Computational Simulation of the Turbulent Flow around an Airfoil using a spectral/hp Method

The precise calculation of loads in turbulent flow is still problematic for most Computational fluid dynamics (CFD) approaches. The spectral/hp approach allows to solve the incompressible NavierStokes equation with spectral accuracy on unstructured grids by means of Direct Numerical simulation (DNS) or Large Eddy Simulation (LES). Here we present first results we obtained from DNS compared to LES and measurements at a low Reynolds number

Minimum information about a protein affinity reagent (MIAPAR)

This is a proposal developed within the community as an important first step in formalizing standards in reporting the production and properties of protein binding reagents, such as antibodies, developed and sold for the identification and detection of specific proteins present in biological samples. It defines a checklist of required information, intended for use by producers of affinity reagents, qualitycontrol laboratories, users and databases. We envision that both commercial and freely available affinity reagents, as well as published studies using these reagents, could include a MIAPAR-compliant document describing the product’s properties with every available binding partner. This would enable the user or reader to make a fully informed evaluation of the validity of conclusions drawn using this reagent

Reconstruction of turbulence properties for stochastical turbulence modeling

The correct modeling of turbulent and transient flow is still a major task for computational fluid dynamics. This is even more a topic concerning the CFD-simulations on wind turbines, which face already highly turbulent in flow conditions. Thus motivated the improvement of stochastic methods of turbulence modeling is the scope of this work. Stochastic turbulence model rely on an estimation of the statistical distribution of the flow properties at a certain point or time. E.g. Bakosi et. al.1 have proposed a model using the probability density functions (PDFs) of the flow properties on an unstructured grid. The method however relies on the knowledge of the PDFs in the flow on the grid. Here we will present a method to gain such PDFs of the flow. We performed a 3D DNS simulation using spectral/hp method on an fx79-w151a airfoil at a Reynolds number of Re=5000. In the wake of the airfoil an inhomogeneous turbulent field evolved. Within this field a time series of the flow properties has been gathered at certain points. As an example the data of the time series at one point has been analyzed using a multi-point correlation method on incremental statistics to gain the Kramers-Moyal coeffcients.2 Using these coeffcients it is possible to reconstruct the time series at the point itself to gain a PDF function artificially. The resulting PDFs did not completely match the statistical properties of the original points. The main reason were to high values of the high order statistical moments and the short time series, that served as a base. However the results were surprisingly good, reproducing the main shapes of the PDFs, even though the underlying function for the reconstruction was a Langevin equation using only Gaussian white noise in the diffusion. Thus further progress is to be expected in the method

Optimize Rotating Wind Energy Rotor Blades Using the Adjoint Approach

Wind energy rotor blades are highly complex structures, both combining a large aerodynamic efficiency and a robust structure for lifetimes up to 25 years and more. Current research deals with smart rotor blades, improved for turbulent wind fields, less maintenance and low wind sites. In this work, an optimization tool for rotor blades using bend-twist-coupling is developed and tested. The adjoint approach allows computation of gradients based on the flow field at comparably low cost. A suitable projection method from the large design space of one gradient per numerical grid cell to a suitable design space for rotor blades is derived. The adjoint solver in OpenFOAM is extended for external flow. As novelty, we included rotation via the multiple reference frame method, both for the flow and the adjoint field. This optimization tool is tested for the NREL Phase VI turbine, optimizing the thrust by twisting of various outer parts between 20–50% of the blade length

Insight into Rotational Effects on a Wind Turbine Blade Using Navier–Stokes Computations

Rotational effects are known to influence severely the aerodynamic performance of the inboard region of rotor blades. The underlying physical mechanisms are however far from being well understood. The present work addresses this problem using Reynolds averaged Navier–Stokes computations and experimental results of the MEXICO (Model Experiments in Controlled Conditions) rotor. Four axisymmetric inflow cases with wind speeds ranging from pre-stall to post-stall conditions are computed and compared with pressure and particle image velocimetry (PIV) experimental data, obtaining, in general, consistent results. At low angles of attack, the aerodynamic behavior of all of the studied blade sections resembles the one from the corresponding 2D airfoils. However, at high angles of attack, rotational effects lead to stall delay and/or lift enhancement at inboard positions. Such effects are shown to occur only in the presence of significant radial flows. Interestingly, the way in which rotational effects influence the aerodynamics of the MEXICO blades differs qualitatively in certain aspects from the descriptions found in the literature about this topic. The presented results provide new insights that are useful for the development of advanced and physically-sound correction models

Optimization of airfoils using the adjoint approach and the influence of adjoint turbulent viscosity

The adjoint approach in gradient-based optimization combined with computational fluid dynamics is commonly applied in various engineering fields. In this work, the gradients are used for the design of a two-dimensional airfoil shape, where the aim is a change in lift and drag coefficient, respectively, to a given target value. The optimizations use the unconstrained quasi-Newton method with an approximation of the Hessian. The flow field is computed with a finite-volume solver where the continuous adjoint approach is implemented. A common assumption in this approach is the use of the same turbulent viscosity in the adjoint diffusion term as for the primal flow field. The effect of this so-called “frozen turbulence” assumption is compared to the results using adjoints to the Spalart–Allmaras turbulence model. The comparison is done at a Reynolds number of Re=2×106 for two different airfoils at different angles of attack

FOXES: Farm Optimization and eXtended yield Evaluation Software

Testing publication workflow pypi.ymlIf you use this software, please cite our article in the Journal of Open Source Software