Generating Wind Load Time Series

Wind load time series generation is essential for conducting wind vibration analysis. These time series can be obtained through various methodologies, each with distinct implementation considerations. One approach utilizes wind tunnel simulation data, where computational fluid dynamics (CFD) algorithms model wind pressure distributions under varying wind speeds and directions. This method typically involves solving Navier-Stokes equations with turbulence modeling to generate time-dependent load data. Alternatively, field measurement data provides another source, implemented through deployed anemometers and wind direction sensors on structures. This real-time monitoring approach requires sensor calibration algorithms and data acquisition systems to capture instantaneous wind load characteristics. Both methodologies necessitate proper signal processing techniques, including data interpolation and filtering algorithms, to ensure temporal continuity in the generated time series. Regardless of the selected method, the generated wind load time series serves as fundamental input data for subsequent wind-induced vibration analysis, where Fast Fourier Transform (FFT) algorithms and statistical processing functions are commonly applied to extract dynamic response characteristics.