Improvements to the Actuator Line Modeling for Wind Turbines

Mittal, Anshul; Sreenivas, Kidambi; Taylor, Lafayette K.; Hereth, Levi

doi:10.2514/6.2015-0216

Cited by 13 publications

(18 citation statements)

References 8 publications

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“…This method has similarities to that proposed by Mittal et al, 19 but its mathematical foundation and integration using g(x, y) as the weighting function is unique.…”

Section: Iib2 Aal Integral Velocity Samplingmentioning

confidence: 94%

“…This method breaks down for line force projection functions in which there is no clear center of the bound vorticity. It is true that the velocity sampling location could be moved ahead of the actuator line and some researchers have tried that, including Mittal et al 19 Additionally, Shen et al 26 address the problem of how to determine angle of attack for a wind turbine blade, and their work is not specific to actuator line modeling. However, the predicted freestream velocity is sensitive to the sampling location, and that location becomes a tunable parameter, which is not desirable.…”

Section: Iib1 Al Pointwise Velocity Samplingmentioning

confidence: 99%

“…However, if a more elaborate line-force projection function is used, sampling along the actuator line likely no longer avoids the blade-local flow effects. Others, such as Mittal et al, 19 have experimented with sampling some distance upstream of the actuator line in an attempt to avoid sampling blade-local flow effects, but the solution is sensitive to the sampling location, which can be seen as a tunable parameter, and there is no general consensus on the proper sampling location. Also, upstream sampling in turbulent flow means the blade forces will react to turbulent structures before the actuator line actually encounters them.…”

Section: Introductionmentioning

confidence: 99%

“…Also, upstream sampling in turbulent flow means the blade forces will react to turbulent structures before the actuator line actually encounters them. Mittal et al 19 also tried sampling at multiple locations to obtain an average velocity.…”

Section: Introductionmentioning

confidence: 99%

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An Advanced Actuator Line Method for Wind Energy Applications and Beyond

Churchfield

Schreck

Martínez‐Tossas

et al. 2017

35th Wind Energy Symposium

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The actuator line method to represent rotor aerodynamics within computational fluid dynamics has been in use for more than a decade. This method applies a body force to the flow field along rotating lines corresponding to the individual rotor blades and employs tabular airfoil data to compute the force distribution. The actuator line method is attractive because, compared to blade-resolved simulations, the required mesh is much simpler and the computational cost is lower. This work proposes a higher fidelity variant of the actuator line method meant to fill the space between current actuator line and blade-resolved simulations. It contains modifications in two key areas. The first is that of freestream velocity vector estimation along the line, which is necessary to compute the lift and drag along the line using tabular airfoil data. Most current methods rely on point sampling in which the location of sampling is ambiguous. Here we test a velocity sampling method that uses a properly weighted integral over space, removing this ambiguity. The second area of improvement is the function used to project the one-dimensional actuator line force onto the three-dimensional fluid mesh as a body force. We propose and test a projection function that spreads the force over a region that looks something like a real blade with the hope that it will produce the blade local and near wake flow features with more accuracy and higher fidelity. Our goal is that with these two improvements, not only will the flow field predictions be enhanced, but also the spanwise loading will be made more accurate. We refer to this combination of improvements as the advanced actuator line method. We apply these improvements to two different wind turbine cases. Although there is a strong wind energy motivation in our work, these advanced actuator line ideas can also be used in other applications, such as helicopter rotors.

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“…This method has similarities to that proposed by Mittal et al, 19 but its mathematical foundation and integration using g(x, y) as the weighting function is unique.…”

Section: Iib2 Aal Integral Velocity Samplingmentioning

confidence: 94%

Section: Iib1 Al Pointwise Velocity Samplingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Advanced Actuator Line Method for Wind Energy Applications and Beyond

Churchfield

Schreck

Martínez‐Tossas

et al. 2017

35th Wind Energy Symposium

View full text Add to dashboard Cite

show abstract

“…However, in most cases, the velocity exactly at the center of the ALM kernel is not available, and thus, it must be obtained by the neighboring available discrete values. Different possibilities exist and have been used in the literature, such as averaging the velocity sampled at multiple points or averaging the velocity in space using the spreading kernel as a weight or other possible methods . Some of the existing approaches have been compared by Merabet and Laurendeau in their study, focusing on their accuracy in giving the actual inflow velocity and on how it is affected by some simulation parameters, such as the grid resolution or the employed solver.…”

Section: Introductionmentioning

confidence: 99%

Appraisal and calibration of the actuator line model for the prediction of turbulent separated wakes

et al. 2020

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The aim of this study is to further investigate the accuracy and the reliability of the actuator line model (ALM) predictions for turbulent separated wakes. Large eddy simulations (LES) of the flow around a NACA0009 airfoil are performed mimicking the geometry with the immersed boundary method. Results are validated against experiments and used to assess the accuracy of the ALM predictions for the same airfoil, with different values of the spreading parameter and of the reference velocity and for two values of the angle of attack. It is found that the ALM setup recently derived from linearized inviscid analysis leads to accurate results for the lower angle of attack, while at the higher one for which a significant separation of the boundary layer occurs, the ALM requires a different set of model parameters. This calls for a systematic investigation of the sensitivity to the ALM parameters for separated flows, which is carried out herein through a stochastic approach allowing continuous response surfaces to be obtained in the parameter space. The ALM parameters are calibrated against the results obtained with the immersed boundaries. With the calibrated model parameters, the ALM gives good predictions of the velocity and turbulent kinetic energy in the far wake. Finally, the proposed model parameters are used to predict the flow past a different geometry, a flat plate, at high angle of attack.The accuracy of the prediction of the far wake is again good, showing the robustness of the identified setup. KEYWORDS actuator line model, generalized Polynomial Chaos expansion, stochastic sensitivity analysis, turbulent wake 1In the actuator line model (ALM), the force is distributed in a small region centered into the line representing the blade position. The spreading kernel is typically a Gaussian function of the distance from the actuator line position. The standard deviation of the Gaussian kernel, , determines the width of the spreading. The ALM is known to represent more accurately the wake flow features than similar models, like the actuator disk or the rotating actuator disk, which have lower computational cost. [3][4][5] However, the flow obtained with the ALM strongly depends on the spreading parameter ( ). There are no definitive guidelines to set this input parameter. For numerical stability, it is suggested that the spreading parameter be at least twice the grid spacing, in order to avoid singularities due to a pointwise force. 6 This was confirmed by Martínez et al. 3 who investigated the sensitivity to the spreading to grid-spacing ratio as well as to the grid resolution for a fixed spreading value. Shives and Crawford suggested 7 that the spreading parameter should be related to the local chord length ( ∕c ≃ 1∕8-1∕4) and thus vary along the radial direction for a common wind turbine blade geometry. An analogous approach was also pursued by Jha et al. 8 and Jha and Schmitz 9 defining an equivalent elliptic blade planform.Recently, Martìnez et al 10 carried out analytical computations using the linearized Eu...

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An actuator‐line model with Lagrangian‐averaged velocity sampling and piecewise projection for wind turbine simulations

Xie

2021

Wind Energy

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A new approach is proposed to do the velocity sampling for actuator‐line models (ALM). Unlike the conventional spatial averaging approaches, the velocity sampling is performed in a Lagrangian averaging way along flow paths with a time scale depending on the local flow patterns. The new approach is evaluated by large‐eddy simulations of a utility‐scale National Renewable Energy Laboratory (NREL)‐5MW wind turbine. The results show that the Lagrangian approach of velocity sampling is effective to reduce the spurious numerical oscillations in the modeling results. The good match with the benchmark data indicates that correct free upwind velocity can be obtained with a careful determination of the associated time scale. Also, a piecewise function is proposed to replace the Gaussian function for the force projection process.

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Improvements to the Actuator Line Modeling for Wind Turbines

Cited by 13 publications

References 8 publications

An Advanced Actuator Line Method for Wind Energy Applications and Beyond

An Advanced Actuator Line Method for Wind Energy Applications and Beyond

Appraisal and calibration of the actuator line model for the prediction of turbulent separated wakes

An actuator‐line model with Lagrangian‐averaged velocity sampling and piecewise projection for wind turbine simulations

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