. The present study aims to asses the aerodynamic performance of Diffuser Augmented Wind Turbine (DAWT) using high lift generating airfoils in the construction of the shroud/diffuser. The study is a Computational Fluid Dynamics (CFD) analysis which is carried out using Reynolds Averaged Navier-Stokes (RANS) simulations. The ﬂow across the duct and rotor blades, which are modeled as an actuator disk (AD), is analyzed. Various High-Lift generating airfoils and their geometries were taken5 into consideration and analyzed with additional geometric modiﬁcations, such as a ﬂange, to improve ﬂow through the AD and increase the augmentation factor. 1 Introduction Wind energy is establishing itself as one of the largest sources of renewable energy in the world. In 2018, wind energy produc- tion reached approximately 600 GW and wind power accounted for almost 6% of the global electricity demand. Wind energy is 10 the most promising, effective and dependable source of renewable energy. Recent predictions of global warming and reaching the point of no return calls for the entire global community to shift focus into developing effective renewable energy systems. The abundance of wind all across the globe has caused researchers to focus on a system can increase power output without a penalty for the size of the wind turbine. While large wind turbines are placed where the wind topology is optimum, smaller wind turbines are locally built to supply power to meet the demands. 15 A bare wind turbine modeled after an idealized actuator disk can extract only 59.3% of the kinetic energy of the ﬂow. This is known as the Betz-Joukouwski limit as deﬁned by the Betz law of wind turbine performance. This limit however, can be overcome by some additional ’augmentation’ devices. The idea of a Shrouded or Diffuser Augmented Wind Turbine (DAWT) was ﬁrst explored by Lilley and Rainbird [7], where they described power augmentation of small shrouded wind turbines as far back as 1956. Since then, numerous studies have been conducted to investigate and optimize the power augmentation factor for 20 wind turbines through various means. This paper aims to investigate the effects of high-lift generating airfoils on a DAWT at moderate Reynolds numbers. A high-lift airfoil improves the aerodynamic efﬁciency (C L/CD) at low speeds by having a high lift coefﬁcient with minimum drag penalties. The thickness has very little effect in determing the maximum lift coefﬁcient of 1 Figure 1. Schematic of the geometry and its orientation to relative velocity U 1 the airfoils. By adding a diffuser the wake of the turbine blades is allowed to rapidly expand causing a drop in pressure, which in turn leads to an increase in the mass ﬂow rate of the incoming ﬂow. This allows for the power augmentaion ratio beyond the Betz-Joukouwski limit. Through wind tunnel testing Igra found that power coefﬁcient could be improved by 80% of that of a conventional wind turbine just by placing a diffuser over it [8]. Abe and Ohya, varied with Diffuser Open Angle by adding a ﬂange around the diffuser exit. Flanged Diffusers show that the additional geometric modiﬁcations to the shroud can cause a5 larger wake expansion due to vortices generated at the tips of the ﬂange, as a result of which an enhanced low pressure region is generated in the vicinity [4], which in turn increases the mass ﬂow rate. The loading coefﬁcient of such Flanged Diffusers is much less, compared to that of a bare wind turbine. In a DAWT, maximum energy can be drawn from a high thrust coefﬁcient actuator disk. The thrust can be increased by increasing the expansion ratio. However, this cannot be increased indeﬁnitely as it would cause boundary layer ﬂow separation. However, the boundary layer is re-energized as by adding a ﬂange. Thus there 10 is an optimum conﬁguration for which the velocity through the actuator disk can be maximized. [4,5] The turbine blades of the Diffuser Augmented Wind Turbine in this present study are modeled as an actuator disk. A pressure drop is induced across this disk which simulates the wake ﬂow for the wind turbine for a speciﬁc coefﬁcent of thrust. The entire ﬂow ﬁeld can be identiﬁed as a one dimensional ﬂow ﬁeld. The separation effects and ﬂow losses from the tips are assumed to be negligible. In this documentation, a basic form of a genetic algorithm is used on a pool of various high lift generating 15 airfoils. The airfoils are categorized as per their family and tests against different parameters such as area ratio, Flange Open 2 Angle, and position of the ﬂange opening along the airfoil chord length are successively performed to ﬁnd the best performing airfoils in each class of airfoils. This process was inspired from the work of Dighe et al, who employed a similar technique. [2] ICEM CFD®, a module of ANSYS®and a commercial Computational Fluid Dynamics (CFD) tool, has been used for meshing as it offers more control over the meshing process. ANSYS Fluent®, a well known commercial RANS solver, has been used for the computational study of the various shape parameters of the models.5 2 Actuator Disk Modeling The purpose of the rotor is to extract kinetic energy from the velocity that impinges on the blades of the rotor. This causes a reduction in velocity of the across the blades. This change in kinetic energy invariably causes a thrust force in the direction of the incoming ﬂow. There is also a frictional drag component that is created as result of the ﬂow over the blades. The resultant torque created due to the rotational motion of the blades also contributes to the change in the kinetic energy of the ﬂow. Thus 10 wind turbine forces are operated balancing the thrust force, torque of the blades and kinetic energy of the ﬂow. The Actuator disk (AD) method is a tool used to model the forces and moments of the rotor system of the turbine blades. The basic idea of an actuator disk is to replace the rotor blades with a permeable disc of equivalent area. The actuator disk uses the mass and momentum conservation principles to balance the applied forces as compared to the axial and tangential momentum equations that balance the applied forces on the real rotor blades. Thus the actuator disk maybe used to conveniently model and assist the 15 calculation of rotor aerodynamics. [10] The Actuator Disk (AD) exerts a constant thrust T Aper unit surface. The coefﬁcient is given by [3]: CTAD=TA 1 1U2Sa where,is the ﬂuid density and U is the freestream velocity and S ais the surface area of the actuator disk. The pressure drop across the AD ( p) is input as a constant during the simulations and the force TA=Saxp. Thus a constant coefﬁcient of thrust can be maintained across the the AD. The average AD velocity can be found by integrating the freestream velocity in the X direction over the deﬁned surface area of the AD: UA VG=1 SaZ@U @xdS Using the above results we can deﬁne a power coefﬁcient for the duct geometry with an AD of surface area S a: CP=P 1 1U2Sa=UA VG UCTAD 3 Figure 2. The genepool of high-lift generating airfoils Figure 3. Meshes at the leading edge ofthe airfoil and at the AD 4 3 Numerical Approach 3.1 Governing equations To properly model the viscous ﬂows over the various diffuser conﬁgurations at moderate Reynolds numbers, the Navier–Stokes equations are selected in Cartesian coordinate system. The turbulence model used is k- !SST which is expressed as partial differential equations. The k- !SST, which was developed by Menter [9] is a robust model for turbulence growth. The k- ! 5 SST blends the use of k- !for near wall ﬂow while using k- for the free-stream ﬂow. This makes the model more accurate and reliable yet computationally more feasible as compared to Large Eddy Simulations (LES) or Direct Numerical Simulation (DNS) which are computationally heavy. Although the models are know to often report higher values of turbulence than normal, the discrepancies are known and documented and these errors are small in order. The governing equations are as follows[9]: 10 Kinematic Eddy Viscosity: T=a1k max(a1!;SF 2) Turbulence Kinetic Energy: @k @t+Uj@k @xj=Pk *k!+@ @xj (+kT) +@k @xj Speciﬁc Dissipation Rate: @! @t+Uj@! @xj= S2 !2+@ @xj (+wT) +@! @xj 3.2 Grid Studies A grid validation and a grid analysis study was conducted to verify the accuracy of mesh and results.Three meshes were used with different number of nodes and elements. All the meshes had Selig 1210 as the airfoil and were simulated under similar 15 conditions with a inlet velocity of 6m/s. The ﬁrst mesh was a very coarse mesh with roughly 4627 nodes and 4776 elements in total and took 129s to converge. As expected, the mesh gave a very poor results with a velocity of only 7.826434m/s at the AD. The second mesh was a ﬁne mesh with a total of roughly 174246 nodes and 175291 elements. This mesh took a about ten minutes for the solution to converge. This mesh gave a better and more accurate result with a velocity of 8.678735m/s at the AD. The third mesh was an even ﬁner 20 mesh which had a total of 456031 nodes and 457512 mesh elements. This mesh took about 22 minutes for the solution to converge. This mesh gave a velocity of 8.7638m/s at the AD. The ﬁnest mesh differed by a 0.98% from the medium quality mesh. Thus the medium quality mesh with 174246 nodes and 175291 elements was chosen at it was accurate with an added advantage of reduced computational time and power. 5 Figure 4. Comparison of the results: a. Coarse b. Medium c. Fine Figure 5. Tabulated Results 4