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Ice accretion poses substantial safety hazards for the manned and unmanned aviation industries. Its study is essential for icing events risk assessment and for the development of efficient ice protection systems. The existing ice accretion measurement techniques—casting, molding, and laser-scanning—are time-consuming, sometimes cumbersome to use, and highly expensive, while hand tracing is inexpensive, but has lower accuracy and time-consuming post-processing. This work presents two low-cost, fast, and easy-to-use measurement techniques for 2D ice accretion profiles. Both employ algorithms of automatic ice shape detection, one based on unmediated image-processing, another based on the processing of manual ice tracings. The techniques are applied to ice accretion experiments conducted in an icing wind tunnel at low Reynolds numbers, and their results are validated against ice thickness caliper measurements. A comparison of the results shows that both techniques accurately measure the leading-edge ice thickness and the 2D shape of the ice accretion profiles. One technique is faster, with higher measurement accuracy, but produces interrupted-line 2D ice profiles and requires good lighting conditions, while the other generates continuous-line 2D profiles and has no application restriction, but it is slower, with lower accuracy. A discussion is conducted, aiming to help one determine the best applications for each ice accretion measurement technique presented. [ABSTRACT FROM AUTHOR]

TheWeather Research and Forecasting (WRF) model offers a multitude of physics parameterizations to study and analyze the different atmospheric processes and dynamics that are observed in the Earth's atmosphere. However, the suitability of a WRF model setup is known to be highly sensitive to the type of weather phenomena and the type and combination of physics parameterizations. A multi-event sensitivity analysis is conducted to identify general trends and suitable WRF physics setups for three extreme weather events identified to be potentially harmful for the operation and maintenance of wind farms located in the Belgian offshore concession zone. The events considered are Storm Ciara on 10 February 2020, a low-pressure system on 24 December 2020, and a trough passage on 27 June 2020. A total of 12 WRF simulations per event are performed to study the effect of the update interval of lateral boundary conditions and different combinations of physics parameterizations (planetary boundary layer, PBL; cumulus; and microphysics). Specifically, the update interval of ERA5 lateral boundary conditions is varied between hourly and 3-hourly. Physics parameterizations are varied between three PBL schemes (Mellor-Yamada-Nakanishi-Niino, MYNN; scale-aware Shin-Hong; and scaleaware Zhang), four cumulus schemes (Kain-Fritsch, Grell-Dévényi, scale-aware Grell-Freitas, and multi-scale Kain-Fritsch), and three microphysics schemes (WRF Single-Moment five-class scheme, WSM5; Thompson; and Morrison). The simulated wind direction and wind speed are compared qualitatively and quantitatively to operational supervisory control and data acquisition (SCADA) data. Overall, a definitive best-case setup common to all three events is not identified in this study. For wind direction and wind speed, the best-case setups are identified to employ scale-aware PBL schemes. These are most often driven by hourly update intervals of lateral boundary conditions as opposed to 3-hourly update intervals, although it is only in the case of Storm Ciara that significant differences are observed. Scale-aware cumulus schemes are identified to produce better results when combined with scale-aware PBL schemes, specifically for Storm Ciara and the trough passage cases. However, for the low-pressure-system case this trend is not observed. No clear trend in utilizing higher-order microphysics parameterization considering the combinations of WRF setups in this study is found in all cases. Overall, the combination of PBL, cumulus, and microphysics schemes is found to be highly sensitive to the type of extreme weather event. Qualitatively, precipitation fields are found to be highly sensitive to model setup and the type of weather phenomena. [ABSTRACT FROM AUTHOR]

During the last three decades, rapid growth of wind energy has led to questions regarding the possible impacts of wind farms on local weather and microclimates. Physically, the increased turbulence due to the wind turbine operation affects the mixing processes, may slightly disturb the pressure and temperature distributions downstream of wind farms and may have an impact on natural ecosystems such as the famous mastic tree population located on the island of Chios in the North Aegean Sea. This study explores the wind farms and their wake effects downstream with a particular focus on the effect on the southern part of the island where the mastic trees cultivation is located. The analysis is carried out with the use of the commercial CFD code ANSYS Fluent. Steady state computations of full 3D Navier–Stokes equations, using the k-ε turbulence closure scheme are carried out. The development of the multiple wake effects of the wind farms and their propagation downstream is examined under low and high turbulence intensities. Results clearly indicate that for both test cases there is no impact to the local microclimate and to the mastic Tree population. [ABSTRACT FROM AUTHOR]

Two-way feedback occurs between offshore wind and waves. However, the influence of the waves on the wind profile remains understudied, in particular the momentum transfer between the sea surface and the atmosphere. Previous studies showed that for swell waves it is possible to have increasing wind speeds in case of aligned wind–wave directions. However, the opposite is valid for opposed wind–wave directions, where a decrease in wind velocity is observed. Up to now, this behavior has not been included in most numerical models due to the lack of an appropriate parameterization of the resulting effective roughness length. Using an extensive data set of offshore measurements in the North Sea and the Atlantic Ocean, we show that the wave roughness length affecting the wind is indeed dependent on the alignment between the wind and wave directions. Moreover, we propose a new roughness length parameterization, taking into account the dependence on alignment, consisting of an enhanced roughness length for increasing misalignment. Using this new roughness length parameterization in numerical models might facilitate a better representation of offshore wind, which is relevant to many applications including offshore wind energy and climate modeling. [ABSTRACT FROM AUTHOR]

An effective structural health monitoring system fully exploits the flexibility offered by the 3D printing process by integrating a smart structural health monitoring technology inside the 3D-printed components. The system relies on the propagation of pressure waves with constant propagation speed through circular capillaries embedded in the structure. The nature of these waves seems to be determinant for the accuracy of the crack localization system. To achieve a better physical understanding of the nature of the propagating waves through the capillaries, computational fluid dynamics simulations are performed and compared to experimental results obtained with a self-built test setup. The presence of propagating shock waves is observed in the simulations and experiments, as well as a complex reflection mechanism around the leak location. Shock waves show the characteristic of not propagating at a constant velocity. This property complicates the actual localization system. To solve this, the constant velocity assumption should be replaced with the effective velocity evolution to increase the localization accuracy. The amplitude of the shock wave is attenuated with propagating distance, which proves that the effect of friction plays an important role and can, in turn, influence the localization system. [ABSTRACT FROM AUTHOR]

The phenomenon of meandering of the wind-turbine wake comprises the motion of the wake as a whole in both horizontal and vertical directions as it is advected downstream. The oscillatory motion of the wake is a crucial factor in wind farms, because it increases the fatigue loads, and, in particular, the yaw loads on downstream turbines. To address this phenomenon, experimental investigations are carried out in a wind-tunnel flow simulating an atmospheric boundary layer with the Coriolis effect neglected. A 3×3 scaled wind farm composed of three-bladed rotating wind-turbine models is subject to a neutral boundary layer over a slightly-rough surface, i.e. corresponding to offshore conditions. Particle-image-velocimetry measurements are performed in a horizontal plane at hub height in the wakes of the three wind turbines occupying the wind-farm centreline. These measurements allow determination of the wake centrelines, with spectral analysis indicating the characteristic wavelength of the wake-meandering phenomenon. In addition, measurements with hot-wire anemometry are performed along a vertical line in the wakes of the same wind turbines, with both techniques revealing the presence of wake meandering behind all three turbines. The spectral analysis performed with the spatial and temporal signals obtained from these two measurement techniques indicates a Strouhal number of ≈0.20-0.22 based on the characteristic wake-meandering frequency, the rotor diameter and the flow speed at hub height. [ABSTRACT FROM AUTHOR]

Two problems arise when estimating numerically wind energy resources, namely: The low resolution of global-scale atmospheric models and the scarcity of meteorological observations to be used as boundary conditions for smaller-scale models. Downscaling techniques were developed to overcome these issues. These methods consist of using global-scale model output as boundary conditions of smaller-scale models. In this research a downscaling tool to refine NCEP/NCAR Reanalysis data using WAsP is presented. The downscaling technique proposed consists of extrapolating the wind climate at a given point using meteorological observations from another point by means of the WAsP model. Then, using time-marching NCEP/NCAR Reanalysis wind velocity values, on-line refined profiles of wind velocity and direction can be obtained. In order to assess the accuracy of the described tool, data of two episodes of 48 hours are downscaled and compared to meteorological observations at two different climates. A sensitivity analysis is performed in order to assess the effect that atmospheric stability and terrain roughness, among others, exert on the results. Results are not as accurate as expected, probably due to atmospheric instability or other factors neglected by the model. However, the main trends are followed when validating the model output using field measurements. [ABSTRACT FROM AUTHOR]

When modelling the turbulent dispersion of a passive tracer using Reynolds-averaged Navier–Stokes (RANS) simulations, two different approaches can be used. The first consists of solving a transport equation for a scalar, where the governing parameters are the mean velocity field and the turbulent diffusion coefficient, given by the ratio of the turbulent viscosity and the turbulent Schmidt number Sc. The second approach uses a Lagrangian particle tracking algorithm, where the governing parameters are the mean velocity and the fluctuating velocity field, which is determined from the turbulence kinetic energy and the Lagrangian time T. A comparison between the two approaches and wind-tunnel data for the dispersion in the wake of a rectangular building immersed in a neutral atmospheric boundary layer (ABL) is presented. Particular attention was paid to the influence of turbulence model parameters on the flow and concentration field. In addition, an approach to estimate Sc and T based on the calculated flow field is proposed. The results show that applying modified turbulence model constants to enable correct modelling of the ABL improves the prediction for the velocity and concentration fields when the modification is restricted to the region for which it was derived. The difference between simulated and measured concentrations is smaller than 25% or the uncertainty of the data on 76% of the points when solving the transport equation for a scalar with the proposed formulation for Sc, and on 69% of the points when using the Lagrangian particle tracking with the proposed formulation for T. [ABSTRACT FROM AUTHOR]

Atmospheric in-flight icing on unmanned aerial vehicles (UAVs) is a significant hazard. UAVs that are not equipped with ice protection systems are usually limited to operations within visual line of sight or to weather conditions without icing risk. As many military and commercial UAV missions require flights beyond visual line of sight and into adverse weather conditions, energy-efficient ice protection systems are required. In this experimental study, two electro-thermal ice protection systems for fixed-wing UAVs were tested. One system was operated in anti-icing and de-icing mode, and the other system was designed as a parting strip de-icing system. Experiments were conducted in an icing wind tunnel facility for varying icing conditions at low Reynolds numbers. A parametric study over the ice shedding time was used to identify the most energy-efficient operation mode. The results showed that longer intercycle durations led to higher efficiencies and that de-icing with a parting strip was superior compared to anti-icing and de-icing without a parting strip. These findings are relevant for the development of energy-efficient systems in the future. [ABSTRACT FROM AUTHOR]