DRDMannTurb

DRDMannTurb (Deep Rapid Distortion Mann Turbulence) is a GPU-accelerated, data-driven Python framework for the automatic fitting of spectra data and generation of synthetic turbulent wind fields. This package is intended to be used by wind engineers in applications requiring rapid simulation of realistic wind turbulence. It is based off of the Deep Rapid Distortion models presented in Keith, Khristenko, Wohlmuth (2021). The data-driven functionalities are GPU-accelerated via a PyTorch implementation.

Contents:

• Getting Started
• Spectra Fitting
• Field Generation
• Installation

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• Examples
  • Example 1: Basic Mann Model Fit
  • Example 2: Synthetic Data Fit
  • Example 3: Adding Regularization and Penalty Terms to Fitting
  • Example 4: Changing MLP Architecture and Fitting
  • Example 5: Custom Data Fit
  • Example 6: Interpolating Spectra Data and Fitting
  • Example 7: Mann Eddy Lifetime Linear Regression
  • Example 8: Fluctuation Field Generation
  • Example 9: Fluctuation Field Generation from DRD Model

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• API Reference
  • Spectra Fitting with DRD Calibration
  • Fluctuation Field Generation
  • Plotting Utilities

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• Internal API Reference
• Spectra Fitting
  • Internal Neural Network Interfaces
  • Rapid Distortion Power Spectra
• Random Field Generation
  • Covariance Kernels
  • Covariance Sampling Methods
  • Gaussian Random Field Generation

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Indices and tables

• Index

• Module Index

• Search Page