The decrease of wind velocity （wake losses） in downstream area of wind turbine is generally quantified using wake models. The overall estimated power of wind farm varies according to reliability of wake model used, ...The decrease of wind velocity （wake losses） in downstream area of wind turbine is generally quantified using wake models. The overall estimated power of wind farm varies according to reliability of wake model used, however it＇s unclear which model is most appropriate and able to give a high performance in predicting wind velocity deficit. In this subject, a qualification of three analytical wake models （Jensen, lshihara and Frandsen） based on three principal criteria is presented in this paper： （i） the parsimony which characterizes the inverse of model complexity, （ii） the accuracy of estimation in which wake model is compared with the experimental data and （iii） imprecision that is related to assumptions and uncertainty on the value of variables considered in each model. This qualitative analysis shows the inability of wake models to predict wind velocity deficit due to the big uncertainty of variables considered and it sensitivity to wind farm characteristic.展开更多
Duo to fluctuations in atmospheric turbulence and yaw control strategies,wind turbines are often in a yaw state.To predict the far wake velocity field of wind turbines quickly and accurately,a wake velocity model was ...Duo to fluctuations in atmospheric turbulence and yaw control strategies,wind turbines are often in a yaw state.To predict the far wake velocity field of wind turbines quickly and accurately,a wake velocity model was derived based on the method of momentum conservation considering the wake steering of the wind turbine under yaw conditions.To consider the shear effect of the vertical incoming wind direction,a two-dimensional Gaussian distribution function was introduced to model the velocity loss at different axial positions in the far wake region based on the assumption of nonlinear wake expansion.This work also developed a“prediction-correction”method to solve the wake velocity field,and the accuracy of the model results was verified in wake experiments on the Garrad Hassan wind turbine.Moreover,a 33-kW two-blade horizontal axis wind turbine was simulated using this method,and the results were compared with the classical wake model under the same parameters and the computational fluid dynamics(CFD)simulation results.The results show that the nonlinear wake model well reflected the influence of incoming flow shear and yaw wake steering in the wake velocity field.Finally,computation of the wake flow for the Horns Rev offshore wind farm with 80 wind turbines showed an error within 8%compared to the experimental values.The established wake model is less computationally intensive than other methods,has a faster calculation speed,and can be used for engineering calculations of the wake velocity in the far wakefield of wind turbines.展开更多
To enhance the prediction accuracy of unsteady wakes behind wind turbines,a novel reduced-order model is proposed by integrating a multifunctional recurrent fuzzy neural network(MFRFNN)and proper orthogonal decom-posi...To enhance the prediction accuracy of unsteady wakes behind wind turbines,a novel reduced-order model is proposed by integrating a multifunctional recurrent fuzzy neural network(MFRFNN)and proper orthogonal decom-position(POD).First,POD is employed to reduce the di-mensionality of the wind field data,extracting spatiotempo-rally correlated modal coefficients and modes.These reduced-order variables can effectively capture the essential features of unsteady wake behaviors.Next,MFRFNN is utilized to predict the time series of modal coefficients.Fi-nally,by combining the predicted modal coefficients with their corresponding modes,a flow field is reconstructed,al-lowing accurate prediction of unsteady wake dynamics.The predicted wake data exhibit high consistency with large eddy simulation results in both the near-and far-wake re-gions and outperform existing data-driven methods.This ap-proach offers significant potential for optimizing wind farm design and provides a new solution for the precise prediction of wind turbine wake behavior.展开更多
With the rapid advancement of machine learning technology and its growing adoption in research and engineering applications,an increasing number of studies have embraced data-driven approaches for modeling wind turbin...With the rapid advancement of machine learning technology and its growing adoption in research and engineering applications,an increasing number of studies have embraced data-driven approaches for modeling wind turbine wakes.These models leverage the ability to capture complex,high-dimensional characteristics of wind turbine wakes while offering significantly greater efficiency in the prediction process than physics-driven models.As a result,data-driven wind turbine wake models are regarded as powerful and effective tools for predicting wake behavior and turbine power output.This paper aims to provide a concise yet comprehensive review of existing studies on wind turbine wake modeling that employ data-driven approaches.It begins by defining and classifying machine learning methods to facilitate a clearer understanding of the reviewed literature.Subsequently,the related studies are categorized into four key areas:wind turbine power prediction,data-driven analytic wake models,wake field reconstruction,and the incorporation of explicit physical constraints.The accuracy of data-driven models is influenced by two primary factors:the quality of the training data and the performance of the model itself.Accordingly,both data accuracy and model structure are discussed in detail within the review.展开更多
A modified wake model was proposed for the newly developed bubble-induced three-phase inverse fluidized bed(BIFB),by combining the generalized wake model and the gas-perturbed liquid model.On the basis of the modified...A modified wake model was proposed for the newly developed bubble-induced three-phase inverse fluidized bed(BIFB),by combining the generalized wake model and the gas-perturbed liquid model.On the basis of the modified wake model,the solids and liquid holdups and the complete fluidization gas velocity in BIFB system have been successfully predicted with two established correlations.The predictions achieved very good agreements with the experimental data.展开更多
The Light Detection and Ranging(LiDAR)data analysis method has emerged as a powerful and versatile tool for characterizing atmospheric conditions and modeling light propagation through various media.In the context of ...The Light Detection and Ranging(LiDAR)data analysis method has emerged as a powerful and versatile tool for characterizing atmospheric conditions and modeling light propagation through various media.In the context of renewable energy,particularly wind energy,LiDAR is increasingly utilized to analyze wind flow,turbine wake effects,and turbulence in complex terrains.This study focuses on advancing LiDAR data interpretation through the development and application of the LiDAR Statistical Barnes Objective Analysis(LiSBOA)method.LiSBOA enhances the capacity of scanning LiDAR systems by enabling more precise optimization of scan configurations and improving the retrieval of wind statistics across Cartesian grids.Unlike conventional approaches,LiSBOA offers fine-grained control over azimuthal resolution and spatial filtering,which allows for the detailed reconstruction of wind fields and turbulence structures.These capabilities are crucial for accurately simulating wind turbine wakes and power capture,particularly in environments with variable atmospheric stability and complex topography.Field deployments and comparative assessments against traditional meteorological mast data demonstrate the effectiveness of LiSBOA.The method reduces wind velocity estimation errors to within 3%and increases the accuracy of turbulence intensity measurements by over 4%.Such improvements are significant for enhancing wind resource assessment,optimizing turbine placement,and refining control strategies for operational turbines.LiSBOA represents a robust advancement in LiDAR data processing for wind energy applications.By addressing limitations in spatial resolution and measurement uncertainty,it supports more reliable modeling of wake interactions and flow variability.This work contributes to improving the efficiency and reliability of wind energy systems through advanced remote sensing and statistical analysis techniques.展开更多
It is well known that the Reynolds number has a significant effect on the vortex-induced vibrations(VIV) of cylinders. In this paper, a novel in-line(IL) and cross-flow(CF) coupling VIV prediction model for circular c...It is well known that the Reynolds number has a significant effect on the vortex-induced vibrations(VIV) of cylinders. In this paper, a novel in-line(IL) and cross-flow(CF) coupling VIV prediction model for circular cylinders has been proposed, in which the influence of the Reynolds number was comprehensively considered. The Strouhal number linked with the vortex shedding frequency was calculated through a function of the Reynolds number. The coefficient of the mean drag force was fitted as a new piecewise function of the Reynolds number, and its amplification resulted from the CF VIV was also taken into account. The oscillating drag and lift forces were modelled with classical van der Pol wake oscillators and their empirical parameters were determined based on the lock-in boundaries and the peak-amplitude formulas. A new peak-amplitude formula for the IL VIV was developed under the resonance condition with respect to the mass-damping ratio and the Reynolds number. When compared with the results from the experiments and some other prediction models, the present model could give good estimations on the vibration amplitudes and frequencies of the VIV both for elastically-mounted rigid and long flexible cylinders. The present model considering the influence of the Reynolds number could generally provide better results than that neglecting the effect of the Reynolds number.展开更多
Presently developed two-phase turbulence models under-predict the gas turbulent fluctuation, because their turbulence modification models cannot fully reflect the effect of particles. In this paper, a two-time-scale d...Presently developed two-phase turbulence models under-predict the gas turbulent fluctuation, because their turbulence modification models cannot fully reflect the effect of particles. In this paper, a two-time-scale dis- sipation model of turbulence modification, developed for the two-phase velocity correlation and for the dissipation rate of gas turbulent kinetic energy, is proposed and used to simulate sudden-expansion and swirling gas-particle flows. The proposed two-time scale model gives better results than the single-time scale model. Besides, a gas tur- bulence augmentation model accounting for the finite-size particle wake effect in the gas Reynolds stress equation is proposed. The proposed turbulence modification models are used to simulate two-phase pipe flows. It can prop- erly predict both turbulence reduction and turbulence enhancement for a certain size of particles observed in ex- periments.展开更多
Determination of the aerodynamic configuration of wake is the key to analysis and evaluation of the rotor aerodynamic characteristics of a horizontal-axis wind turbine. According to the aerodynamic configuration, the ...Determination of the aerodynamic configuration of wake is the key to analysis and evaluation of the rotor aerodynamic characteristics of a horizontal-axis wind turbine. According to the aerodynamic configuration, the real magnitude and direction of the onflow velocity at the rotor blade can be determined, and subsequently, the aerodynamic force on the rotor can be determined. The commonly employed wake aerodynamic models are of the cylindrical form instead of the actual expanding one. This is because the influence of the radial component of the induced velocity on the wake configuration is neglected. Therefore, this model should be called a "linear model". Using this model means that the induced velocities at the rotor blades and aerodynamic loads on them would be inexact. An approximately accurate approach is proposed in this paper to determine the so-called "nonlinear" wake aerodynamic configuration by means of the potential theory, where the influence of all three coordinate components of the induced velocity on wake aerodynamic configuration is taken into account to obtain a kind of expanding wake that approximately looks like an actual one. First, the rotor aerodynamic model composed of axial (central), bound, and trailing vortexes is established with the help of the finite aspect wing theory. Then, the Biot-Savart formula for the potential flow theory is used to derive a set of integral equations to evaluate the three components of the induced velocity at any point within the wake. The numerical solution to the integral equations is found, and the loci of all elementary trailing vortex filaments behind the rotor are determined thereafter. Finally, to formulate an actual wind turbine rotor, using the nonlinear wake model, the induced velocity everywhere in the wake, especially that at the rotor blade, is obtained in the case of various tip speed ratios and compared with the wake boundary in a neutral atmospheric boundary layer. Hereby, some useful and referential conclusions are offered for the aerodynamic computation and design of the rotor of the horizontal-axis wind turbine.展开更多
With the assumption of the Park model that the wake region is in linear expansion and the cross-wind is in multinomial and Gaussian distribution in wake region,one develops the Park-polynomial model and the ParkGaussi...With the assumption of the Park model that the wake region is in linear expansion and the cross-wind is in multinomial and Gaussian distribution in wake region,one develops the Park-polynomial model and the ParkGaussian model to numerically simulate the wake flow field for a single wind turbine.Compared with the measured data of wind farm and the wind tunnel test,it shows that the prediction precision of wake field has been improved obviously under the modified initial wake radius.Moreover,both of the newly modified two models could well simulate the wind velocity in wake region,because the predicted results is approximately consistent with the test result,and the cross-wind distribution conforms to that of the real flow field.The two models have still inherited many advantages of engineering models,such as simple form,easy-to-code,and high computational efficiency.Particularly,the Park-Gaussian model is the best in overall performance among them.展开更多
Wind tunnel measurements using particle image velocimetry have been performed around two perforated discs, with varying streamwise distance, in order to simulate the wake interaction between wind turbines. The static ...Wind tunnel measurements using particle image velocimetry have been performed around two perforated discs, with varying streamwise distance, in order to simulate the wake interaction between wind turbines. The static pressure footprint (p-f) on ground level associated with the wake behind the disc and wake velocity data for both the streamwise and wall-normal velocity components with the corresponding turbulence intensities are reported. The p-f method shows that the size of the wake regions, behind the wind turbine models, initially drop when a second disc is placed just downstream of the first one. From a mutual distance (Δ χ) of about five disc diameters (5D), both wake footprints increase as the mutual distance is increased, and for very large mutual distances, approximately Δ χ/ D > 15, the footprint of the downstream disc has recovered and is about the same as for a single disc. At last we conclude that despite very different inlet conditions to the discs, with about 50% of reduced velocity on the centre line upstream of the second disc and an increase of the maximum streamwise fluctuations by 90%, the mean velocities in the wake are proven to scale with the hub height velocity.展开更多
Different turbulence closures were used to predict the flow interaction between the wakes created by compressor outlet guide vanes(OGVs) and a downstream annular pre-diffuser.Two statistical turbulence models were tes...Different turbulence closures were used to predict the flow interaction between the wakes created by compressor outlet guide vanes(OGVs) and a downstream annular pre-diffuser.Two statistical turbulence models were tested based on the classical Reynolds-averaged Navier-Stokes(RANS) approach.Both high-Re and low-Re(Launder-Sharma) versions of the k-ε model were applied to a selected test problem for OGV wake/diffuser flows.The test problem was specifically chosen because experimentally determined inlet conditions and both profile and performance data were available to validate predictions.A preliminary study was also reported of the more advanced large eddy simulation(LES) approach.The LES sub-grid-scale(SGS) model was the basic Smagorinsky eddy viscosity assumption,with a Van-Driest damping function for improved capture of near-wall viscous behaviour.Comparison between the two RANS models showed little difference in terms of velocity contours at OGV trailing edge and diffuser exit.In terms of overall diffuser performance(static pressure recovery and total pressure loss coefficients),the high-Re model was shown to agree well with experimental data.The preliminary LES study indicates the highly unsteady character of the OGV wake flow,but requires improved treatment of inlet conditions.展开更多
Knowledge about the structure and development of wakes behind wind turbines is important for power optimization of wind power farms. The high turbulence levels in the wakes give rise to undesired unsteady loadings on ...Knowledge about the structure and development of wakes behind wind turbines is important for power optimization of wind power farms. The high turbulence levels in the wakes give rise to undesired unsteady loadings on the downstream turbines, which in the long run might cause fatigue damages. In the present study, the near wake behind a small-scale model wind turbine was investigated experimentally in a wind tunnel. The study consists of measurements with particle image velocimetry using two different inlet conditions: a freely developing boundary layer, causing an almost uniform inflow across the rotor disc, and an inflow with strong shear across the rotor disc, in order to model the atmospheric boundary layer. The results show a faster recovery of the wake in the case with shear inflow, caused by the higher turbulence levels and enhanced mixing of momentum. The increased inlet turbulence levels in this case also resulted in a faster breakdown of the tip vortices as well as different distributions of the streamwise and vertical components of the turbulence intensity in the wake. An analysis comparing vortex statistics for the two cases also showed the presence of strong tip vortices in the case with lower inlet turbulence, while the case with higher inlet turbulence developed a different distribution of vortices in the wake.展开更多
A tight formation of unmanned aerial vehicles(UAVs) has many advantages, such as fuel saving and deceiving enemy radar during battlefield entry. As a result, research on UAVs in close formation has received much atten...A tight formation of unmanned aerial vehicles(UAVs) has many advantages, such as fuel saving and deceiving enemy radar during battlefield entry. As a result, research on UAVs in close formation has received much attention, and the controller design for formation holding has become a popular research topic in the control field. However, there are many unknown disturbances in tight formation, and the tail aircraft is disturbed by the wake. This paper establishes a mathematical model of wake vortices for tail aircraft that considers uncertainty and strong interference. Two UAVs are simulated by Computational Fluid Dynamics software, followed by the design of a semiphysical simulation model predictive control(MPC) scheme that suppresses uncertainty and interference sufficiently to enable the tail aircraft to accurately track the lead aircraft and maintain a stable, tight formation. The tight formation controller is verified by numerical simulation and semiphysical simulation. The results show that the designed controller has an excellent control effect in the case of disturbance caused by the wake vortex.展开更多
文摘The decrease of wind velocity （wake losses） in downstream area of wind turbine is generally quantified using wake models. The overall estimated power of wind farm varies according to reliability of wake model used, however it＇s unclear which model is most appropriate and able to give a high performance in predicting wind velocity deficit. In this subject, a qualification of three analytical wake models （Jensen, lshihara and Frandsen） based on three principal criteria is presented in this paper： （i） the parsimony which characterizes the inverse of model complexity, （ii） the accuracy of estimation in which wake model is compared with the experimental data and （iii） imprecision that is related to assumptions and uncertainty on the value of variables considered in each model. This qualitative analysis shows the inability of wake models to predict wind velocity deficit due to the big uncertainty of variables considered and it sensitivity to wind farm characteristic.
基金Supported by the Key R&D Program of Shandong Province,China(No.2023ZLYS01)the National Key R&D Program of China(No.2022YFC3104200)+2 种基金the National Natural Science Foundation of China(No.12302301)the China Postdoctoral Science Foundation(No.2023M742229)the Zhejiang Provincial Natural Science Foundation(ZJNSF)(No.LQ22F030002)。
文摘Duo to fluctuations in atmospheric turbulence and yaw control strategies,wind turbines are often in a yaw state.To predict the far wake velocity field of wind turbines quickly and accurately,a wake velocity model was derived based on the method of momentum conservation considering the wake steering of the wind turbine under yaw conditions.To consider the shear effect of the vertical incoming wind direction,a two-dimensional Gaussian distribution function was introduced to model the velocity loss at different axial positions in the far wake region based on the assumption of nonlinear wake expansion.This work also developed a“prediction-correction”method to solve the wake velocity field,and the accuracy of the model results was verified in wake experiments on the Garrad Hassan wind turbine.Moreover,a 33-kW two-blade horizontal axis wind turbine was simulated using this method,and the results were compared with the classical wake model under the same parameters and the computational fluid dynamics(CFD)simulation results.The results show that the nonlinear wake model well reflected the influence of incoming flow shear and yaw wake steering in the wake velocity field.Finally,computation of the wake flow for the Horns Rev offshore wind farm with 80 wind turbines showed an error within 8%compared to the experimental values.The established wake model is less computationally intensive than other methods,has a faster calculation speed,and can be used for engineering calculations of the wake velocity in the far wakefield of wind turbines.
基金The National Natural Science Foundation of China (No. 51908107)。
文摘To enhance the prediction accuracy of unsteady wakes behind wind turbines,a novel reduced-order model is proposed by integrating a multifunctional recurrent fuzzy neural network(MFRFNN)and proper orthogonal decom-position(POD).First,POD is employed to reduce the di-mensionality of the wind field data,extracting spatiotempo-rally correlated modal coefficients and modes.These reduced-order variables can effectively capture the essential features of unsteady wake behaviors.Next,MFRFNN is utilized to predict the time series of modal coefficients.Fi-nally,by combining the predicted modal coefficients with their corresponding modes,a flow field is reconstructed,al-lowing accurate prediction of unsteady wake dynamics.The predicted wake data exhibit high consistency with large eddy simulation results in both the near-and far-wake re-gions and outperform existing data-driven methods.This ap-proach offers significant potential for optimizing wind farm design and provides a new solution for the precise prediction of wind turbine wake behavior.
基金Supported by the National Natural Science Foundation of China under Grant No.52131102.
文摘With the rapid advancement of machine learning technology and its growing adoption in research and engineering applications,an increasing number of studies have embraced data-driven approaches for modeling wind turbine wakes.These models leverage the ability to capture complex,high-dimensional characteristics of wind turbine wakes while offering significantly greater efficiency in the prediction process than physics-driven models.As a result,data-driven wind turbine wake models are regarded as powerful and effective tools for predicting wake behavior and turbine power output.This paper aims to provide a concise yet comprehensive review of existing studies on wind turbine wake modeling that employ data-driven approaches.It begins by defining and classifying machine learning methods to facilitate a clearer understanding of the reviewed literature.Subsequently,the related studies are categorized into four key areas:wind turbine power prediction,data-driven analytic wake models,wake field reconstruction,and the incorporation of explicit physical constraints.The accuracy of data-driven models is influenced by two primary factors:the quality of the training data and the performance of the model itself.Accordingly,both data accuracy and model structure are discussed in detail within the review.
文摘A modified wake model was proposed for the newly developed bubble-induced three-phase inverse fluidized bed(BIFB),by combining the generalized wake model and the gas-perturbed liquid model.On the basis of the modified wake model,the solids and liquid holdups and the complete fluidization gas velocity in BIFB system have been successfully predicted with two established correlations.The predictions achieved very good agreements with the experimental data.
文摘The Light Detection and Ranging(LiDAR)data analysis method has emerged as a powerful and versatile tool for characterizing atmospheric conditions and modeling light propagation through various media.In the context of renewable energy,particularly wind energy,LiDAR is increasingly utilized to analyze wind flow,turbine wake effects,and turbulence in complex terrains.This study focuses on advancing LiDAR data interpretation through the development and application of the LiDAR Statistical Barnes Objective Analysis(LiSBOA)method.LiSBOA enhances the capacity of scanning LiDAR systems by enabling more precise optimization of scan configurations and improving the retrieval of wind statistics across Cartesian grids.Unlike conventional approaches,LiSBOA offers fine-grained control over azimuthal resolution and spatial filtering,which allows for the detailed reconstruction of wind fields and turbulence structures.These capabilities are crucial for accurately simulating wind turbine wakes and power capture,particularly in environments with variable atmospheric stability and complex topography.Field deployments and comparative assessments against traditional meteorological mast data demonstrate the effectiveness of LiSBOA.The method reduces wind velocity estimation errors to within 3%and increases the accuracy of turbulence intensity measurements by over 4%.Such improvements are significant for enhancing wind resource assessment,optimizing turbine placement,and refining control strategies for operational turbines.LiSBOA represents a robust advancement in LiDAR data processing for wind energy applications.By addressing limitations in spatial resolution and measurement uncertainty,it supports more reliable modeling of wake interactions and flow variability.This work contributes to improving the efficiency and reliability of wind energy systems through advanced remote sensing and statistical analysis techniques.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.51379144,51479135 and51679167)the Science Fund for Creative Research Groups of the National Natural Science Foundation of China(Grant No.51621092)
文摘It is well known that the Reynolds number has a significant effect on the vortex-induced vibrations(VIV) of cylinders. In this paper, a novel in-line(IL) and cross-flow(CF) coupling VIV prediction model for circular cylinders has been proposed, in which the influence of the Reynolds number was comprehensively considered. The Strouhal number linked with the vortex shedding frequency was calculated through a function of the Reynolds number. The coefficient of the mean drag force was fitted as a new piecewise function of the Reynolds number, and its amplification resulted from the CF VIV was also taken into account. The oscillating drag and lift forces were modelled with classical van der Pol wake oscillators and their empirical parameters were determined based on the lock-in boundaries and the peak-amplitude formulas. A new peak-amplitude formula for the IL VIV was developed under the resonance condition with respect to the mass-damping ratio and the Reynolds number. When compared with the results from the experiments and some other prediction models, the present model could give good estimations on the vibration amplitudes and frequencies of the VIV both for elastically-mounted rigid and long flexible cylinders. The present model considering the influence of the Reynolds number could generally provide better results than that neglecting the effect of the Reynolds number.
基金State Key Development Program for Basic Research of China (No.2006CB200305), the National Natural Sci-ence Foundation of China (No.50376004), and Ph.D. Program Foundation of Ministry of Education of China (No.20030007028).
文摘Presently developed two-phase turbulence models under-predict the gas turbulent fluctuation, because their turbulence modification models cannot fully reflect the effect of particles. In this paper, a two-time-scale dis- sipation model of turbulence modification, developed for the two-phase velocity correlation and for the dissipation rate of gas turbulent kinetic energy, is proposed and used to simulate sudden-expansion and swirling gas-particle flows. The proposed two-time scale model gives better results than the single-time scale model. Besides, a gas tur- bulence augmentation model accounting for the finite-size particle wake effect in the gas Reynolds stress equation is proposed. The proposed turbulence modification models are used to simulate two-phase pipe flows. It can prop- erly predict both turbulence reduction and turbulence enhancement for a certain size of particles observed in ex- periments.
基金Project supported by the National Basic Research Program of China(No.2014CB046201)the National Natural Science Foundation of China(Nos.51766009,51566011,and 51479114)
文摘Determination of the aerodynamic configuration of wake is the key to analysis and evaluation of the rotor aerodynamic characteristics of a horizontal-axis wind turbine. According to the aerodynamic configuration, the real magnitude and direction of the onflow velocity at the rotor blade can be determined, and subsequently, the aerodynamic force on the rotor can be determined. The commonly employed wake aerodynamic models are of the cylindrical form instead of the actual expanding one. This is because the influence of the radial component of the induced velocity on the wake configuration is neglected. Therefore, this model should be called a "linear model". Using this model means that the induced velocities at the rotor blades and aerodynamic loads on them would be inexact. An approximately accurate approach is proposed in this paper to determine the so-called "nonlinear" wake aerodynamic configuration by means of the potential theory, where the influence of all three coordinate components of the induced velocity on wake aerodynamic configuration is taken into account to obtain a kind of expanding wake that approximately looks like an actual one. First, the rotor aerodynamic model composed of axial (central), bound, and trailing vortexes is established with the help of the finite aspect wing theory. Then, the Biot-Savart formula for the potential flow theory is used to derive a set of integral equations to evaluate the three components of the induced velocity at any point within the wake. The numerical solution to the integral equations is found, and the loci of all elementary trailing vortex filaments behind the rotor are determined thereafter. Finally, to formulate an actual wind turbine rotor, using the nonlinear wake model, the induced velocity everywhere in the wake, especially that at the rotor blade, is obtained in the case of various tip speed ratios and compared with the wake boundary in a neutral atmospheric boundary layer. Hereby, some useful and referential conclusions are offered for the aerodynamic computation and design of the rotor of the horizontal-axis wind turbine.
基金funded jointly by the National Basic Research Program of China(″973″Program)(No2014CB046200)the Natural Science Foundation of Jiangsu Province(BK2014059)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘With the assumption of the Park model that the wake region is in linear expansion and the cross-wind is in multinomial and Gaussian distribution in wake region,one develops the Park-polynomial model and the ParkGaussian model to numerically simulate the wake flow field for a single wind turbine.Compared with the measured data of wind farm and the wind tunnel test,it shows that the prediction precision of wake field has been improved obviously under the modified initial wake radius.Moreover,both of the newly modified two models could well simulate the wind velocity in wake region,because the predicted results is approximately consistent with the test result,and the cross-wind distribution conforms to that of the real flow field.The two models have still inherited many advantages of engineering models,such as simple form,easy-to-code,and high computational efficiency.Particularly,the Park-Gaussian model is the best in overall performance among them.
文摘Wind tunnel measurements using particle image velocimetry have been performed around two perforated discs, with varying streamwise distance, in order to simulate the wake interaction between wind turbines. The static pressure footprint (p-f) on ground level associated with the wake behind the disc and wake velocity data for both the streamwise and wall-normal velocity components with the corresponding turbulence intensities are reported. The p-f method shows that the size of the wake regions, behind the wind turbine models, initially drop when a second disc is placed just downstream of the first one. From a mutual distance (Δ χ) of about five disc diameters (5D), both wake footprints increase as the mutual distance is increased, and for very large mutual distances, approximately Δ χ/ D > 15, the footprint of the downstream disc has recovered and is about the same as for a single disc. At last we conclude that despite very different inlet conditions to the discs, with about 50% of reduced velocity on the centre line upstream of the second disc and an increase of the maximum streamwise fluctuations by 90%, the mean velocities in the wake are proven to scale with the hub height velocity.
文摘Different turbulence closures were used to predict the flow interaction between the wakes created by compressor outlet guide vanes(OGVs) and a downstream annular pre-diffuser.Two statistical turbulence models were tested based on the classical Reynolds-averaged Navier-Stokes(RANS) approach.Both high-Re and low-Re(Launder-Sharma) versions of the k-ε model were applied to a selected test problem for OGV wake/diffuser flows.The test problem was specifically chosen because experimentally determined inlet conditions and both profile and performance data were available to validate predictions.A preliminary study was also reported of the more advanced large eddy simulation(LES) approach.The LES sub-grid-scale(SGS) model was the basic Smagorinsky eddy viscosity assumption,with a Van-Driest damping function for improved capture of near-wall viscous behaviour.Comparison between the two RANS models showed little difference in terms of velocity contours at OGV trailing edge and diffuser exit.In terms of overall diffuser performance(static pressure recovery and total pressure loss coefficients),the high-Re model was shown to agree well with experimental data.The preliminary LES study indicates the highly unsteady character of the OGV wake flow,but requires improved treatment of inlet conditions.
文摘Knowledge about the structure and development of wakes behind wind turbines is important for power optimization of wind power farms. The high turbulence levels in the wakes give rise to undesired unsteady loadings on the downstream turbines, which in the long run might cause fatigue damages. In the present study, the near wake behind a small-scale model wind turbine was investigated experimentally in a wind tunnel. The study consists of measurements with particle image velocimetry using two different inlet conditions: a freely developing boundary layer, causing an almost uniform inflow across the rotor disc, and an inflow with strong shear across the rotor disc, in order to model the atmospheric boundary layer. The results show a faster recovery of the wake in the case with shear inflow, caused by the higher turbulence levels and enhanced mixing of momentum. The increased inlet turbulence levels in this case also resulted in a faster breakdown of the tip vortices as well as different distributions of the streamwise and vertical components of the turbulence intensity in the wake. An analysis comparing vortex statistics for the two cases also showed the presence of strong tip vortices in the case with lower inlet turbulence, while the case with higher inlet turbulence developed a different distribution of vortices in the wake.
基金funded by the National Natural Science Foundation of China (Grant Nos. 62173277 and 61573286)the Natural Science Foundation of Shaanxi Province (Grant No. 2022JM-011)+1 种基金the Aeronautical Science Foundation of China (Grant No. 201905053004)the Shaanxi Province Key Laboratory of Flight Control and Simulation Technology。
文摘A tight formation of unmanned aerial vehicles(UAVs) has many advantages, such as fuel saving and deceiving enemy radar during battlefield entry. As a result, research on UAVs in close formation has received much attention, and the controller design for formation holding has become a popular research topic in the control field. However, there are many unknown disturbances in tight formation, and the tail aircraft is disturbed by the wake. This paper establishes a mathematical model of wake vortices for tail aircraft that considers uncertainty and strong interference. Two UAVs are simulated by Computational Fluid Dynamics software, followed by the design of a semiphysical simulation model predictive control(MPC) scheme that suppresses uncertainty and interference sufficiently to enable the tail aircraft to accurately track the lead aircraft and maintain a stable, tight formation. The tight formation controller is verified by numerical simulation and semiphysical simulation. The results show that the designed controller has an excellent control effect in the case of disturbance caused by the wake vortex.
