Wind Speed Time History Simulation Using Autoregressive Moving Average Model

This program implements wind speed time history simulation using the Autoregressive Moving Average (ARMA) model. The core implementation focuses on the Davenport spectrum, which is widely used for calculating structural responses under wind loads. The ARMA model, as a statistical time series forecasting approach, employs a combination of autoregressive (AR) terms that capture dependencies on previous values and moving average (MA) terms that account for error corrections. The code implementation involves key algorithms for parameter estimation through spectral density matching, where the model coefficients are optimized to replicate the frequency characteristics of the Davenport spectrum. The simulation process generates realistic wind speed sequences by solving the ARMA difference equation with properly calibrated noise inputs. This method provides engineers and researchers in structural design and wind engineering with a practical computational tool for accurate assessment of structural behavior under wind-induced vibrations, facilitating more reliable wind load analysis in building design and structural engineering applications.