Identification of large coherent structures in supersonic axisymmetric wakes

Direct numerical simulation data of supersonic axisymmetric wakes are analysed for the existence of large coherent structures. Wakes at Ma ¼ 2:46 are considered with results being presented for cases at Reynolds numbers ReD ¼ 30; 000 and 100,000. Criteria for identification of coherent structures in freeshear flows found in the literature are compiled and discussed, and the role of compressibility is addressed. In particular, the ability and reliability of visualisation techniques intended for incompressible shear-flows to educe meaningful structures in supersonic wakes is scrutinised. It is shown that some of these methods retain their usefulness for identification of vortical structures as long as the swirling rate is larger than the local compression and expansion rates in the flow field. As a measure for the validity of this condition in a given flow the ‘vortex compressibility parameter’ is proposed which is derived here. Best ‘visibility’ of coherent structures is achieved by employing visualisation techniques and proper orthogonal decomposition in combination with the introduction of artificial perturbations (forcing of the wake). The existence of both helical and longitudinal structures in the shear layer and of hairpin-like structures in the developing wake is demonstrated. In addition, elongated tubes of streamwise vorticity are observed to emanate from the region of recirculating flo

Interaction of the filter and spatial discretisation operators for Large-Eddy Simulation using the Approximate Deconvolution Model

The Approximate Deconvolution Model (ADM) for Large–Eddy Simulation is an approach for the computation of turbulent flows. The main idea of ADM is to approximate the unfiltered data in the filtered Navier–Stokes equations by deconvolution of filtered values. This is achieved via repeated filtering. Thereby problems may arise for cases where the order of the spatial discretisation scheme is too low or lower than the order of the filter operation. The interaction of the discretisation and the filtering was investigated for one–dimensional forced Burgers turbulence. For this study, both the order of the filter operator and the order of the spatial discretisation of the derivatives were varied independently. It was found that the use of ADM with low–order discretisation schemes can not be recommended

An adaptive local deconvolution method for general curvilinear coordinate systems

Turbulence modeling and the numerical discretization of the Navier–Stokes equations are strongly coupled in large-eddy simulations (LES). The truncation error of common approximations for the convective terms can outweigh the effect of a physically sound subgrid-scale (SGS) model, which generally operates on a range of scales that is marginally resolved by any discretization scheme. This mutual interference can have large and generally unpredictable effects on the accuracy of the solution. On the other hand, one can exploit this link by developing discretization methods from subgrid-scale models, or vice versa. Approaches where the SGS model and the numerical discretization scheme are fully merged are called implicit LES (ILES) methods

The emergence of supersonic flow on wind turbines

The future generation of wind turbines will be characterised by longer and more flexible blades. These large wind turbines are facing higher Reynolds numbers, as a consequence of longer chord lengths and increased relative wind speeds. Higher tip speeds, however, also result in an increased Mach number. Although the maximum tip speed in steady design conditions may remain (well) below the critical value, the presence of turbulence, wind gusts, blade deflections, etc. in combination with the flow acceleration over the airfoil surface, may cause a significant increase in the velocity perceived over the blade surface. We have evaluated the operational conditions of the IEA 15MW reference turbine using OpenFAST in normal design and off-design conditions to demonstrate that, if unabated, near-future wind turbines will be at risk of suffering from local supersonic flow. The driving factor is identified to be inflow turbulence, however, the tip airfoil is also of major importance. Local supersonic flow conditions may lead to severe lifetime degradation. Wind Energ

High accuracy DNS and LES of high Reynolds number, supersonic base flows and passive control of the near wake

Supersonic axisymmetric base flows are prototypical for flows behind projectiles and missiles. For these flows, drag reduction can be achieved by means of passive control of the near wake. Thereby, large (turbulent) coherent structures play a dominant role. The objective of the present investigationis to elucidate if and how successful passive flow control techniques modify these structures. To this end, first Direct Numerical Simulations (DNS) for a Reynolds number of ReD = 100,000 and Mach number of Ma = 2.46 were performed using a high-order accurate and highly parallelized research code which was developed at the University of Arizona. Thereby, roughly 52 million grid points were employed. The DNS data serve to visualize typical structures of the unsteady flow field and to verify that the use of less computational costly RANS/LES methods is applicable for this flow. Two of these methods, the Flow Simulation Methodology (FSM) and Detached Eddy Simulations (DES), were then employed to investigate the supersonic base flow at ReD = 3.3 106 and Ma = 2.46 using between 460,000 and seven million grid points. For the DES, the commercial CFD-code Cobalt was employed. This unstructured grid solver allowed then to perform simulations with boat-tailing. The obtained mean flow data is compared to available experimental result

Performance of Fixed-wing Airborne Wind Energy Systems: A Parametric Study

Wind Energ

Drivers for optimum sizing of wind turbines for offshore wind farms

Large-scale exploitation of offshore wind energy is deemed essential to provide its expected share to electricity needs of the future. To achieve the same, turbine and farm-level optimizations play a significant role. Over the past few years, the growth in the size of turbines has massively contributed to the reduction in costs. However, growing turbine sizes come with challenges in rotor design, turbine installation, supply chain, etc. It is, therefore, important to understand how to size wind turbines when minimizing the levelized cost of electricity (LCoE) of an offshore wind farm. Hence, this study looks at how the rated power and rotor diameter of a turbine affect various turbine and farm-level metrics and uses this information in order to identify the key design drivers and how their impact changes with setup. A multi-disciplinary design optimization and analysis (MDAO) framework is used to perform the analysis. The framework uses low-fidelity models that capture the core dependencies of the outputs on the design variables while also including the trade-offs between various disciplines of the offshore wind farm. The framework is used, not to estimate the LCoE or the optimum turbine size accurately, but to provide insights into various design drivers and trends. A baseline case, for a typical setup in the North Sea, is defined where LCoE is minimized for a given farm power and area constraint with the International Energy Agency 15 MW reference turbine as a starting point. It is found that the global optimum design, for this baseline case, is a turbine with a rated power of 16 MW and a rotor diameter of 236 m. This is already close to the state-of-the-art designs observed in the industry and close enough to the starting design to justify the applied scaling. A sensitivity study is also performed that identifies the design drivers and quantifies the impact of model uncertainties, technology/cost developments, varying farm design conditions, and different farm constraints on the optimum turbine design. To give an example, certain scenarios, like a change in the wind regime or the removal of farm power constraint, result in a significant shift in the scale of the optimum design and/or the specific power of the optimum design. Redesigning the turbine for these scenarios is found to result in an LCoE benefit of the order of 1 %–2 % over the already optimized baseline. The work presented shows how a simplified approach can be applied to a complex turbine sizing problem, which can also be extended to metrics beyond LCoE. It also gives insights into designers, project developers, and policy makers as to how their decision may impact the optimum turbine scale.Wind Energ