Generation of Wind Load Time Series with Implementation Approaches

In structural engineering, wind load time series serve as critical input data for studying the dynamic response of buildings and other structures under wind effects. These time series are essential for wind-induced vibration analysis, helping engineers assess structural safety and human comfort.

### Fundamental Principles Wind load time series describe the temporal variation of wind speed or wind pressure. They can be generated through field measurements, wind tunnel experiments, or numerical simulation methods like Computational Fluid Dynamics (CFD). In practical engineering where measured data is unavailable, numerical simulations or stochastic process models (such as Davenport spectrum or Kaimal spectrum) are commonly employed to simulate wind load characteristics over time.

### Key Implementation Steps Wind Spectrum Model Selection: Different wind fields (e.g., steady wind, fluctuating wind) require appropriate spectrum models. Kaimal spectrum suits turbulent wind simulation, while Davenport spectrum fits atmospheric boundary layer wind simulation. Random Process Generation: Based on selected spectrum models, engineers can use Inverse Fast Fourier Transform (IFFT) algorithms or Auto-Regressive (AR) models to generate wind speed time histories with desired statistical properties. Code implementation typically involves: - Defining spectrum parameters (integral length scale, turbulence intensity) - Generating random phase angles for Fourier components - Applying IFFT to transform frequency domain to time domain data Wind Pressure Conversion: Wind speed time series must be converted to surface wind pressure/loads using aerodynamic coefficients and structural shape relationships. This conversion often implements: - Bernoulli's equation for basic pressure calculation - Shape factor adjustments for complex geometries - Directional coefficient applications for multidirectional winds Validation and Adjustment: Generated time series require validation against measured data or design codes to ensure statistical properties (mean, variance, power spectral density) meet requirements. This involves: - Statistical moment calculations (mean, standard deviation) - Power Spectral Density (PSD) verification - Correlation function analysis for temporal characteristics

### Application Scenarios High-rise Buildings: Evaluating wind-induced vibration impacts on occupant comfort. Long-span Bridges: Analyzing buffeting and flutter stability. Wind Turbines: Simulating dynamic wind loads on blades and towers.

Through accurate wind load time series generation, engineers can conduct reliable structural dynamic analysis and optimize wind-resistant designs, thereby enhancing structural safety and durability.