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Multirotor configurations introduce complicated aerodynamic and aeroacoustic interactions that must be considered during aircraft design. In this paper we explore two numerical methods to model the acoustic noise caused by aerodynamic rotor-on-rotor interactions of rotors in hover. The first method uses a conventional mesh-based unsteady Reynolds-average Navier-Stokes (URANS) solver, while the second consists of a meshless Lagrangian solver based on the viscous vortex particle method (VPM). Both methods are coupled with an aeroacoustics solver for tonal and broadband noise predictions. Noise predictions are validated for single and multi-rotor configurations, obtaining with the VPM a similar accuracy than URANS while being two orders of magnitude faster. We characterize the interactions of two side-by-side rotors in hover as the tip-to-tip distance and downstream spacing are varied. At an observer located six diameters away, multirotor noise is the strongest above and below the rotors, increasing by about 10 dBA directly underneath as the rotors are brought closer together. The interactions show no sensitivity to blade loading distribution, indicating that multirotor interactions are not alleviated with a lighter tip loading. We found that noise can be mitigated by spacing the rotors in the downstream direction—with the optimal spacing being about half a diameter—achieving a noise decrease of about 4 dBA without any aerodynamic penalties.
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Wind Speed Statistics from a Small UAS and Its Sensitivity to Sensor Location
With the increase in the use of small uncrewed aircraft systems (UAS) there is a growing need for real-time weather forecasting to improve the safety of low-altitude aircraft operations. This will require integration of measurements with autonomous systems since current available sampling lack sufficient resolution within the atmospheric boundary layer (ABL). Thus, the current work aims to assess the ability to measure wind speeds from a quad-copter UAS and compare the performance with that of a fixed mast. Two laboratory tests were initially performed to assess the spatial variation in the vertically induced flow from the rotors. The horizontal distribution above the rotors was examined in a water tunnel at speeds and rotation rates to simulate nominally full throttle with a relative air speed of 0 or 8 m/s. These results showed that the sensor should be placed between rotor pairs. The vertical distribution was examined from a single rotor test in a large chamber, which suggested that at full throttle the sensor should be about 400 mm above the rotor plane. Field testing was then performed with the sensor positioned in between both pairs of rotors at 406, 508, and 610 mm above the rotor plane. The mean velocity over the given period was within 5.5% of the that measured from a fixed mast over the same period. The variation between the UAS and mast sensors were better correlated with the local mean shear than separation distance, which suggests height mismatch could be the source of error. The fluctuating velocity was quantified with the comparison of higher order statistics as well as the power spectral density, which the mast and UAS spectra were in good agreement regardless of the separation distance. This implies that for the current configuration a separation distance of 5.3 rotor diameters was sufficient to minimize the influence of the rotors.
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- Award ID(s):
- 1925147
- PAR ID:
- 10384536
- Date Published:
- Journal Name:
- Atmosphere
- Volume:
- 13
- Issue:
- 3
- ISSN:
- 2073-4433
- Page Range / eLocation ID:
- 443
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Multirotor configurations introduce complicated aerodynamic and aeroacoustic interactions that must be considered during aircraft design. In this paper we explore two numerical methods to model the acoustic noise caused by aerodynamic rotor-on-rotor interactions of rotors in hover. The first method uses a conventional mesh-based unsteady Reynolds-average Navier-Stokes (URANS) solver, while the second consists of a meshless Lagrangian solver based on the viscous vortex particle method (VPM). Both methods are coupled with an aeroacoustics solver for tonal and broadband noise predictions. Noise predictions are validated for single and multi-rotor configurations, obtaining with the VPM a similar accuracy than URANS while being two orders of magnitude faster. We characterize the interactions of two side-by-side rotors in hover as the tip-to-tip distance and downstream spacing are varied. At an observer located six diameters away, multirotor noise is the strongest above and below the rotors, increasing by about 10 dBA directly underneath as the rotors are brought closer together. The interactions show no sensitivity to blade loading distribution, indicating that multirotor interactions are not alleviated with a lighter tip loading. We found that noise can be mitigated by spacing the rotors in the downstream direction—with the optimal spacing being about half a diameter—achieving a noise decrease of about 4 dBA without any aerodynamic penalties.more » « less
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Abstract Flow modifications induced by wind turbine rotors on the incoming atmospheric boundary layer (ABL), such as blockage and speedups, can be important factors affecting the power performance and annual energy production (AEP) of a wind farm. Further, these rotor‐induced effects on the incoming ABL can vary significantly with the characteristics of the incoming wind, such as wind shear, veer, and turbulence intensity, and turbine operative conditions. To better characterize the complex flow physics underpinning the interaction between turbine rotors and the ABL, a field campaign was performed by deploying profiling wind LiDARs both before and after the construction of an onshore wind turbine array. Considering that the magnitude of these rotor‐induced flow modifications represents a small percentage of the incoming wind speed ( ), high accuracy needs to be achieved for the analysis of the experimental data and generation of flow predictions. Further, flow distortions induced by the site topography and effects of the local climatology need to be quantified and differentiated from those induced by wind turbine rotors. To this aim, a suite of statistical and machine learning models, such as k‐means cluster analysis coupled with random forest predictions, are used to quantify and predict flow modifications for different wind and atmospheric conditions. The experimental results show that wind velocity reductions of up to 3% can be observed at an upstream distance of 1.5 rotor diameter from the leading wind turbine rotor, with more significant effects occurring for larger positive wind shear. For more complex wind conditions, such as negative shear and low‐level jet, the rotor induction becomes highly complex entailing either velocity reductions (down to 9%) below hub height and velocity increases (up to 3%) above hub height. The effects of the rotor induction on the incoming wind velocity field seem to be already roughly negligible at an upstream distance of three rotor diameters. The results from this field experiment will inform models to simulate wind‐turbine and wind‐farm operations with improved accuracy for flow predictions in the proximity of the rotor area, which will be instrumental for more accurate quantification of wind farm blockage and relative effects on AEP.more » « less
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Abstract A field experiment was conducted to investigate the effects of the thrust force induced by utility-scale wind turbines on the incoming wind field. Five wind profiling LiDARs and a scanning Doppler pulsed wind LiDAR were deployed in the proximity of a row of four wind turbines located over relatively flat terrain, both before and after the construction of the wind farm. The analysis of the LiDAR data collected during the pre-construction phase enables quantifying the wind map of the site, which is then leveraged to correct the post-construction LiDAR data and isolate rotor-induced effects on the incoming wind field. The analysis of the profiling LiDAR data allows for the identification of the induction zone upstream of the turbine rotors, with an increasing velocity deficit moving from the top tip towards the bottom tip of the rotor. The largest wind speed reduction (about 5%) is observed for convective conditions and incoming hub-height wind speed between cut-in and rated wind speeds. The scanning LiDAR data indicate the presence of speedup regions within the gaps between adjacent turbine rotors. Speedup increases with reducing the transverse distance between the rotors, atmospheric instability (maximum 15%), while a longer streamwise extent of the speedup region is observed under stable atmospheric conditions.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/atmos13030443
