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The demand in solving complex turbulent fluid flows has been growing rapidly in the automotive industry for the last decade as engineers strive to design better vehicles to improve drag coefficients, noise levels and drivability. This paper presents the implementation of an arbitrary hybrid turbulence modeling (AHTM) approach in OpenFOAM for the efficient simulation of common automotive aerodynamics with unsteady turbulent separated flows such as the Kelvin–Helmholtz effect, which can also be used as an efficient part of aerodynamic design optimization (ADO) tools. This AHTM approach is based on the concept of Very Large Eddy Simulation (VLES), which can arbitrarily combine RANS, URANS, LES and DNS turbulence models in a single flow field depending on the local mesh refinement. As a result, the design engineer can take advantage of this unique and highly flexible approach to tailor his grid according to his design and resolution requirements in different areas of the flow field over the car body without sacrificing accuracy and efficiency at the same time. This paper presents the details of the implementation and careful validation of the AHTM method using the standard benchmark case of the Ahmed body, in comparison with some other existing models, such as RANS, URANS, DES and LES, which shows VLES to be the most accurate among the five examined. Furthermore, the results of this study demonstrate that the AHTM approach has the flexibility, efficiency and accuracy to be integrated with ADO tools for engineering design in the automotive industry. The approach can also be used for the detailed study of highly complex turbulent phenomena such as the Kelvin–Helmholtz instability commonly found in automotive aerodynamics. Currently, the AHTM implementation is being integrated with the DAFoam for gradient-based multi-point ADO using an efficient adjoint solver based on a Sparse Nonlinear optimizer (SNOPT).

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.

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).

Abstract. The aim of this study is to contribute towards the development of an open source MDO (multidisciplinary design optimization) platform DAFoam (https://github.com/DAFoam) in general and develop, implement, and integrate various technologies for wind turbine MDO for the energy community in particular, and to implement hi-fidelity concurrent multi-disciplinary the aerodynamic design optimization in terms of five different schemes as well as to contribute to the development of the opensource MDO software, DAFoam. 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 like blade element momentum (BEM) are more popular, but new tools to increase the accuracy must be developed as the latest wind turbines are larger and 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 baseline geometry to conduct extensive aerodynamic design optimizations such as cross-sectional shape, pitch angle, twist, chord length, and dihedral optimization. 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 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.