Dynamic Stall Control on the Wind Turbine Airfoil via a Co-Flow Jet

Transcription

1 energies Article Dynamic Stall Control on Wind Turbine Airfoil via a Co-Flow Jet He-Yong Xu *, Chen-Liang Qiao Zheng-Yin Ye National Key Laboratory Science Technology on Aerodynamic Design Research, Northwestern Polytechnical University, Xi an , China; qiao_chenliang@163.com (C.-L.Q.); yezy@nwpu.edu.cn (Z.-Y.Y.) * Correspondence: xuheyong@nwpu.edu.cn; Tel.: Academic Editors: Lance Manuel Rupp Carriveau Received: 18 March 2016; Accepted: 30 May 2016; Published: 2 June 2016 Abstract: Dynamic stall control a S809 airfoil is numerically investigated by implementing a co- jet (). numerical methods solver are validated by comparing results with baseline experiment as well as a NACA 6415-based experiment, showing good agreement in both static dynamic characteristics. airfoil with inactive jet is simulated to study impact that jet channel imposes upon dynamic characteristics. It is shown that presence a long jet channel could cause a negative effect decreasing lift increasing drag, leading to fluctuating extreme loads in terms drag moment. main focus present research is investigation dynamic characteristics airfoil with three different jet momentum coefficients, which are compared with baseline, giving encouraging results. Dynamic stall can be greatly suppressed, showing a very good control performance significantly increased lift reduced drag moment. Analysis amplitude variation in aerodynamic coefficients indicates that fluctuating extreme aerodynamic loads are significantly alleviated, which is conducive to structural reliability improved life cycle. energy consumption analysis shows that concept is applicable economical in controlling dynamic stall. Keywords: dynamic stall; wind turbine; control; numerical simulation; co- jet 1. Introduction depletion fossil-fuel reserves, stricter environmental regulations world s ever-growing energy dem have greatly promoted usage alternative renewable energy sources. Among various renewable energy alternatives, wind energy is one most promising fastest growing installed alternative-energy production technology due to its wide availability [1]. In Half Year Report World Wind Energy Association [2], it was reported that growth wind energy industry will continue with rapid increase in energy dem, refore more efforts are still needed to increase efficiency wind energy generation in order to keep wind energy economically competitive compared with traditional fossil fuels or renewable energy sources such as hydroelectric energy, solar energy bio-energy. Two factors that affect cost wind energy are lifetime energy capture maintenance cost. refore, since beginning commercial wind industry, rotor diameter turbine size have gradually increased in order to capture more energy during lifetime. As turbines grow in size, structural fatigue loads become more noticeable. extreme structural fatigue loads are important factors in turbine design most se loads result from dynamic stall. A dynamic stall phenomenon takes place when wind turbine blade section is subjected to unsteady variation angle attack. Due to complicated atmospheric environment at wind farms, wind turbine blades usually experience adverse conditions under which local angle attack a particular blade Energies 2016, 9, 429; doi: /en

2 Energies 2016, 9, section will vary with time, including ground boundary layer effects, horizontal or vertical wind shear, tower shadowing, yaw tilt misalignment, unsteady in due to atmospheric turbulence or wake from or turbines. All se conditions can give rise to dynamic stall phenomenon. unsteady aerodynamic load produced by dynamic stall is also a main source vibration [3] aero-acoustic noise [4]. With increasing deployment, more wind turbines will be located within residential areas, where aerodynamic noise emitted by rotors may have a negative impact on comfort living in vicinity. To minimize se factors, reduce maintenance costs, prolong turbine lifetime reduce noise level, one effective way is to explore effective control methods, passive or active, to alleviate fluctuations aerodynamic loads. On or h, wind farms in natural conditions may frequently experience adverse working conditions where wind speed is very low hence conventional wind turbines generate little or no usable power. This issue has limited deployment wind turbines to relatively few sites where favorable wind conditions exist. refore, re is a dem to develop effective control methods which can significantly increase lift blade at low wind speeds allow turbine to cut-in earlier capture additional energy. Hence, for a control method, it is important to provide blade with both, good static dynamic, aerodynamic permance. Various control methods have been investigated to enhance wind turbine blade performance, including trailing edge flaps [5], microtabs [6,7], vortex generators [8], blowing jets [9,10], circulation control [11], Gurney flaps [11], syntic jets [12], plasma actuators [13]. Hanns et al. [10] carried out an experimental study to explore constant blowing as a control concept for wind turbine blades. ir results showed that control from leading-edge slot had a significant potential for load control applications, while control from mid-chord slot significantly enhanced lift at pre-stall angles attack but was ineffective for suppressing leading-edge stall. Tongchitpakdee et al. [11] studied compared static aerodynamic performances a wind turbine rotor equipped with trailing-edge blowing Gurney flaps. results indicated that for attached conditions, trailing-edge blowing Gurney flap both can produce a net increase in power generation compared with baseline turbine rotor. However, results also indicated that at high-wind speed conditions where separates, trailing-edge blowing Gurney flap both became ineffective in increasing power output. Yen Ahmed [12] implemented syntic jets to study wind turbine dynamic stall control demonstrated that syntic jets could improve low speed vertical-axis wind turbine performance but without substantially alleviating stall separation. Greenblatt et al. [13] experimentally measured effects plasma pulsation on dynamic stall control on upwind half a turbine also limited phase-locked particle image velocimetry measurements were performed under baseline as well as two controlled conditions. It was found that at lower maximum angles attack, effect pulsations on dynamic stall was greater, but separation was not fully controlled, power required to drive actuators was significantly larger than resulting turbine power increase. Zha et al. [14 20] have developed a new control method by implementing a co- jet () on suction surface, which has been proved an effective way to significantly increase lift, stall margin drag reduction for stationary airfoils enhance performance pitching airfoils in aircraft research field. working mechanism a is different from conventional circulation control which relies on large-radius leading edge or trailing edge to induce Coa effect enhance circulation. relies on jet mixing with main to energize main overcome adverse pressure gradient. Moreover, jet suction effect near suction slot furr enhances stability to remain attached to surface at high angles attack (AoA), thus inducing much higher circulation than conventional circulation control without jet suction. In a previous study, Xu et al. [21] introduced this concept to wind turbine airfoil application, focusing on static performance with active as well as inactive. results showed that steady co- jet had a great positive effect in lift enhancement, stall margin expansion, drag reduction. For cases with jet momentum coefficients larger than 0.12, total drag even became negative due to jet reaction forces.

3 Energies 2016, 9, In present study, concept is extended to dynamic stall control on a wind turbine Energies 2016, 9, airfoil. Energies 2016, 9, primary 429 purpose is to investigate dynamic performance in suppressing 3 25 wind turbine airfoil airfoil dynamic dynamic stall stall consequently consequently alleviating alleviating fluctuating fluctuating aerodynamic aerodynamic loads. Energy loads. consumed Energy wind turbine consumed by airfoil by pump dynamic is pump analyzed stall is analyzed consequently compared compared with alleviating amount with fluctuating amount gainedaerodynamic energy to assess energy loads. to economy assess Energy consumed economy implementing by implementing pump onis analyzed wind on turbine wind compared to control turbine with dynamic to control amount stall. dynamic gained stall. energy to assess economy implementing on wind turbine to control dynamic stall Design Design Airfoil Airfoil 2. Design NREL S809 wind Airfoil NREL S809 wind turbine turbine airfoil airfoil is is used used in in present present study study as as baseline baseline its its detailed detailed parameters parameters NREL are are given given S809 wind [22]. [22]. turbine corresponding corresponding airfoil is used in conceptual conceptual present study airfoil airfoil as is is shown shown baseline Figure Figure its 1, 1, detailed with with an an injection injection parameters slot slot are near near given in leading leading [22]. edge edge corresponding a suction suction slot slot conceptual near near airfoil trailing trailing is edge edge shown on on in Figure airfoil airfoil 1, suction with suction an surface. surface. injection se se slot near slots slots are are leading formed formed edge by by translating translating a suction downward downward slot near a portion portion trailing suction suction edge surface, surface, on airfoil giving giving suction rise rise to to surface. presence presence se slots a jet jet are channel. channel. formed When When by translating co- co downward jet jet is is activated, activated, a portion a jet jet is is suction injected injected surface, tangentially tangentially giving into into rise to main main presence,, a same same jet channel. amount amount When mass mass co is is sucked sucked jet is activated, into into suction suction a jet is slot, slot, injected forming forming tangentially a closed-loop closed loop into jet jet circuit. circuit. main, A pump pump a can can same be beamount used used to to power power mass co- co is sucked jet jet.. into By By suction using using a slot, closed-loop closed loop forming jet jet a closed loop recirculation, recirculation, jet circuit. A attachment attachment pump can on on be used suction suction to power surface surface will will co be be greatly greatly jet. strengned, strengned, By using a allowing allowing closed loop an an attractive attractive jet recirculation, ability ability to to resist resist severe severe attachment adverse adverse on pressure pressure suction gradients gradients surface at will at high high be greatly angles angles strengned, attack. attack. source source allowing jet jet an attractive is is provided provided ability by by to resist sucking sucking severe an an equal equal adverse amount amount pressure gradients mass mass from from at high angles suction suction slot slot attack. rar rar than than source engine, engine, jet which which is provided makes makes by sucking co- co jet an jet equal a zero zero amount net net mass mass.. mass from suction slot rar than engine, which makes co jet a zero net mass. Figure 1. Co jet conceptual airfoil. Figure 1. Co- jet conceptual airfoil. Figure 1. Co jet conceptual airfoil. computational model S809 airfoil is shown in Figure 2a, which includes cavities computational model S809 airfoil is shown in Figure 2a, which includes cavities injection computational suction in model order to S809 make airfoil simulation is shown more in Figure realistic. 2a, which location includes injection cavities slot injection suction in order to make simulation more realistic. location injection slot AC injection is set at 6.0%c suction from in order leading to make edge, perpendicular simulation to more realistic. local surface with location height injection 0.65%c. slot AC is set at 6.0%c from leading edge, perpendicular to local surface with height 0.65%c. AC is location set 6.0%c suction from slot leading BD is set edge, at 20.0%c perpendicular from to trailing local edge, surface perpendicular with a height to 0.65%c. local location suction slot BD is set at 20.0%c from trailing edge, perpendicular to local surface surface location with a height suction 1.38%c. slot BD To is ensure set at 20.0%c that from jet is tangential trailing to edge, surface, perpendicular a jet channel to linking local with a height 1.38%c. To ensure that jet is tangential to surface, a jet channel linking surface injection with a height suction 1.38%c. slots is To carefully ensure that designed jet by is tangential translating to downward surface, a jet slightly channel rotating linking injection suction slots is carefully designed by translating downward slightly rotating portion injection AB suction baseline slots suction is carefully surface designed to targeted by translating location downward CD. For case slightly inactivated rotating portion AB baseline suction surface to targeted location CD. For case inactivated co portion jet, re AB is nearly baseline no mass suction surface through to slots, targeted high pressure location CD. For low pressure case inactivated cavities co- jet, re is nearly no mass through slots, high-pressure low-pressure cavities are co excluded jet, re for simplicity, is nearly no as mass shown in through Figure 2b. slots, high pressure low pressure cavities are excluded for simplicity, as shown in Figure 2b. are excluded for simplicity, as shown in Figure 2b. (a) (b) (a) (b) Figure 2. computational models S809 airfoil: (a) Jet on; (b) Jet f. Figure 2. computational models S809 airfoil: (a) Jet on; (b) Jet f. Figure 2. computational models S809 airfoil: (a) Jet-on; (b) Jet-f. 3. Methodology 3. Methodology 3. Methodology 3.1. Numerical Methods 3.1. Numerical unsteady Methods Reynolds Averaged Navier Stokes equations Spalart Allmaras one equation turbulence unsteady model are Reynolds-Averaged Reynolds Averaged used in present Navier-Stokes Navier Stokes in house code equations to carry out Spalart-Allmaras Spalart Allmaras numerical study. one-equation one equation More details turbulence about governing model are equations used in present boundary in-house in house conditions code to can carry be out found in numerical [21]. study. dual time More stepping details about method [23] governing is adopted equations to advance boundary time accuracy conditions solution can be be with found pseudo in in [21]. time marching dual-time dual time by stepping means method LU SGS [23] is adopted method to [24]. advance Roe scheme time accuracy [25] with solution a third with order pseudo MUSCL time reconstruction marching by means [26] is used to LU SGS discretize method inviscid [24]. fluxes Roe scheme second [25] with central a third differencing order MUSCL is used reconstruction for computing [26] is viscous used to fluxes. discretize OpenMP inviscid parallel fluxes computing second technique central [27] is differencing applied to accelerate is used for computing simulation. viscous fluxes. OpenMP parallel computing technique [27] is applied to accelerate simulation.

4 Energies 2016, 9, method [23] is adopted to advance time-accuracy solution with pseudo time marching by means LU-SGS method [24]. Roe scheme [25] with a third order MUSCL reconstruction [26] is used to discretize inviscid fluxes second central differencing is used for computing viscous fluxes. OpenMP parallel computing technique [27] is applied to accelerate simulation. in out specified at far-field boundary are based on characteristics. For inlet exit boundaries, EF GH, in high-pressure cavity low-pressure cavity shown in Figure 2a, conditions are defined in different ways in order to easily implement concept. At inlet boundary EF, total pressure P t, total temperature T t, angle α are specified in velocity u is extrapolated from interior. At exit boundary GH, static pressure P s is specified, three primitive variables u, v ρ are extrapolated from interior domain. In simulation, total pressure P t at boundary EF static pressure P s at boundary GH are subject to change during numerical iteration until desired jet momentum coefficient is achieved at both inlet EF outlet GH. solid surface airfoil cavities are defined as non-slip wall boundaries. Density pressure on surface are obtained by extrapolation from interior solution. For jet-f case, jet slots AC BD are assumed to be wall boundaries, high-pressure low-pressure cavities are not included in computation Pitch Oscillation Motion Relevant Parameters present study investigates unsteady aerodynamic characteristics NREL S809 baseline airfoils undergoing sinusoidal pitch oscillations about quarter chord point with various jet momentum coefficients. pitch oscillation motion an airfoil can be described in a sine-wave form expression which is defined in terms instantaneous angle attack by: αptq α 0 ` α 1 sinpωtq (1) where α 0 α 1 are mean angle pitch oscillation amplitude respectively. ω 2π f, with f being frequency oscillation. For oscillating airfoils, reduced frequency κ is usually used to describe unsteady motion, which is defined as: κ ωc (2) 2V 8 where c is chord length, V 8 is velocity free stream. This parameter represents interaction between oscillation motion about pitch axis main in chord-wise direction. magnitude parameter reflects degree impact that oscillation motion imposes upon main Relevant Parameters in Airfoil Simulation implementation a co- jet is usually characterized by a similarity parameter C µ, known as momentum coefficient, which is defined as: C µ. m j V j 0.5ρ 8 V 2 8S where ṁ j is co- jet mass rate, V j is injection jet velocity, ρ 8 is free-stream density, V 8 is free-stream velocity, S is equal to c for present two dimensional cases. In concept, power required to pump jet is determined by jet mass rate total pressure ratio to overcome total pressure loss recirculated jet. power is usually described by a non-dimensional similarity parameter called power coefficient P c, which is defined as: P c. m c f j c p T 01 η c f j» ˆ P02 P 01 γ 1 γ c f j fi ı 1flO 0.5ρ 8 V8S 3 (3) (4)

5 Energies 2016, 9, where η cfj is pump efficiency, c p is specific heat at constant pressure, P 01 is total pressure at pump inlet GH, P 02 is total pressure at pump exit EF, T 01 is total temperature at pump inlet GH Dynamic Mesh Strategy pitch oscillation motion an airfoil is a classic unsteady problem which needs a dynamic mesh to simulate motion airfoil. dynamic mesh is necessary for hling unsteady problems involving geometric deformation or relative motion between multiple bodies. Usually dynamic mesh strategies are divided into several categories, including mesh deformation, mesh regeneration, sliding mesh, overset mesh. current authors have also developed a new kind rotational dynamic overset mesh, simulated NACA 0012 pitch oscillation [28] as well as or cases with relatively moving bodies [29 33]. All above four dynamic grid strategies can be applied to airfoil oscillation simulation, but more manipulation is needed to obtain accurate results. In present study, only single airfoil undergoing a rigid oscillation motion is considered without regarding any or relatively moving bodies. Hence a more simple dynamic mesh strategy that does not fall into above four categories is appropriate for present study, which is called rigid moving mesh. mesh performs a rigid rotation about airfoil quarter-chord point according to oscillation motion grid velocity can be calculated in a straightforward way by dividing moved distance from one physical time step to next by interval time step. 4. Results Discussion 4.1. Baseline Simulation Validation static prediction precision solver has been validated in a previous study [21] by comparing numerical results NREL S809 airfoil static characteristics with experiment conducted in Delft University Technology [34]. Here, dynamic prediction precision solver will be validated by comparing results with experiment conducted at Ohio State University (OSU) [22]. pitch oscillation, as well as static characteristics, are both investigated in OSU experiment in order to aid in developments new airfoil performance codes that account for unsteady behavior. OSU-measured sectional static aerodynamic coefficients S809 airfoil with angle attack will also be simulated can be used to compare with dynamic counterparts Static Aerodynamic Characteristics Grid-Resolution Study In experiment, original sharp trailing edge a 457-mm chord S809 airfoil was thickened to 1.25-mm for fabrication purposes. This thickness was added to upper surface over last 10% chord. In present simulation, this minor modification is taken into account for modeling grid generation. For a locally blunt trailing edge, O-mesh is a better choice than C-mesh which is used for a previous static performance study [21] on a sharp trailing edge S809 airfoil, since O-mesh can easily ensure mesh orthogonality in vicinity a blunt trailing edge. static simulation conditions are set in correspondence with its counterpart oscillation simulation, with Ma = 0.076, Re = 1.0 ˆ First, grid-resolution study is carried out for AoA = 4.1. Three different mesh resolutions are tested: a course mesh 1.28 ˆ 10 4 cells, a medium mesh 2.88 ˆ 10 4 cells, a fine mesh 5.12 ˆ 10 4 cells. Relevant dimensions spacing three meshes are given in Table 1. mesh refinement is carried out in airfoil s normal direction as well as wrapping direction. first layer spacing is equal to or less than 1 ˆ 10 5 to ensure that y+ is less than 1. Figure 3 shows medium mesh. comparisons aerodynamic coefficients for different mesh levels are listed in Table 2. lift moment coefficients have a fairly good agreement with experimental results, whereas numerical drag coefficients are much larger. This discrepancy between numerical experimental drag coefficients is probably because numerical simulations are carried out under assumption full turbulence which causes drag larger than that a laminar. In experiment re

6 Energies 2016, 9, probably exists transition at a certain location on suction surface, before which is laminar, hence resulting drag is lower than assumed full turbulent. introduction a transition model into simulation is expected to reduce discrepancy. From an overall view Table 2, aerodynamic coefficients predicted with a finer mesh are closer to experimental results, re is a small difference between medium fine mesh. refore, all simulations are performed using medium mesh. jet-f airfoil mesh is obtained by adding corresponding part jet channel mesh to baseline medium mesh. Similarly, jet-on airfoil mesh is obtained by adding corresponding parts jet channel mesh, high-pressure low-pressure cavities meshes to baseline medium mesh. Table 1. Details grid employed for S809 baseline airfoil. Parameters Coarse Grid Medium Grid Fine Grid Far field radius/c Normal layers in O-mesh Wrap-around points Leading-edge spacing/c Trailing-edge spacing/c First layer spacing/c, ˆ Spacing increasing ratio Total number cells, ˆ Energies 2016, 9, Figure 3. O mesh for S809 airfoil (medium level). Figure 3. O-mesh for S809 airfoil (medium level). comparisons aerodynamic coefficients for different mesh levels are listed in Table 2. Table 2. Comparison aerodynamic coefficients for different mesh levels [Ma = 0.076, Re = 1 ˆ 10 lift moment coefficients have a fairly good agreement with experimental results, whereas 6, AoA = 4.1 ]. numerical drag coefficients are much larger. This discrepancy between numerical experimental drag coefficients is probably because numerical simulations are carried out under Parameters Coarse Grid Medium Grid Fine Grid Experiment assumption full turbulence which causes drag larger than that a laminar. In experiment re probably C L exists transition at a certain location on suction surface, before which is laminar, C D hence resulting drag is lower than assumed full turbulent. C introduction M a transition model into simulation is expected to reduce discrepancy. From an overall view Table 2, aerodynamic coefficients predicted with a finer mesh are closer to experimental medium mesh results, is furr used re to is simulate a small difference a wide range between angles medium attack from 20 fine mesh. to 24 forrefore, more validations. all simulations computed are performed aerodynamic using force medium moment mesh. coefficients jet f areairfoil compared mesh with is experimental obtained by results adding in Figure corresponding 4. All simulations part jet are channel carriedmesh out at to same baseline Mach number medium mesh. Reynolds Similarly, number jet on 1.0 ˆ 10airfoil 6. mesh present is obtained static results by adding will be used corresponding to compareparts with next jet channel dynamic stall mesh, results which high pressure vary in a range low pressure anglescavities attackmeshes between to 4 baseline 24. medium From Figure mesh. 4, for range angles attack from 6 to 8, numerical results agree rar well with measurement. After separation Table 2. Comparison occurrence, aerodynamic lift is a little coefficients over-predicted for different but mesh within levels an [Ma acceptable = 0.076, Re degree, = , variation AoA trend = 4.1 ]. is well captured. Overall, present numerical results agree fairly well with experiment. Parameters Coarse Grid Medium Grid Fine Grid Experiment CL CD CM

7 Energies 2016, 9, Figure 5 gives comparison surface pressure coefficient distributions with measurements for several AoA conditions, also showing rar good agreements except for large angles attack over 20. Energies 2016, 9, Energies 2016, 9, (a) (a) (b) (b) (c) Figure 4. Comparisons computed static aerodynamic (c) coefficients with experiment: (a) Lift coefficient; Figure 4. Comparisons computed static aerodynamic coefficients with experiment: (a) Lift coefficient; (b) Figure Drag 4. coefficient; Comparisons (c) Moment computed coefficient. static aerodynamic coefficients with experiment: (a) Lift coefficient; (b) Drag coefficient; (c) Moment coefficient. (b) Drag coefficient; (c) Moment coefficient. (a) (a) Figure Cont. Cont. Figure 5. Cont. (b) (b)

8 Energies 2016, 9, Energies 2016, 9, Energies 2016, 9, (c) (d) Figure 5. Comparisons surface pressure coefficient distributions with experiment: (a) AoA = 6.1 ; Figure 5. Comparisons surface pressure coefficient distributions with experiment: (a) AoA = 6.1 ; (b) AoA = 12.2 ; (c) AoA = 18.1 ; (d) AoA = 24. (b) AoA = 12.2 ; (c) AoA (c) = 18.1 ; (d) AoA = 24. (d) Dynamic Figure 5. Comparisons Characteristics surface Time Resolution pressure coefficient Study distributions with experiment: (a) AoA = 6.1 ; Dynamic (b) AoA Characteristics = 12.2 ; (c) AoA = 18.1 ; Time-Resolution (d) AoA = 24. Study In OSU experiment, unsteady data were obtained for S809 airfoil model undergoing In OSU experiment, unsteady data were obtained for S809 airfoil model undergoing sinusoidal Dynamic pitch oscillations Characteristics with a comprehensive Time Resolution set Study test conditions, including two angle attack sinusoidal amplitudes, pitch ±5.5 oscillations ±10 ; with four a Reynolds comprehensive numbers, set 0.75, test 1.0, conditions, 1.25, 1.4 including million; three two angle pitch attack oscillation amplitudes, In OSU reduced 5.5 experiment, frequencies, 10 ; unsteady 0.026, fourdata 0.052, Reynolds were obtained 0.077; numbers, for three 0.75, S809 mean 1.0, airfoil angles 1.25, model attack, 1.4undergoing million; 8, 14, three pitch sinusoidal 20. oscillation pitch In present reduced oscillations study, frequencies, with a comprehensive following 0.026, conditions 0.052, set are selected 0.077; test conditions, for three including all mean validation angles two angle simulations attack, attack 8, as 14, amplitudes, ±5.5 ±10 ; four Reynolds numbers, 0.75, 1.0, 1.25, 1.4 million; three pitch well 20. as In subsequent present study, comparative following studies: conditions mean angle are selected attack αfor 0 = all 14, angle validation attack amplitude simulations oscillation reduced frequencies, 0.026, 0.052, 0.077; three mean angles attack, 8, 14, as αwell 1 = 10, as Reynolds subsequent number comparative Re = 1.0 million, studies: mean reduced angle frequency attackκ α= 0 = , angle airfoil attack performs amplitude 20. In present study, following conditions are selected for all validation simulations as α 1 sinusoidal = 10, Reynolds pitch oscillation number Re about = 1.0its million, quarter chord reduced point. frequency κ = airfoil performs well as subsequent comparative studies: mean angle attack α 0 = 14, angle attack amplitude sinusoidal α 1 = 10, pitch Reynolds simulations oscillation number are about Re performed = 1.0 itsmillion, quarterusing chord reduced point. three frequency different κ = non dimensional airfoil performs time steps (non dimensionalized sinusoidal simulations pitch oscillation by arec/v about performed ) dt = its 0.008, quarter 0.010, using chord 0.012, three point. respectively, different in non-dimensional order to investigate time time steps (non-dimensionalized step sensitivity simulations based on by are c/v aerodynamic 8 performed ) dt = 0.008, coefficients. using 0.010, three Four 0.012, different consecutive respectively, non dimensional cycles inare order sufficient time to investigate to steps obtain a time (non dimensionalized periodic stepsolution, sensitivity based by in c/v on ) present dt = 0.008, aerodynamic study 0.010, plotted 0.012, coefficients. curves respectively, are Four obtained consecutive order from to investigate cycles fourth are cycle. sufficient time to comparison obtain step sensitivity a periodic numerical based solution, on aerodynamic in present coefficients. study with Four plotted experimental consecutive curvescycles are measurements obtained are sufficient from are to given obtain fourth in cycle. Figure a periodic 6, comparison showing solution, a reasonably numerical in present good aerodynamic study agreement. plotted coefficients Hysteresis curves are with is obtained present experimental from in aerodynamic fourth measurements cycle. force are given coefficient comparison in Figure curves 6, numerical showing as well as aaerodynamic reasonably moment good coefficients agreement. with curve. experimental Hysteresis It also shown is measurements present that smaller in are aerodynamic time given steps in force have Figure coefficient little 6, effects showing curves on a asreasonably accuracy well good moment results, agreement. coefficient hence Hysteresis curve. middle is It is present also time shown in step that aerodynamic dt = smaller is selected time force steps to coefficient carry out all curves subsequent as well as pitch moment oscillation coefficient cases for curve. both It is also jet f shown that jet on smaller configurations. time steps have little effects on accuracy results, hence middle time step dt = is selected have little effects on accuracy results, hence middle time step dt = is selected to carry out all subsequent pitch oscillation cases for both jet-f jet-on configurations. to carry out all subsequent pitch oscillation cases for both jet f jet on configurations. (a) (a) Figure 6. Cont. Figure 6. Cont. Figure 6. Cont. (b) (b)

9 Energies 2016, 9, Energies 2016, 9, Energies 2016, 9, (c) (c) Figure Figure Comparison aerodynamic coefficient loops for for reduced frequency frequency κ = κ 0.077: = 0.077: Figure 6. Comparison aerodynamic coefficient loops for reduced frequency κ = 0.077: (a) Lift (a) Lift (a) Lift coefficient; (b) (b) Drag coefficient; (c) Moment coefficient. coefficient; (b) Drag coefficient; (c) Moment coefficient. In Figure In Figure 7, 7, calculated results both static oscillating motions at three at three reduced reduced frequencies In Figure 0.026, 7, 0.026, 0.052, calculated 0.052, results are are plotted both toger, static in oscillating order to to clearly motions exhibit exhibit at three effect reduced effect oscillating frequencies oscillating 0.026, motion motion 0.052, reduced reduced are plotted frequency toger, on on in airfoil order aerodynamic to clearly exhibit performance. effect It can It oscillating can be be found found motion that that reduced motion motion frequency airfoil airfoil on parameter airfoil parameter aerodynamic reduced reduced performance. frequency frequency have have Ita can a substantial substantial be foundimpact that impact on on motion field. airfoil field. oscillating motion leads to appearance hysteresis loops for all aerodynamic coefficients, oscillating parameter motion reduced leads to frequency appearance have a substantial hysteresis impact loops on for all aerodynamic field. coefficients, oscillating motion leads a larger toreduced appearance frequency leads hysteresis to larger loops opening for allin aerodynamic hysteresis coefficients, loops. highest alift a larger reduced frequency leads to a larger opening in hysteresis loops. highest larger lift reduced coefficient frequency obtained leads during to a larger oscillation opening is correspondingly hysteresis much loops. higher than highest its static lift counterpart. coefficient obtained coefficient obtained during oscillation is correspondingly much higher than its static counterpart. higher reduced frequency, higher highest lift coefficient. It is also shown that a higher during higher oscillation is correspondingly much higher than its static counterpart. higher reduced reduced reduced frequency frequency, can generate even higher larger drag highest moment lift coefficient. peaks at high It is angles also shown attack, that causing a higher frequency, reduced higher highest lift coefficient. It is also shown that a higher reduced frequency a greater frequency extreme can aerodynamic generate even load larger which drag could lead moment to structural peaks fatigue high or angles even worse attack, total causing can a greater generate even larger drag moment peaks at high angles attack, causing a greater extreme damage extreme structure. aerodynamic One purpose load which could present lead research to structural is to reduce fatigue this or kind even worse fluctuating total aerodynamic damage extreme aerodynamic load structure. which could load One by lead purpose implementing to structural a present fatigue co or research jet even on worse is airfoil to reduce suction total this damage surface kind fluctuating will structure. be One extreme presented purpose aerodynamic later. present load research by implementing is to reduce a this co kindjet on fluctuating airfoil extreme suction aerodynamic surface load will by be implementing presented later. a co- jet on airfoil suction surface will be presented later. (a) (a) Figure 7. Cont. Figure 7. Cont. Figure 7. Cont. (b) (b)

10 Energies 2016, 9, Energies 2016, 9, (c) Figure 7. Comparison aerodynamic coefficient loops for static oscillating motions under Figure 7. Comparison aerodynamic coefficient loops for static oscillating motions under three reduced frequencies: (a) Lift coefficient; (b) Drag coefficient; (c) Moment coefficient. three reduced frequencies: (a) Lift coefficient; (b) Drag coefficient; (c) Moment coefficient Simulation Simulation Validation Validation A airfoil airfoil based based on on NACA NACA airfoil airfoil was was tested tested by by Dano Dano et et al. al. [17] [17] in in University University Miami Miami ˆ24 wind wind tunnel tunnel facilities. facilities. airfoil airfoil was a was NACA a NACA 6415 with 6415 with injection injection suction suction located located at 7.5% at 7.5% 88.5% 88.5% chord, respectively. chord, respectively. injection injection suction suction slot heights slot heights were 0.65% were 0.65% 1.42% 1.42% chord. chord. In experiment, In experiment, is provided is provided by a separated by a separated high pressure high pressure source source for for injection injection a low a pressure low pressure vacuum vacuum sink sink for for suction. suction. injection injection suction suction conditions conditions were were independently independently controlled. controlled. A compressor compressor supplied supplied injection injection a vacuum vacuum pump pump generates generates necessary necessary low low pressure pressure for for suction. suction. Both Both mass mass rates rates in in injection injection suction suction slots slots were were measured measured using using orifice orifice mass mass meters. meters. More More experiment experiment details details can can be be found found in in [17]. [17]. free free stream stream Mach Mach number number was was 0.03, 0.03, chord-based chord based Reynolds Reynolds number number was was 195, ,000. leading leading edge edge trip trip was was used used to to achieve achieve full full turbulent turbulent boundary boundary layer layer to to be be consistent consistent with with CFD analysis. open slot case in experiment with momentum coefficient Cμ CFD analysis. open slot case in experiment with momentum coefficient C 0.08 is chosen to µ = 0.08 is chosen to validate validate present present solver solver for for simulation. simulation. Based Based on on grid-resolution grid resolution study study in Section in Section 4.1.1, 4.1.1, computational computational mesh for mesh for present present NACA 6415 NACA 6415 airfoil is airfoil generated is generated in a similar in a similar way according way according to to medium medium mesh mesh for for NREL NREL S809 S809 airfoil. airfoil. computed computed lift, drag lift, drag power power coefficients coefficients are are presented presented in in Figure Figures 8 8 Figure 9, 9, field field at AoA at AoA = 15 = is shown in Figure 10. present numerical results are compared with 15 is shown in Figure 10. present numerical results are compared with experimental experimental as well as as well CFD as results CFD results by Lefebvre by Lefebvre et al. [18], et showing al. [18], showing fairly good fairly agreements, good agreements, especially especially for power for coefficient. power coefficient. For lift coefficient, For lift good coefficient, agreement good is agreement achieved up is achieved to highest up to AoA highest 30, except AoA AoA 30, except 25 where AoA lift is underpredicted by present solver as well as Lefebvre et 25 where lift is underpredicted by present solver as well as Lefebvre al. [18]. et al. computed [18]. drag computed coefficient drag is coefficient underpredicted is underpredicted when AoA when is greater AoA than is greater 15. Among than 15. comparisons, Among comparisons, computed power computed coefficient power agrees coefficient best agrees with best experiment. with experiment. reason may reason be that may be total that pressure total pressure total temperature total temperature are integrated are integrated parameters parameters using mass using average, mass average, which is which easier to is easier predict to accurately predict accurately than than drag that drag is determined that is determined by skin friction by skin friction pressure pressure distribution. distribution. Overall, Overall, it is demonstrated it is demonstrated that that present solver present can solver predict can predict with a fairly with a good fairly precision, good precision, it is reliable it is reliable to be used to be for used for present present numerical numerical study study..

11 Energies 2016, 9, Energies 2016, 9, Energies 2016, 9, Energies 2016, 9, Figure 8. Comparison lift drag coefficients between experiment CFD simulations. Figure 8. Comparison lift drag coefficients between experiment CFD simulations. Figure 8. Comparison lift drag coefficients between experiment CFD simulations. Figure 8. Comparison lift drag coefficients between experiment CFD simulations. Figure 9. Comparison power coefficient between experiment CFD simulations. Figure 9. Comparison power coefficient between experiment CFD simulations. Figure 9. Comparison power coefficient between experiment CFD simulations. Figure 9. Comparison power coefficient between experiment CFD simulations. Figure 10. Streamlines Mach contour at AoA 15. Figure 10. Streamlines Mach contour at AoA 15. Figure 10. Streamlines Mach contour at AoA Inactive Cases Figure 10. Streamlines Mach contour at AoA Inactive Cases 4.3. Inactive co Cases jet control concept has a distinct feature with a jet channel on a large portion airfoil co- co suction jet surface control by a concept translation has has aa distinct slight feature rotation with with operation. a jet a jet channel channel This channel on on a large a large is necessary portion portion for airfoil airfoil co co suction suction jet jet surface concept. surface by control by ahowever, translation a concept translation has presence a slight distinct slight rotation rotation feature a channel operation. with operation. a jet inevitably This channel This channel channel on affects is a necessary large is necessary portion original for well designed for airfoil co suction aerodynamic jet concept. surface by performance However, a translation presence slight baseline rotation airfoil a channel operation. when inevitably This channel co affects jet is inactive, is necessary original since it well designed for co has changed aerodynamic jet concept. aerodynamic performance However, shape presence airfoil. baseline airfoil a channel effect when inevitably presence co affects jet a is channel inactive, original on since it well designed has changed aerodynamic aerodynamic performance shape airfoil. baseline airfoil effect when presence co jet a is channel inactive, on since it has changed aerodynamic shape airfoil. effect presence a channel on

12 Energies 2016, 9, co- jet concept. However, presence a channel inevitably affects original well-designed aerodynamic performance baseline airfoil when co- jet is inactive, since it has changed Energies aerodynamic 2016, 9, 429 shape airfoil. effect presence a channel on static characteristics airfoil has been investigated in a previous work [21], showing that channel will lead to a mild liftstatic decrease, characteristics earlier stall, airfoil drag has been increase. investigated In present in a previous study, work effect [21], showing a jet-f that channel channel on dynamic will lead characteristics to a mild lift decrease, is studiedearlier by simulating stall, drag sinusoidal increase. In oscillation present study, jet-f effect configuration a jetf channel same conditions dynamic as baseline. characteristics is studied by simulating sinusoidal oscillation at jet f configuration numerical results at are same shown conditions in Figure as 11, baseline. are compared with baseline results. For lift coefficient, numerical jet-f results casesare have shown an overall in Figure lower 11, value are than compared baseline, with especially baseline results. range For lower angles lift coefficient, attack during jet f down-stroke cases have an overall motion. lower In value upstroke than process, baseline, especially lift coefficient in is constantly range lower lower angles than attack baseline during till down stroke angle motion. attack about In 20, upstroke after process, which lift lift coefficient increases to is constantly lower than baseline till angle attack about 20, after which lift increases to a peak even larger than corresponding baseline, n experiences a rapid drop. This drastic a peak even larger than corresponding baseline, n experiences a rapid drop. This drastic variation consequently causes corresponding peaks in drag coefficient moment coefficient variation consequently causes corresponding peaks in drag coefficient moment coefficient hysteresis loops. That is to say, with jet-f channel, wind turbine airfoil will experience a more hysteresis loops. That is to say, with jet f channel, wind turbine airfoil will experience a severe extreme air load in terms drag moment. more severe extreme air load in terms drag moment. (a) (b) (c) Figure 11. Comparison aerodynamic coefficient loops for reduced frequency κ = 0.077: Figure 11. Comparison aerodynamic coefficient loops for reduced frequency κ = 0.077: (a) Lift (a) Lift coefficient; (b) Drag coefficient; (c) Moment coefficient. coefficient; (b) Drag coefficient; (c) Moment coefficient. In previous static study [21], force moment coefficient peaks in jet f case were not Inpresent, previous hence staticit study is expected [21], to be force reflection moment coefficient pitch oscillation peaks in effect jet-f on case. were not To present, make clear hence reason it is expected peak s to existence, be reflection fields pitch pressure oscillation coefficient effect distributions. To make six specific clear time reason locations are peak s plotted existence, in Figures 12 fields 13, respectively. pressure coefficient six time locations distributions are denoted six specific by time A, B, locations C, D, E, are F plotted in Figure in Figure 11a, which 12 cover Figure 13, range respectively. angles attack six time that see locations peak occurrence. For purpose comparison, corresponding baseline fields pressure coefficient distributions are also plotted in same scale. At time location A, pattern jet f case is similar to baseline, except that a small recirculating region exists behind injection slot surface. It can be seen from comparison pressure coefficient distribution in Figure 13a that

13 Energies 2016, 9, are denoted by A, B, C, D, E, F in Figure 11a, which cover range angles attack that see peak occurrence. For purpose comparison, corresponding baseline fields pressure coefficient distributions are also plotted in same scale. At time location A, pattern jet-f case is similar to baseline, except that a small recirculating region exists behind injection slot surface. It can be seen from comparison pressure coefficient distribution in Figure 13a that Energies 2016, 9, presence a channel results in a lower suction peak a lower suction for a large proportion presence channel surface, a channel causing results in lift a lower to decrease suction by peak a small a amount, lower suction although for a large local proportion suction is increased channel in small surface, recirculating causing region. lift to decrease n by small a small sting amount, vortex although continues local tosuction increase is in streamwise increased in size assmall angle recirculating attack region. increases. n At small time sting location vortex B, continues front vortex to increase develops in enough streamwise to connect size with as angle trailing attack edge vortex. increases. At At time time location location C, B, front front vortex vortex develops trailing edge enough vortex to start connect to combine with toger, trailing edge causing vortex. At corresponding time location surface C, pressure front vortex lower than baseline trailing as edge shown vortex in start comparison to combine toger, pressure causing coefficient corresponding distribution surface in Figure pressure 13c. lower At than time location baseline D, as two shown vortices in continue comparison to merge, pressure coefficient lift continues distribution to increase. Figure 13c. At time At location time E, location twod, vortices two completely vortices continue mergeto into merge, one larger vortex, lift continues causing to increase. lift toat reach time alocation maximum. E, By comparing two vortices Mach completely contours merge ininto Figure one 12i,j, larger it can vortex, be found causing that lift to reach velocity a maximum. on jet-f By suction comparing surface atmach location contours about in Figure 70%c from 12i,j, it can leading be found edgethat is much larger velocity than that on baseline, jet f causing suction much surface lower at pressure. location about difference 70%c from between leading pressures edge is much this larger particular than that part baseline, suction causing much lower pressure. difference between pressures this particular part suction surface is evidently reason that forces moment reach a peak. After formation a single surface is evidently reason that forces moment reach a peak. After formation a larger vortex, lift starts to decrease rapidly due to convection vortex into wake. At single larger vortex, lift starts to decrease rapidly due to convection vortex into time location F, jet-f field presents a more complicated multiple-vortex feature, lift wake. At time location F, jet f field presents a more complicated multiple vortex feature, is lower than baseline. refore, dynamic process vortex merging gives rise to presence lift is lower than baseline. refore, dynamic process vortex merging gives rise to peak which is a kind extreme aerodynamic load. presence peak which is a kind extreme aerodynamic load. (a) Time location A for jet f case (b) Time location A for baseline case (c) Time location B for jet f case (d) Time location B for baseline case Figure 12. Cont.

14 Energies 2016, 9, Energies 2016, 9, (e) Time location C for jet f case (f) Time location C for baseline case (g) Time location D for jet f case (h) Time location D for baseline case (i) Time location E for jet f case (j) Time location E for baseline case (k) Time location F for jet f case (l) Time location F for baseline case Figure 12. Comparison fields for six instantaneous angles attack: (a) Time location A for Figure 12. Comparison fields for six instantaneous angles attack: (a) Time location A jet f case; (b) Time location A for baseline case; (c) Time location B for jet f case; (d) Time location for jet-f case; (b) Time location A for baseline case; (c) Time location B for jet-f case; (d) Time B for baseline case; (e) Time location C for jet f case; (f) Time location C for baseline case; (g) Time location B for baseline case; (e) Time location C for jet-f case; (f) Time location C for baseline case; (g) Time location D for jet-f case; (h) Time location D for baseline case; (i) Time location E for jet-f case; (j) Time location E for baseline case; (k) Time location F for jet-f case; (l) Time location F for baseline case.

15 Energies 2016, 9, Energies 2016, location 9, 429 D for jet f case; (h) Time location D for baseline case; (i) Time location E for jet f case; (j) Time location E for baseline case; (k) Time location F for jet f case; (l) Time location F for baseline case. (a) (b) (c) (d) (e) (f) Figure 13. Comparisons pressure coefficient distributions for six instantaneous angles attack: Figure 13. Comparisons pressure coefficient distributions for six instantaneous angles attack: (a) Time location A; (b) Time location B; (c) Time location C; (d) Time location D; (e) Time location E; (a) Time location A; (b) Time location B; (c) Time location C; (d) Time location D; (e) Time location E; (f) Time location F. (f) Time location F Active Cases 4.4. Active Cases As main focus present study, dynamic characteristics S809 airfoil are investigated As main with focus three jet present momentum study, coefficients dynamic Cμ = 0.06, characteristics 0.09, Figure 14 S809 shows comparison airfoil are investigated with three jet momentum coefficients C µ = 0.06, 0.09, Figure 14 shows comparison unsteady aerodynamic characteristics between baseline cases with three momentum coefficients at Re = 1 ˆ overall lift coefficients cases are much higher than that

16 Energies 2016, 9, Energies 2016, 9, unsteady aerodynamic characteristics between baseline cases with three momentum coefficients baseline, while at Re = 1 drag moment overall lift coefficients cases cases are are much much lower higher than than that that baseline. baseline, It is obvious while fordrag moment cases that coefficients co- jet with cases a higher are much momentum lower than coefficient that has a greater baseline. ability It is obvious in lift for enhancement, cases that results co in ajet wider with a range higher momentum linear portion coefficient has a lift coefficient greater ability curves. in With increasing lift enhancement, momentum results coefficient in a from wider 0.06 range to 0.12, linear aerodynamic portion coefficient lift coefficient curves. With increasing momentum coefficient from 0.06 to 0.12, aerodynamic loops exhibit smaller hysteresis as expected. A stronger jet can suppress separation at higher coefficient loops exhibit smaller hysteresis as expected. A stronger jet can suppress separation at angles attack. It can be found in Figure 14a that for case with C µ = 0.06, at higher angles higher angles attack. It can be found in Figure 14a that for case with Cμ = 0.06, at higher attack larger than 21 during down-stroke, lift coefficient curve presents a -separation angles attack larger than 21 during down stroke, lift coefficient curve presents a separation characteristic, indicating that this Cμ level is not strong enough to suppress separation characteristic, indicating that this C µ level is not strong enough to suppress separation at angle attack greater than 21. However, for case with C µ = 0.12, lift coefficient curve does not present at angle attack greater than 21. However, for case with Cμ = 0.12, lift coefficient curve does not a noticeable present a noticeable stall feature, stall demonstrating feature, demonstrating that a stronger that a stronger jet can jet fully can fully control control dynamic dynamic stall. stall. (a) (b) (c) Figure 14. Comparison aerodynamic coefficient loops for reduced frequency κ = 0.077: Figure 14. Comparison aerodynamic coefficient loops for reduced frequency κ = 0.077: (a) Lift (a) Lift coefficient; (b) Drag coefficient; (c) Moment coefficient. coefficient; (b) Drag coefficient; (c) Moment coefficient. To show in detail compare abilities co jets with different Cμ levels in suppressing separation To show at in large detailangles compare attack, five abilities typical instantaneous co- jets with time locations different for C µ levels case in suppressing κ = separation are investigated largein angles terms attack, field fivecontours typical instantaneous streamlines time as well locations as surface forpressure casecoefficient κ = aredistributions, investigated as in shown terms in Figures field 15 contours 16. five streamlines time locations as well are as labeled surface in Figure pressure 14a. coefficient lift distributions, coefficients as shown time locations in Figure A, B, 15C are Figure highest 16. values fivefor time locations baseline, are labeled with Cμ in= Figure 0.06, 14a. with lift coefficients Cμ = 0.09, respectively. time locations angle A, B, C are attack highest time values location for D is baseline, 24, maximum with C µ = 0.06, investigated with C µ = 0.09, pitch respectively. oscillation motion. angle time attack location E is time position location that Dit is is 24, most likely maximum to occur a investigated separation pitch since oscillation it is locally motion. lowest time point location in down stroke E is position hysteresis thatloop. it is most All likely four to occur a separation since it is locally lowest point in down-stroke hysteresis loop. All four cases baseline, C µ = 0.06, 0.09, 0.12 are simultaneously investigated at each five time

17 Energies 2016, 9, Energies 2016, 9, locations. In Figure 15a, it is shown that baseline has a mild trailing edge separation, whereas cases cases baseline, withcμ all = 0.06, three 0.09, 0.12 C µ are levels simultaneously can completely investigated suppress at each separation. five time In locations. Figure 15b, In baseline Figure 15a, experiences it is shown athat massive baseline separation, has a mild trailing edge withseparation, C µ = 0.06 is whereas not strong enough cases to suppress with all it. With three stronger Cμ levels can withcompletely C µ = 0.09 suppress 0.12, this massive separation. separation In Figure can15b, still be completely baseline suppressed. experiences Ina Figure massive 15c, separation, a stronger separation with Cμ exists = in0.06 is baseline not strong case enough as well to as suppress it. case With with C stronger µ = 0.06 due towith Cμ large = 0.09 angle 0.12, attack this being massive separation But withcan a stronger still be completely with C suppressed. µ = 0.09 In 0.12, Figure separation 15c, a stronger still disappears. separation In exists Figure in 15d, baseline at highest case as angle well as attack case in with Cμ pitch = motion, 0.06 due to large angle attack being But with a stronger with Cμ = , separation baseline, with C µ = are all undergoing a separation, while with C µ = 0.12 still disappears. In Figure 15d, at highest angle attack in pitch motion, baseline, remains ability completely suppressing separation. At down-stroke time location E, with Cμ = are all undergoing a separation, while with Cμ = 0.12 remains ability field with C µ = 0.12 remains attached, demonstrating a perfect performance in suppressing completely suppressing separation. At down stroke time location E, field with dynamic stall. Cμ = 0.12 remains attached, demonstrating a perfect performance in suppressing dynamic stall. (a1) Baseline (a2) Cμ = 0.06 (a3) Cμ = 0.09 (a4) Cμ = 0.12 (a) Time location A, AoA = (upstroke) (b1) Baseline (b2) Cμ = 0.06 Figure 15. Cont. Figure 15. Cont.

18 Energies 2016, 9, Energies 2016, 9, (b3) Cμ = 0.09 (b4) Cμ = 0.12 (b) Time location B, AoA = (upstroke) (c1) Baseline (c2) Cμ = 0.06 (c3) Cμ = 0.09 (c4) Cμ = 0.12 (c) Time location C, AoA = (upstroke) (d1) Baseline (d2) Cμ = 0.06 Figure 15. Cont. Figure 15. Cont.

19 Energies 2016, 9, Energies 2016, 9, (d3) Cμ = 0.09 (d4) Cμ = 0.12 (d) Time location D, AoA = 24 (e1) Baseline (e2) Cμ = 0.06 (e3) Cμ = 0.09 (e4) Cμ = 0.12 (e) Time location E, AoA = (downstroke) Figure 15. Comparison fields at five instantaneous angles attack for reduced frequency Figure 15. Comparison fields at five instantaneous angles attack for reduced frequency κ = (a) Time location A, AoA = (upstroke); (a1) Baseline; (a2) Cμ = 0.06; (a3) Cμ = 0.09; κ = (a) Time location A, AoA = (upstroke); (a1) Baseline; (a2) Cµ = 0.06; (a3) Cµ = 0.09; (a4) Cμ = 0.12; (b) Time location B, AoA = (upstroke); (b1) Baseline; (b2) Cμ = 0.06; (b3) Cμ = 0.09; (a4) Cµ = 0.12; (b) Time location B, AoA = (upstroke); (b1) Baseline; (b2) Cµ = 0.06; (b3) Cµ = 0.09; (b4) Cμ = 0.12; (c) Time location C, AoA = (upstroke); (c1) Baseline; (c2) Cμ = 0.06; (c3) Cμ = (b4) 0.09; Cµ (c4) = 0.12; Cμ (c) = 0.12; Time (d) location Time C, location AoA = D, AoA (upstroke); = 24 ; (d1) (c1) Baseline; Baseline; (d2) (c2) Cμ Cµ = 0.06; = 0.06; (d3) (c3) Cμ Cµ = 0.09; = 0.09; (c4) (d4) Cµ Cμ = = 0.12; 0.12; (e) (d) Time Time location location E, AoA D, = AoA = (downstroke); 24 ; (d1) Baseline; (e1) Baseline; (d2) (e2) Cµ Cμ = 0.06; = 0.06; (d3) (e3) Cμ Cµ = = 0.09; 0.09; (d4) (e4) Cµ Cμ = 0.12; = (e) Time location E, AoA = (downstroke); (e1) Baseline; (e2) Cµ = 0.06; (e3) Cµ = 0.09; (e4) Cµ = Figure 16 presents corresponding pressure coefficient distributions for five time locations, Figure 16 showing presents that enclosed corresponding area is larger pressure for coefficient cases with distributions a higher jet for momentum five time coefficient, locations, showing representing that enclosed a higher area lift. is larger From for view cases with akutta Joukowski higher jet momentum orem coefficient, [35], a higher representing lift a higher corresponds lift. From to a larger viewcirculation, Kutta-Joukowski which is embodied orem in [35], how afar higher downstream lift corresponds location to a larger circulation, stagnation which point is. embodied in how far downstream location stagnation point is.

20 Energies 2016, 9, Energies 2016, 9, (a) (b) _C =0.12 _C =0.09 _C =0.06 Baseline NREL S809 airfoil pitching ( + baseline) Ma = Re = 1x10 6 =0.077 AoA = 24 o C p C p stagnation points x/c 0 (c) x/c (d) (e) Figure 16. Comparison pressure coefficient distributions at five instantaneous angles attack: Figure 16. Comparison pressure coefficient distributions at five instantaneous angles attack: (a) Time location A, AoA = (upstroke); (b) Time location B, AoA = (upstroke); (c) Time (a) Time location A, AoA = (upstroke); (b) Time location B, AoA = (upstroke); (c) Time location C, AoA = (upstroke); (d) Time location D, AoA = 24 ; (e) Time location E, AoA = location C, AoA = (upstroke); (d) Time location D, AoA = 24 ; (e) Time location E, AoA = (downstroke). (downstroke). time location D is chosen to show this interesting phenomenon in Figure 16d, which in enlarged time window location shows D isthat chosen to show case with this interesting highest phenomenon Cμ = 0.12 has in Figure most downstream 16d, which in stagnation enlarged point window while shows baseline that has case most with front stagnation highest C point. µ = 0.12 has most downstream stagnation One point purpose while baseline present study has is most to find front out stagnation performance point. in reducing fluctuating One purpose extreme loads, present especially study is to pitching find out drag force performance moment. Table 3 inpresents reducing fluctuating amplitudes extreme aerodynamic loads, especially hysteresis pitching loops for drag all cases force with three moment. different Table jet 3momentum presents amplitudes coefficients, as well aerodynamic as variation hysteresis quantities loops foramplitudes all cases with three cases different relative jet to momentum those

21 Energies 2016, 9, coefficients, as well as variation quantities amplitudes cases relative to those baseline. It is shown that amplitude lift coefficient can be significantly increased by implementing, while amplitudes drag moment coefficients can be significantly reduced. enhanced lift is beneficial for power generation, while reduction drag moment is beneficial to structural fatigue problem. amplitude lift can be enhanced by up to 51.14% in case with C µ = 0.12, amplitude drag can be reduced by as much as 78.72% with C µ = 0.09, amplitude moment can be reduced by 76.57% with C µ = 0.12, as shown in Table 3. It should also be noted that in terms drag moment reduction, with C µ = have an equivalent ability, meaning that a stronger jet with C µ larger than 0.09 cannot necessarily result in a better performance in furr reducing amplitudes drag moment coefficients, although it may bring a furr enhancement in lift. amount moment amplitude reduction only increases from 76.15% to 76.57% when C µ varies from 0.09 to 0.12, amount drag amplitude reduction even decreases from 78.72% to 78.01%. Overall, study exhibits a rar encouraging desired result: concept can greatly enhance lift, reduce fluctuating drag moment, leading to a larger output wind energy, while reducing potential structural fatigue damage. Table 3. Comparison amplitudes force moment coefficients (κ = 0.077) Energy Consumption Analysis Coefficient Baseline C µ = 0.06 C µ = 0.09 C µ = 0.12 C L,min C L,max C L,amp C L,amp 24.62%Ò 36.35%Ò 51.14%Ò C D,min C D,max C D,amp C D,amp 69.49%Ó 78.72%Ó 78.01%Ó C M,min s C M,max C M,amp C M,amp 40.49%Ó 76.15%Ó 76.57%Ó consideration energy cost a control method is important in all-round assessment method s practicability economy. As an active control method, implementation needs a certain amount energy input to perform its effect on field. Figure 17 gives comparison power coefficient hysteresis loops for all three C µ levels, showing that more power input is required to pressurize jet for a higher C µ level jet. In attached regime, required power input decreases as angle attack increases. reason is, from view airfoil aerodynamics, pressure in vicinity injection slot which is near leading edge becomes lower when angle attack increases, namely suction peak becomes gradually higher with increasing angle attack before separates. low pressure will benefit power consumption, because pump will perform less work to drive jet. On or h, pressure around suction slot which is near trailing edge is relatively higher due to pressure recovery process on airfoil suction surface. This higher pressure also makes it easier for pump to suck from suction slot. combination injection suction takes full advantage pressure difference between injection suction slots, hence results in relatively lower energy consumption. At very high angles attack, energy input increases with increasing angle attack, regardless is attached or separated. For separated at high angles attack in case with C µ = 0.06, energy input reaches a peak during upstroke process, while keeps at a nearly constant high level during down-stroke process. Even so, cycle

22 Energies 2016, 9, averaged value energy input case with C µ = 0.06 is still much lower than that cases with higher C µ levels, which will be seen in Table 4. Energies 2016, 9, Figure Comparison power coefficients between differentcμ C µ levels. Table Table Averaged Averaged aerodynamic power coefficients in inone oscillationcycle cycle (κ (κ = = 0.077) ). Coefficient Baseline Cμ = 0.06 Cμ = 0.09 Cμ = 0.12 Coefficient CL,ave Baseline C µ = C µ = C µ = 0.12 C CD,ave L,ave C CM,ave D,ave C M,ave Pc,ave P c,ave analysis energy consumption performance present two dimensional implementation analysisis given energy here based consumption an average performance estimation, more present comprehensive two-dimensional computation implementation analysis are isleft given to be here conducted based on in an furr average three dimensional estimation, wind more turbine comprehensive rotor simulation computation work. Table analysis 4 gives are left time averaged to be conducted aerodynamic in furr three-dimensional power coefficients, wind which turbine are rotor calculated simulation from one work. oscillation cycle. It is shown that lift power increase with Cμ, while drag moment decrease Table 4 gives time-averaged aerodynamic power coefficients, which are calculated from one with Cμ. reduction drag with increasing Cμ is attributed to contribution jet reaction force. oscillation cycle. It is shown that lift power increase with C µ, while drag moment decrease Indeed, energy consumed by pump is partly injected into main energizes with C main µ. reduction drag with increasing C as well as boundary layer, resulting µ is attributed to contribution jet reaction force. in a reduced drag. Indeed, energy consumed by pump is partly injected into main energizes main For simplicity, assume that free stream direction is perpendicular to rotor plane as well as boundary layer, resulting in a reduced drag. with a magnitude V 2 (V is local coming seen by sectional airfoil, which is equal For simplicity, assume that free stream direction is perpendicular to rotor plane with to m/s = m/s). Assume that controlled S809 airfoil is located at a position that a magnitude V rotates at a speed 8 {? 2 (V equal to 8 is local coming seen by sectional airfoil, which is equal to free stream velocity. Hence, a decomposed component airfoil lift by multiplying ˆ 340 m/s = total lift m/s). with Assume 2 2 will that contribute controlled to energy S809 generation. airfoil is located Assume at that a position wind that rotates at a speed equal to free stream velocity. Hence, a decomposed component airfoil lift by turbine efficiency energy generation from torque is η e = n coefficient rotor power multiplying total lift with? 2{2 will contribute to energy generation. Assume that wind generation P e by 2 D airfoil with unit span can be calculated by: turbine efficiency energy generation from torque is η e = n coefficient rotor power 2 generation P e by 2-D airfoil LVwith unit0.5 span Vcan c(1) be calculated 2 2CL, ave Vby: 2 1 P e, ave e e ec 3 L, ave (5) q V 0.5 V c(1) 2 P e,ave LV η e 0.5ρ 8V 2? 8cp1q 2{2CL,ave V 8 {? 2 power loss for q 8 pumping V 8 can be calculated 0.5ρ 8 in Vpercentage 3 η e 1 8cp1q baseline rotor 2 η ec L,ave (5) power by power loss for pumping can be calculated in P percentage baseline rotor power by c, ave P pumping, ave 100% (6) Pe P, ave c,ave, baseline P pumping,ave ˆ 100% (6) power gain through increased CL,ave can P e,ave,baseline be calculated by power gain through increased C L V L,ave can be calculated by CL, ave Pgain, ave e / Pe, avebaseline, 100% 100% (7) P q V C gain,ave L V η e {P L, ave, baseline q 8 V e,ave,baseline ˆ 100% C L,ave ˆ 100% (7) 8 C L,ave,baseline Table 5 shows power performance analyses for different Cμ levels. It is shown that more power can be gained by using larger jet strength. However, it should be noted that increase net

23 Energies 2016, 9, Table 5 shows power performance analyses for different C µ levels. It is shown that more power can be gained by using larger jet strength. However, it should be noted that increase net power gain from C µ = 0.09 to C µ = 0.12 is much lower than that from C µ = 0.06 to C µ = 0.09, implying that a too strong jet will not necessarily have a better performance, re is an optimal jet strength choice. Table 5. Power performance analysis for different C µ levels (κ = 0.077). Cases P pumping P gain P gain P pumping C µ = % 54.53% 39.29% C µ = % 82.18% 57.16% C µ = % 98.37% 62.18% 5. Conclusions Dynamic stall control using a co- jet is systematically investigated by numerically solving unsteady Reynolds-Averaged Navier-Stokes equations. solver is validated by comparing numerical results with a baseline experiment a experiment. jet-f configuration is simulated to assess negative effect jet channel existence. dynamic stall control performance is investigated by implementing co- jets at three momentum coefficients on pitching airfoil comparing results with baseline. detailed instantaneous field contours streamlines, surface pressure coefficient distributions are examined analyzed. energy consumption applying a co- jet is computed analyzed to assess concept. conclusions obtained are as follows: (1) solver can predict well aerodynamic characteristics baseline airfoil as well as airfoil, including static characteristics dynamic pitch oscillation characteristics on basis grid-resolution time-step resolution studies. (2) When co- jet is inactive, jet channel has a negative effect on airfoil dynamic aerodynamic performance. lift is reduced, while drag moment increase. In particular, drag moment hysteresis loops exhibit a higher local peak which, as a form fluctuating extreme aerodynamic loads on structure, can cause potential structural fatigue damage. (3) A co- jet can effectively suppress dynamic stall, especially with a higher momentum coefficient level which can fully control separation. amplitude lift increases it is beneficial to energy output. amplitudes drag moment are significantly reduced, showing an attractive performance in reducing fluctuating aerodynamic loads on wind turbine structure. dynamic stall caused by unsteady in due to atmospheric turbulence or wakes form or turbines in a wind farm can lead to generation unsteady torque at shaft. By applying concept, it is expected that unsteady torque at shaft can be greatly mitigated. (4) co- jet concept makes use advantageous pressure difference between injection suction slots, requires a minimum energy input to pump jet. A positive net power gain is obtained by approximate two-dimensional energy consumption analysis. It is demonstrated that method is an applicable economic approach in dynamic stall control. Numerical results present study show a powerful ability for to suppress dynamic stall, oretically proving it s promising application for wind turbines. However, it should be noted that implementation a will give rise to some concerns, including added weight, complexity spanwise slots, control recirculating jets potential extra maintenance. extra maintenance is an important issue for long-term cost analysis, potential situation in which co- jet is closed due to failure device should be taken into account. From studies shown in this paper, co- jet channel has a moderate negative effect on aerodynamic performance when device doesn t work. In view long-term benefit from application, it is

24 Energies 2016, 9, worthwhile to make efforts to reduce maintenance keep carrying this research furr. In fact, fast development material science manufacturing technology have made great contributions in reducing rotor weight, allowing more complicated designs enhancing structural reliability. In practice, high-pressure low-pressure cavities could be connected by a pump inside blade or by pipes linked to special pressurization equipment integrated in stationary part wind turbine system. For large scale wind turbines, chord length sectional airfoil thickness near blade root are relatively large in velocity is relatively low, making it feasible to install a pump inside blade. slots channel could be designed as a continuous whole or be discretely distributed on blade surface. Three-dimensional simulations would be helpful to underst more about phenomena mechanism concept, which is our future work plan. Acknowledgments: This work was supported by National Natural Science Foundation China (Grant Nos ), Natural Science Foundation Shaanxi Province (Grant No. 2016JM1015), Fundamental Research Funds for Central Universities China, Innovation Foundation Shenzhen government. Thank Ge-Cheng Zha Alexis Lefebvre in University Miami for providing Fortran code for mass calculation which is adapted incorporated into present solver. authors would also like to thank High Performance Computer Center Northwestern Polytechnical University for computation support. Author Contributions: He-Yong Xu performed a majority numerical simulations, analyzed data, wrote paper; Chen-Liang Qiao performed simulations for baseline validation; Zheng-Yin Ye analyzed data jet-f configuration, provided constructive instructions in process preparing paper. Conflicts Interest: authors declare no conflict interest. References 1. Tchakoua, P.; Wamkeue, R.; Ouhrouche, M.; Slaoui-Hasnaoui, F.; Tameghe, T.A.; Ekemb, G. Wind turbine condition monitoring: State---art review, new trends, future challenges. Energies 2014, 7, World Wind Energy Association. Half Year Report Available online: webimages/wwea_half_year_report_2014.pdf (accessed on 6 August 2015). 3. Mo, W.; Li, D.; Wang, X.; Zhong, C. Aeroelastic coupling analysis flexible blade a wind turbine. Energy 2015, 89, [CrossRef] 4. Sanaye, S.; Hassanzadeh, A. Multi-objective optimization airfoil shape for efficiency improvement noise reduction in small wind turbines. J. Renew. Sustain. Energy 2014, 6, [CrossRef] 5. Lee, J.W.; Kim, J.K.; Shin, H.K.; Bang, H.J. Active load control for wind turbine blades using trailing edge flap. Wind Struct. 2013, 16, [CrossRef] 6. Macquart, T.; Maheri, A.; Busawon, K. Microtab dynamic modeling for wind turbine blade load rejection. Renew. Energy 2014, 64, [CrossRef] 7. Johnson, S.J.; Baker, J.P.; van Dam, C.P.; Berg, D. An overview active load control techniques for wind turbines with an emphasis on microtabs. Wind Energy 2010, 13, [CrossRef] 8. Gao, L.Y.; Zhang, H.; Liu, Y.Q.; Han, S. Effects vortex generators on a blunt trailing-edge airfoil for wind turbines. Renew. Energy 2015, 76, [CrossRef] 9. Wang, G.N.; Lewalle, J.; Glauser, M.; Walczak, J. Investigation benefits unsteady blowing actuation on a 2D wind turbine blade. J. Turbul. 2013, 14, [CrossRef] 10. Müller-Vahl, H.F.; Strangfeld, C.; Nayeri, C.; Paschereit, C.; Greenblatt, D. Thick Airfoil Deep Dynamic Stall Its Control. Available online: (accessed on 22 December 2015). 11. Tongchitpakdee, C.; Benjanirat, S.; Sankar, L.N. Numerical Studies Effects Active Passive Circulation Enhancement Concepts on Wind Turbine Performance. J. Sol. Energy Eng. 2006, 128, [CrossRef] 12. Yen, J.; Ahmed, N.A. Enhancing vertical axis wind turbine by dynamic stall control using syntic jets. J. Wind Eng. Ind. Aerodyn. 2013, 114, [CrossRef] 13. Greenblatt, D.; Ben-Harav, A.; Mueller-Vahl, H. Dynamic stall control on a vertical-axis wind turbine using plasma actuators. AIAA J. 2014, 52, [CrossRef] 14. Zha, G.C.; Carroll, B.; Paxton, C.; Conley, C.A.; Wells, A. High performance airfoil with co- jet control. AIAA J. 2007, 45, [CrossRef]

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