WIND SPEED DISTRIBUTION REGULARITY AND WIND REDUCTION EFFECT OF SHELTER NET

Wind speed distribution regularities in a shelter mesh (S. M.) have been deduced from the wind speed distribution in the sheltered area of a single shelter beh (S. B.).The components of a wind vector in a mesh follow the error function distribution model or the logarithmic model of 2-variable power function.The wind vector itself follows the vector composition model of these models.We can calculate the wind speed distribution and wind reduction effect of a mesh under the conditions of any shelter-belt characteristics, any size and shape of a mesh and any wind inclination angle with this model. The results of our field model experiment are in better agreement with the theoretically calculated results.

Extreme Values of Wind Speed over the Kara Sea Based on the ERA5 Dataset

Extreme values of wind speed were studied based on the highly detailed ERA5 dataset covering the central part of the Kara Sea. Cases in which the ice coverage of the cells exceeded 15% were filtered. Our study shows that the wind speed extrema obtained from station observations, as well as from modelling results in the framework of mesoscale models, can be divided into two groups according to their probability distribution laws. One group is specifically designated as black swans, with the other referred to as dragons (or dragon-kings). In this study we determined that the data of ERA5 accurately described the swans, but did not fully reproduce extrema related to the dragons;these extrema were identified only in half of ERA5 grid points. Weibull probability distribution function (PDF) parameters were identified in only a quarter of the pixels. The parameters were connected almost deterministically. This converted the Weibull function into a one-parameter dependence. It was not clear whether this uniqueness was a consequence of the features of the calculation algorithm used in ERA5, or whether it was a consequence of a relatively small area being considered, which had the same wind regime. Extremes of wind speed arise as mesoscale features and are associated with hydrodynamic features of the wind flow. If the flow was non-geostrophic and if its trajectory had a substantial curvature, then the extreme velocities were distributed according to a rule similar to the Weibull law.

Location of anemometer along Lanzhou-Xinjiang railway

Using structured mesh to discretize the calculation region, the wind velocity and pressure distribution in front of the wind barrier under different embankment heights are investigated based on the Detached Eddy Simulation(DES) with standard SpalartAllmaras(SA) model. The Reynolds number is 4.0×105 in this calculation. The region is three-dimensional. Since the wind barrier and trains are almost invariable cross-sections, only 25 m along the track is modeled. The height of embankment ranges from 1 m to 5 m and the wind barrier is 3 m high. The results show that the wind speed changes obviously before the wind barrier on the horizontal plane, which is 4.5 m high above the track. The speed of wind reduces gradually while approaching the wind barrier. It reaches the minimum value at a distance about 5 m before the wind barrier, and increases dramatically afterwards. The speed of wind at this location is linear with the speed of far field. The train aerodynamic coefficients decrease sharply with the increment of the embankment height. And they take up the monotonicity. Meanwhile, when the height increases from 3 m to 5 m, they just change slightly. It is concluded that the optimum anemometer location is nearly 5 m in front of the wind barrier.