a common framework for integrated RD&D at different fidelity levels (both turbines and plants)
• WP2: Reference wind energy systems (both turbines and plants)
- 3.4 MW onshore wind turbine
- 10 MW offshore wind turbine
• WP3: Benchmarking MDAO activities at different system levels (both turbines and plants)
Link: http://www.ieawind.org/
Contacts:
K. Dykes, NREL, USA, P. E. Rethore and F. Zahle, DTU Wind Energy, Risø, Denmark
K. Merz, SINTEF Energy Research, Norway
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Applications: Passive Load AlleviationOptimal blade design with Bend-Twist Coupling (BTC) by fiber rotation
Note: all designs satisfy exactly the same requirements
Assume fiber angle as design variable in skin and spar caps
Spar-caps: steep increase
Skin: milder increase
Design trade-offs
+ Decreased load envelope and fatigue+ Decreased actuator duty cycle
+ Decreased weightBut same power
Spar-cap/skin synergy
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Integrated Passive and Active Load Alleviation
Active load alleviation: Individual Blade pitch Control (IBC) Significant life-time improvement,
but large duty cycle increase
Integrated Passive-Active load alleviation: IBC+BTC
Decreased pitch activity for BTC blade
IBC+BTCLifetime ADC: +5% wrt baselineLifetime DEL: circa BTC + IPC effects
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Applications: Passive Load Alleviation
Optimal blade design with Bend-Twist Coupling (BTC) by spar cap offset
Coupling coefficient 𝜶 =𝑲𝒇𝒍𝒂𝒑−𝒆𝒅𝒈𝒆𝟐
𝑲𝒇𝒍𝒂𝒑𝑲𝒆𝒅𝒈𝒆
Note: all designs satisfy exactly the same requirements
Flap up –> bend edgewise back (sweep)
Optimal offset: 20 cm
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Applications: Passive Load Alleviation
Optimal combination of spar fiber rotation and offset
Note: all designs satisfy exactly the same requirements
Optimal combination: offset 20 cm + angle 5 deg
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Optimal combination of spar fiber rotation and offset
Rotor resizing:
◀ Significant benefits
Applications: Passive Load Alleviation
Optimum: R+5%(similar hub loads as baseline)
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Composite Optimization
Automatic selection of composite laminates along the blade for the different structural components (in collaboration with Owens Corning)
Material catalogue: Multi-parametric composite material model(e.g. fiber fraction, technological parameter, etc.)
Application
INNWIND 10 MW wind turbine, equipped with E-GFRP
Costs estimated from SANDIA model
Blade cost breakdown
Blade materials cost breakdown
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Composite Optimization
Redesign of the spar caps laminate
Redesign of the shell skin laminate
The optimum laminate is between H-GFRP and CFRP
The optimum laminate is between Bx-GFRPand Tx-GFRP
Combined optimum: Blade mass -9.3%, blade cost -2.9%
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In
te
g
ra
te
d
a
p
p
ro
a
c
h
fo
r a
e
ro
-stru
c
tu
ra
l o
p
tim
iza
tio
n
o
f
W
T
B
la
d
e
s
POLITECNICO di MILANO POLI-Wind Research Lab
Case Study Results: Optimal blade 3D
Three-dimensional view with detail of thick trailing edge and flatback airfoils.
Free-Form 3D Aero-Structural Optimization
Design airfoils together with blade:
• Bezier airfoil parameterization
• Airfoil aerodynamics by Xfoil + Viterna extrapolation
Additional constraints:
• CL max (margin to stall), geometry
Automatic appearance of flatback airfoil!
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Some ReferencesP. Bortolotti, A. Croce, and C.L. Bottasso: Combined preliminary–detailed design of wind turbines. Wind Energ. Sci., 1, 1–18, 2016, doi:10.5194/wes-1-1-2016
C.L. Bottasso, P. Bortolotti, A. Croce, and F. Gualdoni: Integrated Aero-Structural Optimization of Wind Turbine Rotors. Multibody Syst. Dyn., doi: 10.1007/s11044-015-9488-1
C.L. Bottasso, F. Campagnolo, A. Croce, S. Dilli, F. Gualdoni, M.B. Nielsen: Structural Optimization of Wind Turbine Rotor Blades by Multi-Level Sectional/Multibody/3DFEM Analysis, Multibody System Dynamics, 32:87-116, 2014
C.L. Bottasso, F. Campagnolo, C. Tibaldi: Optimization-Based Study of Bend-Twist Coupled Rotor Blades for Passive and Integrated Passive/Active Load Alleviation, Wind Energy, 16:1149-1166, 2013
C.L. Bottasso, A. Croce, F. Campagnolo: Multi-Disciplinary Constrained Optimization of Wind Turbines, Multibody System Dynamics, 27:21-53, 2012
O.A. Bauchau, A. Epple, C.L. Bottasso: Scaling of Constraints and Augmented Lagrangian Formulations in Multibody Dynamics Simulations, ASME Journal of Computational and Nonlinear Dynamics, 4:021007, 2009
• P. Bortolotti, G. Adolphs, C.L. Bottasso: A methodology to guide the selection of composite materials in a windturbine rotor blade design process
• A. Croce, L. Sartori, M.S. Lunghini, L. Clozza, P. Bortolotti, C.L. Bottasso: Lightweight rotor design by optimalspar cap offset
• L. Sartori, P. Bortolotti, A. Croce, and C.L. Bottasso: Integration of prebend optimization in a holistic windturbine design tool
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Conclusions
• Strong couplings between aero and structural design variables
• Multi-level approach to marry high fidelity and computational effort
• Integrated design optimization allows for fast exploration of design space, leading to potential significant CoE improvements
Open issues/outlook:• CoE: solutions are highly sensitive to cost model, need detailed
reliable models that truly account for all significant effects, problem partially alleviated by Pareto solutions (in progress)
• Uncertainties everywhere (aero, structure, wind, …), move away from deterministic design (but what about certification standards?), currently working on UQ and robust design P
DF
Input
PD
F
Output
Simulation
model
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Acknowledgements
Work in collaboration with:
• Pietro Bortolotti (TUM)
• Alessandro Croce, Luca Sartori (Politecnico di Milano)
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Email: info@torque2016.org
Web: www.torque2016.org
TORQUE 2016Munich, Germany, 5-7 October 2016
The Science of Making Torque from Wind
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