Development and application of synthetic turbulence methods for computational fluid dynamics

Synthetic turbulence methods are an important tool for the study of turbulent flows. They allow to reduce the computational effort of numerical simulations of fluid flows and thereby, improve the quality of simulations of complex flow problems. Contributing to the field of turbulence research, this thesis proposes two new methods of simulating turbulent flows using synthetic turbulence. The methods developed in this work were tested for two scenarios of turbulent flow simulations. The first scenario was the numerical simulation of turbulent flow around a wing. For this simulation a synthetic turbulence method was developed, which generated an initial 3D turbulent wind field to initialise the simulation. Using a complex numerical setup it was possible to simulate the interaction of the synthetic turbulence field, representing atmospheric boundary layer (ABL) turbulence, with a wing on a relatively large range of scales. This method allows to simulate the influence of ABL turbulence on the aerodynamics of the wing, for example, at large angles of attack. In the second scenario a new method was developed to generate synthetic turbulence as inflow boundary condition for Large-Eddy Simulation (LES). A new method to generate anisotropy in the turbulence field was introduced, which allowed to prescribe 1D statistics of the turbulent flow independently. This method can be used, for example, for feeding synthetic turbulence into the interface between the Reynolds-Averaged Navier Stokes (RANS) and LES part of a hybrid RANS/LES. For the first scenario, the generated turbulence was tested in a simple LES of decaying turbulence where it was found that the input statistics for the turbulence generator were reproduced very well. It was also shown that the statistical properties were maintained reasonably well during the simulation with the exception of fluctuations observed in the cross-correlations. In order to investigate the quality of the turbulence generator further, the generated turbulence field was compared to data from an LES of the ABL. It was found that the synthetic turbulence was not able to represent the coherent structures present in a convective boundary layer, but apart from that the turbulence statistics from the synthetic turbulence and LES of the ABL agreed very well. After studying the properties of the synthetic turbulence generator in detail, a synthetic turbulence field was generated for the initialisation of the simulation of the flow around a wing. In a complex setup of two different grid types (Cartesian and unstructured) and two different turbulence model types (LES and RANS), the development of the turbulence in the different numerical environments was studied. It was found that the change in grid characteristics led to a stronger dissipation of turbulence on the unstructured grid. No significant effect on the turbulence could be found when the turbulence model switched from LES to RANS mode, most likely due to the short time the turbulence was exposed to the RANS model. For the second scenario, a new approach for generating anisotropic turbulence was developed. An extensive analysis of the statistics of the generated turbulence was carried out and the results showed very good agreement with the reference data from a Direct Numerical Simulation (DNS). The generated turbulence then served as inflow boundary condition in an LES of a channel flow. A strong influence of the statistical properties of the synthetic turbulence on the behaviour of the turbulence in the channel was found. Comparison to two established synthetic turbulence methods showed a similar performance of the new approach, which at the same time caused much less computational costs and allowed better control of the statistical parameters of the synthetic turbulence

Evaluation of fast atmospheric dispersion models in a regular street network

The need to balance computational speed and simulation accuracy is a key challenge in designing atmospheric dispersion models that can be used in scenarios where near real-time hazard predictions are needed. This challenge is aggravated in cities, where models need to have some degree of building-awareness, alongside the ability to capture effects of dominant urban flow processes. We use a combination of high-resolution large-eddy simulation (LES) and wind-tunnel data of flow and dispersion in an idealised, equal-height urban canopy to highlight important dispersion processes and evaluate how these are reproduced by representatives of the most prevalent modelling approaches: (i) a Gaussian plume model, (ii) a Lagrangian stochastic model and (iii) street-network dispersion models. Concentration data from the LES, validated against the wind-tunnel data, were averaged over the volumes of streets in order to provide a high-fidelity reference suitable for evaluating the different models on the same footing. For the particular combination of forcing wind direction and source location studied here, the strongest deviations from the LES reference were associated with mean over-predictions of concentrations by approximately a factor of 2 and with a relative scatter larger than a factor of 4 of the mean, corresponding to cases where the mean plume centreline also deviated significantly from the LES. This was linked to low accuracy of the underlying flow models/parameters that resulted in a misrepresentation of pollutant channelling along streets and of the uneven plume branching observed in intersections. The agreement of model predictions with the LES (which explicitly resolves the turbulent flow and dispersion processes) greatly improved by increasing the accuracy of building-induced modifications of the driving flow field. When provided with a limited set of representative velocity parameters, the comparatively simple street-network models performed equally well or better compared to the Lagrangian model run on full 3D wind fields. The study showed that street-network models capture the dominant building-induced dispersion processes in the canopy layer through parametrisations of horizontal advection and vertical exchange processes at scales of practical interest. At the same time, computational costs and computing times associated with the network approach are ideally suited for emergency-response applications

An anisotropic synthetic turbulence method for Large-Eddy Simulation

The method for generating anisotropic synthetic turbulence by Auerswald and Bange (2015) is extended to account for the integral length scales in y - and z -direction. This extension leads to more realistic tur- bulent structures. The method reproduces the given turbulence statistics very well and allows to set a number of turbulence parameters independently. In four Large-Eddy Simulations of a channel flow the synthetic turbulence is used as inflow boundary condition. The performance of the synthetic turbulence is tested and compared to the Direct Numerical Simulation (DNS) results by Moser et al. (1999). In these simulations the synthetic turbulence shows good performance in recovering realistic turbulence down- stream in the channel. The skin-friction coefficient converges to the level of the DNS. The profiles of the Reynolds stresses are very similar in the LES and the DNS except for the profiles of R + ww where large deviations occur

Large-Eddy Simulations of realistic atmospheric turbulence with the DLR-TAU-code initialized by in situ airborne measurements

In this paper the numerical simulation of a turbulent flow in the atmospheric boundary layer (ABL) with a Large-Eddy Simulation (LES)-model is discussed. The results of this work are intended to be used for the numerical simulation of turbulent flows around an airfoil. To simulate the characteristics of the ABL flow and its influence on the airfoil realistically the flow upstream of the airfoil has to be turbulent with statistical properties that are comparable to those found in atmospheric measurements. To achieve this goal, a method to generate synthetic turbulent wind fields was used to initialize an LES model which is able to simulate the turbulent flow around an airfoil. For the initial turbulent wind field to contain realistic statistics of atmospheric turbulence, data taken with the Helipod system are used. The Helipod is a helicopter-borne measurement probe that is able to take high-resolution measurements of temperature, wind vector and humidity. The statistical properties that are used as input parameters for the turbulence generator are the spectral energy, the correlation matrix and the variances of the three components of the wind vector. The LES model used in this project is the flow solver TAU developed by the German Aerospace Center (DLR). TAU is a compressible computational fluid dynamics (CFDs) tool that is able to compute the flow around obstacles (e.g. parts of aircrafts or even whole aircrafts) on an unstructured grid. Calculations with TAU can be performed in Reynolds-Averaged Navier–Stokes-, LES- or Detached Eddy Simulation-mode using different sub-grid scale models

Simulation of Wing Stall

Simulation capabilities for low-speed aircraft stall prediction are important for determining the limits of safe aircraft operations during design processes. The simulations are extremely demanding in terms of physical models involved, overall computation effort, and the needed efforts for validation. The present paper describes coordinated, fundamental research into new simulation methodologies for wing stall that also include the effects of atmospheric gusts. The research is carried out by the DFG funded Research Unit FOR 1066 composed of German Universities and the German Aerospace Center, DLR. The research Unit investigates advanced models of turbulence, advanced physics-based gust models, and new numerical approaches for gust simulation. These modeling and computational activities are supplemented by an unique validation experiment, that aims at providing stall data on a high-lift wing with well defined, generic distortions of the onset flow