To evaluate novel turbine designs, the wind energy sector extensively depends on computational fluid dynamics (CFD). To use CFD in the design optimization process, where lower-fidelity approaches such as blade element momentum (BEM) are more popular, new tools to increase the accuracy must be developed as the latest wind turbines are larger and the aerodynamics and structural dynamics become more complex. In the present study, a new concurrent aerodynamic shape optimization approach towards multidisciplinary design optimization (MDO) that uses a Reynolds-averaged Navier–Stokes solver in conjunction with a numerical optimization methodology is introduced. A multidisciplinary design optimization tool called DAFoam is used for the NREL phase VI turbine as a baseline geometry. Aerodynamic design optimizations in terms of five different schemes, namely, cross-sectional shape, pitch angle, twist, chord length, and dihedral optimization are conducted. Pointwise, a commercial mesh generator is used to create the numerical meshes. As the adjoint approach is strongly reliant on the mesh quality, up to 17.8 million mesh cells were employed during the mesh convergence and result validation processes, whereas 2.65 million mesh cells were used throughout the design optimization due to the computational cost. The Sparse Nonlinear OPTimizer (SNOPT) is used for the optimization process in the adjoint solver. The torque in the tangential direction is the optimization’s merit function and excellent results are achieved, which shows the promising prospect of applying this approach for transient MDO. This work represents the first attempt to implement DAFoam for wind turbine aerodynamic design optimization.

This study presents an aerostructural optimization process for wind turbine blades aimed at enhancing the turbine’s performance. The optimization framework integrates DAFoam as the computational fluid dynamics (CFD) solver, TACS as the finite element method (FEM) solver, Mphys for fluid–structure coupling, and SNOPT as the optimizer within the OpenMDAO framework. The objective is to simultaneously increase the torque generated by the wind turbine while decreasing the mass of the blade, thereby improving its efficiency. The design variables in this optimization process are the blade shape and panel thickness. The aerodynamic objective function is torque, a key performance indicator for wind turbine efficiency. The structural objective function is the blade mass, as reducing mass is essential to minimize material and manufacturing costs. The optimization process utilizes the integrated capabilities of DAFoam, TACS, Mphys, and SNOPT to iteratively evaluate and modify the blade shape and panel thickness. The OpenMDAO framework facilitates seamless communication between the solvers and the optimizer, ensuring a well-coordinated, efficient optimization process. The results of the optimization show a 6.78% increase in torque, which indicates a significant improvement in the wind turbine’s energy production capacity. Additionally, a 4.22% decrease in blade mass demonstrates a successful reduction in material usage without compromising structural integrity. These findings highlight the potential of the proposed aerostructural optimization process to enhance the performance and cost-effectiveness of wind turbine blades, contributing to the advancement of sustainable energy solutions. This work represents the first attempt to implement DAFoam for wind turbine aerostructural design optimization.

This paper presents two novel automated optimization approaches. The first one proposes a framework to optimize wind turbine blades by integrating multidisciplinary 3D parametric modeling, a physics-based optimization scheme, the Inverse Blade Element Momentum (IBEM) method, and 3D Reynolds-averaged Navier–Stokes (RANS) simulation; the second method introduces a framework combining 3D parametric modeling and an integrated goal-driven optimization together with a 4D Unsteady Reynolds-averaged Navier–Stokes (URANS) solver. In the first approach, the optimization toolbox operates concurrently with the other software packages through scripts. The automated optimization process modifies the parametric model of the blade by decreasing the twist angle and increasing the local angle of attack (AoA) across the blade at locations with lower than maximum 3D lift/drag ratio until a maximum mean lift/drag ratio for the whole blade is found. This process exploits the 3D stall delay, which is often ignored in the regular 2D BEM approach. The second approach focuses on the shape optimization of individual cross-sections where the shape near the trailing edge is adjusted to achieve high power output, using a goal-driven optimization toolbox verified by 4D URANS Computational Fluid Dynamics (CFD) simulation for the whole rotor. The results obtained from the case study indicate that (1) the 4D URANS whole rotor simulation in the second approach generates more accurate results than the 3D RANS single blade simulation with periodic boundary conditions; (2) the second approach of the framework can automatically produce the blade geometry that satisfies the optimization objective, while the first approach is less desirable as the 3D stall delay is not prominent enough to be fruitfully exploited for this particular case study.

With increased interest in renewable energy, the power capacity of wind turbines is constantly increasing, which leads to increased rotor sizes. With ever larger rotor diameters, the complex and non-linear fluid-structure interaction (FSI) effects on wind turbine aerodynamic performances become significant, which can be fully studied using hi-fidelity 2-way FSI simulation. In this study, a two-way FSI model is developed and implemented in Openfoam to investigate the FSI effects on the NREL Phase VI wind turbine. The fully structured multiblock (MB) mesh method is used for the fluid and solid domains to achieve good accuracy. A coupling method based on the ALE is developed to ensure rotation and deformation can happen simultaneously and smoothly. The simulation results show that hi-fidelity CFD (Computational Fluid Dynamics) and CSD (Computational Structural Dynamics) -based 2-way FSI simulation provides high accurate results for wind turbine simulation and multi-disciplinary design optimization (MDO).

Today, growth in renewable energy is increasing, and wind energy is one of the key renewable energy sources which is helping to reduce carbon emissions and build a more sustainable world. Developed countries and worldwide organizations are investing in technology and industrial application development. However, extensive experiments using wind turbines are expensive, and numerical simulations are a cheaper alternative for advanced analysis of wind turbines. The aerodynamic properties of wind turbines can be analyzed and optimized using CFD tools. Currently, there is a general lack of available high-fidelity analysis for the wind turbine design community. This study aims to fill this urgent gap. In this paper, an arbitrary hybrid turbulence model (AHTM) was implemented in the open-source code OpenFOAM and compared with the traditional URANS model using the NREL Phase VI wind turbine as a benchmark case. It was found that the AHTM model gives more accurate results than the traditional URANS model. Furthermore, the results of the VLES and URANS models can be improved by improving the mesh quality for usage of higher-order schemes and taking into consideration aeroelastic properties of the wind turbine, which will pave the way for high-fidelity concurrent multidisciplinary design optimization of wind turbines.

During this research, aerodynamic shape optimization is conducted on the Ahmed body with the drag coefficient as the objective function and the ramp shape as the design variable, while aero-structural optimization is conducted on NACA 0012 to reduce the drag coefficient for the aerodynamic performance with the shape as the design variable while reducing structural mass with the thickness of the panels as the design variables. This is accomplished through a gradient-based optimization process and coupled finite element and computational fluid dynamics (CFD) solvers under fluid–structure interaction (FSI). In this study, DAFoam (Discrete Adjoint with OpenFOAM for High-fidelity Multidisciplinary Design Optimization) and TACS (Toolkit for the Analysis of Composite Structures) are integrated to optimize the aero-structural design of an airfoil concurrently under the FSI condition, with TACS and DAFoam as coupled structural and CFD solvers integrated with a gradient-based adjoint optimization solver. One-way coupling between the fluid and structural solvers for the aero-structural interaction is adopted by using Mphys, a package that standardizes high-fidelity multiphysics problems in OpenMDAO. At the end of the paper, we compare and discuss our findings in the context of existing research, specifically highlighting previous results on the aerodynamic and aero-structural optimization of wind turbine blades.