Narrow Results

The Wind–Vehicle–Bridge (WVB) coupling method is extensively applied in engineering practices for the dynamic analysis of railway bridges. However, research on the dynamic behaviors of the vehicle on curved bridges in wind conditions remains limited due to the complexities of interactions involved. In this study, the railway alignment and an actual curved bridge were chosen and modeled. The framework of the WVB system was detailed, and four excitation cases were investigated, considering mean wind, fluctuating wind and track irregularities. Three distinct scenarios, including vehicle on a curved bridge subjected to Inward Blowing Wind (IBW), Outward Blowing Wind (OBW) and vehicle on a straight bridge subjected to wind, were explored. The main conclusions are as follows: (1) wind direction significantly affects wheel unloading rate, lateral force, and derailment coefficient; (2) under mean wind condition, critical wind speed increases with the vehicle speed increasing under IBW, while it decreases with the vehicle speed increasing under OBW; (3) Combined wind and track irregularities reveal that wind direction significantly influences dynamic responses, and lower speeds are not necessarily equal to safer conditions for vehicles on curved bridges.

Aerosols were continuously collected for 2 or 3 hours during the periods of 4-27 August 1997 and of 23 March-2 April 1998 at a suburb of Sendai City (east 10 km from Sendai), and meteorological data such as wind directions, wind velocities, etc were measured at the same time. The collected aerosol samples were analyzed by the particle-induced X-ray emission (PIXE) method. Fourteen elements (S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Hg and Pb) were contained in these samples. The elemental concentrations increased in the daytime and decreased at night. It coincided with the time variation of people movement. The concentrations of Mn, Fe, Zn and Pb elements depended strongly on the direction of wind and their distributions for wind directions reflected to the position of aerosol sources. This result suggests that the position of aerosol source can be determined by measuring aerosols and wind directions at the many positions.

In this paper, an analysis of temporal variation of wind speed and wind direction recorded at 10 min intervals are presented. The measurements were carried out at Hambanthota, a site located in the southern coastal belt of Sri Lanka which has a high potential for wind power generation. The multifractal detrended fluctuation analysis was used to analyze the temporal scaling properties of wind speeds and wind directions. The analysis was carried out for seasonal variation of wind speed and wind direction. It was observed that the scaling behavior of wind speed in Hambanthota is similar to the scaling behavior observed in previous studies which were carried out in other parts of the world. The seasonal wind and wind direction change exhibits different scaling behavior. No difference in scaling behavior was observed with heights. The degree of multifractality is high for wind direction when compared with wind speed for each season.

Based on grid icing observation data of Erlang Mountain region in the winter during 2013-2014, the characteristics of the grid icing in the regional Erlang Mountain and time variations were researched. The regional power grid and icing intensity classified into mild, moderate, severe icing, and ice characteristics of the growth process were also studied. Air temperature, wind direction, wind speed and other meteorological elements were discussed in the influence of the strength of the power grid ice. The results showed that: (1) in Erlang mountain areas, most icing are mild to moderate icing, severe icing phenomenon is relatively rare, except for the special effects of the weather system. (2) When the temperature is low, roughly -5 °C ∼ -8 °C is the most conducive to ice crystals due to the air in the water, constant humidity and the lower the air temperature, the faster the ice formation. Certain temperature and humidity result in longer freezing and thicker ice. Wind speed plays a role in transporting water vapor and water droplets have an important influence on the formation of ice. This study demonstrates when the wind speed is at 2 ∼ 6m/s, ice forms the fastest. (3) Temperature, wind speed and quantitative relationship of ice thickness are linear correlation.