In rugged mountain areas, the lateral aerodynamic force and aerodynamic lift caused by strong winds are the main reasons for the lateral overturning of trains and the destruction of buildings and structures along the railroad line. Therefore, it is important to build a strong wind alarm system along the railroad line, and a reasonable and accurate short-time forecast of a strong wind is the basis of it. In this research, two methods of constructive function and time-series decomposition are proposed to pre-process the input wind speed for periodic strong winds in mountainous areas. Then, the improved Auto-Regressive Integrated Moving Average model time-series model was established through the steps of a white noise test, data stationarity test, model recognition, and order determination. Finally, the effectiveness of the improved wind speed prediction was examined. The results of the research showed that rational choice of processing functions has a large impact on wind speed prediction results. The prediction accuracy of the improved ARIMA model proposed in this paper is better than the results of the traditional Seasonal Auto-Regressive Integrated Moving Average model, and it can quickly and accurately realize the short-time wind speed prediction along the railroad line in rugged mountains. In addition, the improved ARIMA model has verified its universality in different mountainous places.

Bridges in mountainous areas are indispensable nodes in transportation networks, and wind resistance capabilities have become a controlling factor of long-span bridges built in mountain areas. Therefore, it is necessary to study the characteristics of wind fields under complex terrain. An improved inlet boundary by fitting the boundary curve was proposed in this study. The inlet fluctuating wind field was generated by the Correlation Improved Random Flow Generation method (CIRFG). The results of the numerical simulations show that the fluctuating wind input generated by CIRFG tallies with the target wind field, which proves the reliability of the proposed method. The method of fitting boundary curves to give inlet wind speed profiles can achieve non-uniform wind profile inputs. The results show the wind direction of the gorge varies significantly by height. The wind speed at the summit will accelerate affected by the terrain. Also influenced by the terrain, the turbulence intensity profiles in the simulated area show an S-shape. The transverse wind and angle of attack are uneven along the main girder, especially near slopes. The conclusions obtained in the study can provide references for the wind resistance of bridges built in mountainous areas.