Computational Modelling of Unsteady Rotor Effects Duncan McNae – PhD c in addition to idate P

Computational Modelling of Unsteady Rotor Effects Duncan McNae – PhD c in addition to idate P www.phwiki.com

Computational Modelling of Unsteady Rotor Effects Duncan McNae – PhD c in addition to idate P

Stenson, Jacqueline, Contributing Editor has reference to this Academic Journal, PHwiki organized this Journal Computational Modelling of Unsteady Rotor Effects Duncan McNae – PhD c in addition to idate Professor J Michael R Graham Summary Background Numerical Model Results Ongoing Work Summary Background Numerical Model Results Ongoing Work

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Background – Blade loads in addition to fatigue SeaGen rotor, Marine Current Turbines Ltd. Fatigue life is a major consideration as long as rotor blade design Flow unsteadiness: – Turbulent flow structures – Waves Background – Unsteady Flow Effects Key principle: Dynamic Inflow Fluctuations in flow speed cause changes in the loading on the rotor, in addition to there as long as e the strength of vorticity trailing into the wake is not constant. The induced velocity field takes time to develop as a result. Burton et al Burton et al. 2001 Summary Background Numerical Model Results Ongoing Work

Numerical Model Numerical modelling techniques: Blade Element Momentum Theory (BEM) Potential Flow / Vortex Methods Computational Fluid Dynamics (CFD) Numerical Model Numerical modelling techniques: Blade Element Momentum Theory (BEM) Potential Flow / Vortex Methods Computational Fluid Dynamics (CFD) Numerical Model – The Vortex Lattice Method The blade–wake system can be represented by a lattice of “vortex rings”, or “panels”. This concept is derived from potential flow theory. Vortex rings are distributed on the blade camber line, in addition to the wake panels are free – they move with the flow. A system of equations is as long as med with the use of a zero-flow-normal boundary condition at the center of each panel – the “collocation points”. Representation of a vortex ring = circulation strength Biot–Savart Law

Numerical Model – The wake At each time step, a row of wake panels is released from the trailing edge of the blade. The circulation strength of each wake panel is determined to be the strength of it’s corresponding panel on the trailing edge of the blade. At each time step, the nodes of the wake lattice move with the local flow velocity, (including the influence of all wake in addition to blade Panels) – this is computationally expensive. Numerical Model – Loads The loading contribution of each panel is calculated using the following: This is a as long as m of the unsteady Kutta-Joukowski equation. Numerical Model – Validation Validation of the unsteady vortex lattice method (VLM): Flat plate steady case Flat plate unsteady Rotor

Numerical Model – Validation For a simple flat plate wing case (AR=8), the VLM has been compared with “Tornado”, which is a similar program that has been developed as long as aircraft design. Numerical Model – Validation Unsteady flat plate oscillations, vs Theodorsens theory: Numerical Model – Coefficient of Power: – Coefficient of Thrust:

Numerical Model – Validation Validation of rotor loads against BEM model Range of tips speed ratios (TSR) Inviscid flat plate approximation as long as BEM coefficients Rotor Blade Properties (3 bladed) Numerical Model – Demonstration Numerical Model – Demonstration

Review Background Numerical Model Results Ongoing Work Numerical Model – Results Example load case: Comparison of a step increase in flow velocity against a step change in pitch angle. The step change in pitch is -2 degrees. The step change in free stream flow velocity is set to match the thrust loading after the transients have diminished. (1.08x increase) The Imperial College turbine blade shape has been used as long as the computational modelling. – Ø 0.4m – 2 Blades – Free stream flow velocity = 1m/s – Tip speed ratio = 5 Numerical Model – Results Axial thrust as long as ce shown vs. time (in rotor rotations) as long as the two cases: The simulations are first started impulsively, in addition to allowed to reach a steady condition be as long as e the changes are applied.

Numerical Model – Results With the reverse case: Pitch change: +2 degrees Flow change: 0.91 Numerical Model – Results Induced velocity at the tip ( = 0.95) Numerical Model – Results Induced velocity, thrust in addition to angle of incidence at three radial sections:

Stenson, Jacqueline MSNBC.com Contributing Editor www.phwiki.com

Numerical Model – Results Numerical Model – Results Numerical Model – Results

Numerical Model – Results Matching induced velocity in the tip region: Free stream velocity after change = 1.2 Numerical Model – Results Higher tip speed ratio example (TSR = 7) Flow speed after change = 1.12 m/s Numerical Model – Results Higher Tip Speed Ratio – Induced velocities

Numerical Model – Results Flexible blade

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