Simulations of a model wind turbine at various tip-speed-ratios were carried out using Tenasi, a node-centered, finite volume unstructured flow solver. The simulations included the tunnel walls, tower, nacelle, hub and the blades. The effect of temporal convergence on the predicted thrust and power coefficients is evaluated and guidelines for best practices are established. The results presented here are for tip-speed-ratios of 3, 6 and 10, with 6 being the design point. All simulations were carried out at a freestream velocity of 10 m s À1 with an incoming boundary layer present and the wind turbine RPM was varied to achieve the desired tip-speed-ratio. The performance of three turbulence models is evaluated. The models include a one-equation model (Spalart-Allmaras), a two-equation model (Menter SST) and the DES version of the Menter SST. Turbine performance as well as wake data at various locations is compared to experiment. All the turbulence models performed well in terms of predicting power and thrust coefficients. The DES model was significantly better than the other two turbulence models for predicting the mean and fluctuating components of the velocity in the wake.

No abstract

The increase in both computational capability (CPU speed, memory capacity, etc) and flow solver/grid generation sophistication over the last two decades has allowed for computational simulations of so-called "real-world" problems to become more commonplace. While not meant to suggest that new developments in computational science and simulation have reached their limit, it seems fair to say that the analogy of the computer being used as a computational or numerical wind tunnel has been, at least to some degree, realized. With regard to aero-propulsion applications, the computational simulation of engine components (inlets, nozzles, compressors, turbines, etc.) has been quite successful, especially over the past 10 -15 years. The topic of this paper is a qualitative demonstration of the scope that should logically follow component simulations, namely, that of simulating combined components on a system (or sub-system) level basis. While hypothetical in the sense that the actual hardware combination examined here does not exist, the results illustrate the interaction of the two components in the title and the importance of having the capability to conduct such system-level studies. Nomenclature AIP= aerodynamic interface plane A 0 /A c = ratio of free-stream flow area to inlet face capture area BWB = blended-wing-body CFL = Courant-Freidrich-Lax number

In this paper, air flow around a model wind turbine and the NREL offshore 5-MW baseline wind turbine is simulated using different rotor modeling techniques/methodologies. The actuator line (AL) method of modeling the rotor is compared with the fully resolved rotor simulation. The aerodynamic forces for the AL method are computed using an open source code, FAST, from NREL. An in-house code, Tenasi, is used to carry out the CFD simulations. Validation of the computational methodology is carried out by comparing the simulation results with the experimental data for the model wind turbine. Since the NREL offshore 5-MW baseline wind turbine is notional, experimental data is not available for validation. The simulation results are verified using the results from other studies. Nomenclature = projection width r = distance of the actuator (blade) point from the control volume F  = aerodynamic force computed using FAST f  = projected force on a control volume

Simulations of a model wind turbine at various tip-speed-ratios are carried out using Tenasi, a node-centered, finite volume unstructured flow solver. The model wind turbine was designed using the NREL S826 airfoils as cross sections and detailed experimental data is available for a variety of flow conditions. The simulations included the tunnel walls as the blockage (based on tower area and the swept area of the rotor) was 12%. The results presented here are for tip-speed-ratios of 3, 6 and 10, with 6 being the design point. All simulations were carried out at a freestream velocity of 10 m/s and the wind turbine RPM was varied to achieve the desired tip-speed-ratio. Results are presented for various one-and two-equation turbulence models. Turbine performance as well as wake data at various locations is compared to experiment. The overall agreement between the computation and experiment is good.