The accurate prediction of the laminar‐turbulence transition process is fundamental in predicting the aerodynamic performance of wind turbine profiles. Fully turbulent flow simulations have been shown to over‐predict the aerodynamic performance and thereby negatively impacting the design of airfoils in flow regimes where the possible presence of laminar flow could be exploited to improve the performance of wind turbine rotors. Correlation‐based transition modelling offers a fully computational fluid dynamics compatible approach, where the model integrates completely with the existing turbulence model, allows for the prediction of various transition mechanisms, is applicable to three‐dimensional flows and compatible to adjoint‐based design optimization frameworks. The present paper addresses several modifications necessary for a robust transition model and investigates the accuracy of the model for a wide range of angles of attack and Reynolds numbers, which are necessary for a thorough validation of the correlation‐based transition model for wind turbine profiles. The transition model was employed to predict the transition locations; and an assessment of the various transition mechanisms, Reynolds number effects, sectional characteristics and aerodynamic performance for the NLF(1)‐0416 and S809 airfoils is presented with comparisons to experimental data and numerical solutions. Copyright © 2013 John Wiley & Sons, Ltd.

In this paper the γ−Re θ transition model is combined with the k−ωSST turbulence model to predict the transition region for a laminar-turbulent boundary layer. A preconditioned Jameson-Schmidt-Turkel (JST) scheme is used to accurately solve the laminar-turbulent flow. Two subsonic airfoils at various angles of attack are solved to demonstrate the capability of the transition model. Adjoint equations for the transition and turbulence models are derived and implemented into the design framework. The effect of adding the transition and turbulence adjoint costates to the design framework is studied for the optimization of the NLF(1)-0416 airfoil. This adjoint-based optimization procedure is employed to optimize the NACA0012 airfoil to postpone the onset of transition and extend the natural laminar region of the transitional flow for minimizing the total drag and maintaining the lift or maximizing the lift-to-drag ratio. The obtained results demonstrate the ability of the developed optimization framework to design new NLF airfoils.

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Genetic Algorithms (GAs) have initiated a new scheme for solution of the complicated optimization problems. Here a genetic algorithm is developed for optimization of the convergent-divergent nozzles. First, a popular numerical method is chosen for solving the fluid dynamic problem. Then, optimization criterion and evaluation parameters (such as maximum thrust force) are determined. After introduction of the simple genetic algorithm, parameters of this method such as crossover probability, mutation probability and population size in each generation are used for optimization of the algorithm. After independent verification of the computational fluid dynamic scheme and the genetic algorithm, these two are integrated, and using different values for the above parameters, performance of the optimization algorithm for shape optimization of a nozzle is studied. Finally an optimum range of GA parameters are found, and are used to find optimum shape by less than 0.1% exhaustive search CPU time.