Blade modelling, lifetime assessment, and health monitoring
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1 Blade modelling, lifetime assessment, and health monitoring Dr Geoff Dutton Energy Research Unit (ERU) Rutherford Appleton Laboratory (RAL) Science and Technology Facilities Council (STFC) With acknowledgements to: Matt Clarke 1, Paul Bonnet 2 (now at 1 Oxford Brookes University and 2 SAMTECH Iberica) Presented at: Wind Energy challenges for materials, mechanics and surface science Institute of Physics, London, 28 October 2010
2 Background: Blade modelling Introduction Parametric blade model Exemplar (5 MW) blade Static and fatigue strength Thermoelastic stress analysis (Condition monitoring) Picture credit: LM Glasfiber Picture credit: EWEA
3 Background: Blade modelling What would be the effect of innovative materials? What additional stresses do smart control devices generate in a blade? How should NDT measurements be interpreted? Picture credit: LM Glasfiber Picture credit: EWEA
4 Blade design / blade testing DESIGN OBJECTIVES: Maximise energy yield Limit maximum power output Maximise material static and fatigue strength High blade stiffness Minimise overall rotor mass Avoid potential resonance conditions Lightning protection Radar interaction DESIGN STANDARDS: ISO Certification bodies: GL, DNV Smart control devices Condition monitoring PARAMETRIC BLADE MODEL Blade load cases (multi-axial) Partial safety factors: Loads Materials Consequence of failure Exact fibre lay-up Manufacturing process Materials data (uni-axial) Component design/testing Adhesives Composite of composites Full scale blade design & certification test:
5 Wind turbine blade structure and testing Flanges, web, bondlines Repair Sandwich Blade root Spar end detail Figure after Denja Lekou, CRES, Greece
6 Parametric blade model: Design strategy Parametric processing tool for creation and running of the underlying FE model Suitable for sensitivity analyses, flexibility, documenting, re-usability Python script front end for automation of the Abaqus FE package Modular program Realistic load application, including quasi-static aerodynamic loading Ultimate strength & fatigue analysis Developing dynamic implementation
7 Parametric blade model: Geometry definition a b => parameter sweeps: e.g. tip deflection or max stress c d aerofoil shape d - shear web offset (mm)
8 Parametric blade model: Geometry definition
9 Parametric blade model: Lay-up
10 Parametric blade model: Fully distrubuted aerodynamic load
11 Parametric blade model: Variable mesh density at the push of a button
12 Parametric blade model
13 5 MW (61 m) blade model Basic lay-up information Target mass and stiffness distributions Limitations of lay-up information Overall mass Discretisation of lay-up info Required spar-cap stress profile? Lay-up modification Materials variation Static load case (aerodynamic load distribution) Fatigue lifetime
14 5 MW (61 m) blade model: Spar-cap stress distribution (smoothed)
15 Example application collective v. cyclic pitch control 3º cyclic: maximum flap load reduced by 8.4% while edge load is relatively unchanged (WARNING: quasi-static)
16 5 MW (61 m) blade model: Materials Material property Baseline UD material High fatigue strength material E 1T (GPa) E 1C (GPa) ν E 2T (GPa) E 2C (GPa) ν E E-01 G 12 (MPa) Material property Baseline UD material High fatigue strength material X T (MPa) X C (MPa) Y T (MPa) Y C (MPa) S (MPa) Fatigue Baseline UD High fatigue strength S-n curve at 1 S 0 = 1176 S 0 = 1250 R=0.1 b σ max = S0 N b = 9.74 b = 10.59
17 5 MW (61 m) blade model: Static strength skins and shear web Choice of static failure criteria: Tsai-Wu Tsai-Hill Other (user specified)
18 5 MW (61 m) blade model: Static strength skins and shear web Choice of static failure criteria: Tsai-Wu Tsai-Hill Other (user specified)
19 5 MW (61 m) blade model: Static strength bonding paste Cohesive element model Normal stress component Shear stress component Linear up to characteristic value Material softening
20 5 MW (61 m) blade model: Fatigue strength estimation Complex loading Stochastic / semi-deterministic (cyclic) loading Biaxial (triaxial) stress state Fatigue characterisation Predominantly uni-directional materials data Uncertainty in how best to combine different stress cycles R-ratio (minimum:maximum stress in a load cycle) Combine into constant life diagram IEC
21 5 MW (61 m) blade model: Fatigue strength estimation Data: Optimat Blades
22 5 MW (61 m) blade model: Fatigue strength estimation Complex loading Stochastic / semi-deterministic (cyclic) loading Biaxial (triaxial) stress state Fatigue characterisation Predominantly uni-directional materials data Uncertainty in how best to combine different stress cycles R-ratio (minimum:maximum stress in a load cycle) Combine into constant life diagram applies to a single material direction How to deal with complex stress states? IEC Biaxial stress ratio
23 5 MW (61 m) blade model: Biaxial stress ratio Biaxial stress ratio is the ratio between the two largest magnitude principal stress components
24 5 MW (61 m) blade model: Fatigue strength estimation
25 5 MW (61 m) blade model: Fatigue lifetime Min: 1.3 x 10 9 Min: 1.6 x S = n S = n Baseline glass fibre Uniaxial fatigue High performance glass fibre
26 Full scale blade testing Thermoelastic stress analysis Blade test: blade with defects Isotropic materials: T = T ρc p α ( + ) σ 11 σ 22 Orthotropic materials: T = ( α σ + α ) T ρ c p σ 22
27 Full scale blade testing Thermoelastic stress analysis Blade test: blade with defects Blade model: normal blade Blade model: blade with defects
28 SUPERGEN Wind 1 - Achievements Flexible, parametric blade model for assessment of alternative materials Simple failure model in blade skin and developing damage model in bonding paste implemented Fatigue methodology under development Initial results also available for application to full-scale blade testing, control of smart blades and interpretation of condition monitoring data Supergen Wind 2 work planned on dynamic loading operation in wakes from upstream turbines & smart blade devices
29 SUPERGEN Wind 2 + Further develop turbine wake interaction model (IC) Develop three-blade reduced degree of freedom rotor FE model to incorporate aeroelastic interaction (RAL) Link to Phase I work using sub-structures Assess new materials & construction techniques Assess control effects of aerodynamic control devices
30 Acknowledgements EPSRC grant no. EP/D034566/1 SUPERGEN Wind Energy Technologies Consortium For further information please contact:
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