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Computer-Aided Engineering

Illustration of an offshore wind turbine on a barge with an illustration of how the moorings would work.

A simulation of a 5-MW wind turbine on an offshore semi-submersible with catenary moorings.

The National Wind Technology Center (NWTC) at NREL develops advanced computer-aided engineering (CAE) tools to support the wind and water power industries with state-of-the-art design and analysis capabilities. We have developed many software tools that produce realistic models that simulate the behavior of wind and water power technologies in complex environments—storm winds, waves offshore, earthquake loading, and extreme turbulence—and model the effects of turbulent inflow, unsteady aerodynamic forces, structural dynamics, drivetrain response, control systems, and hydrodynamic loading for offshore applications. NREL has also developed preprocessors to help build the models, postprocessors to analyze the results, and utilities to run and manage the processing tasks.

Our CAE tools have become the industry standard for analysis and development and are used by thousands of United States-based and international wind turbine designers, manufacturers, consultants, certifiers, researchers, and educators. The tools are developed as free, publicly available, open-source, professional-grade products as a resource for the wind industry. The open-source approach facilitates the tools' credibility and adaptability within the industry. The tools are modular, well documented, and supported by NREL through workshops and an on-line forum. They have been verified through model-to-model comparisons, validated with test measurements, and certified by Germanischer Lloyd.

For more information, visit the Computer-Aided Engineering Tools Web page. Please note that the tools are meant for professionals with expertise in wind energy engineering disciplines.

NWTC-Developed CAE Tools and Features


  • Generates airfoil data files from 2-D data
  • Adjusts 2-D data for rotational augmentation (3-D effects)
  • Extrapolates to high AoA
  • Computes dynamic stall parameters
  • Blends aerodynamic coefficients


  • Computes full-field stochastic wind realizations
  • Inputs are the desired wind profile and turbulence characteristics
  • Includes IEC- and site-specific turbulence models
  • Option to generate coherent structures


  • Computes coupled section properties of composite blades for beam-type models
  • Inputs are the airfoil shape and internal lay-up of composite laminas
  • Uses a combined laminate theory (modified) with shear flow approach


  • Computes coupled mode shapes and frequencies of blades and towers
  • Inputs are the boundary conditions and distributed isotropic beam properties
  • Considers axial-flap-lag-torsion coupling
  • Uses a 15-DOF FE developed to handle rotation-related terms


  • Calculates steady-state rotor performance
  • Inputs are the rotor geometry, airfoil data, wind, pitch, and rotor speed
  • Uses BEM theory


  • Wraps a genetic algorithm (GA) around WT_Perf
  • Optimizes rotor geometry (e.g. twist, chord) for optimal aerodynamic performance


  • Computes aerodynamics as part of the aero-elastic solution
  • Equilibrium (BEM) an dynamic (GDW) wake
  • Beddoes-Leishman dynamic stall
  • Turbulent and uniform wind input


  • Computes hydrodynamics as part of the hydro-elastic solution
  • Morison's equation for monopiles
  • Linear radiation/diffraction theory for floating platforms
  • Regular or irregular linear waves


  • Computes structural-dynamic and control-system responses as part of the aero-hydro-servo-elastic solution
  • Uses a combined modal and multi-body representation through 24 DOFs
  • Control system modeling through subroutines, DLLs, or Simulink® with MATLAB®
  • Nonlinear time-domain solution for loads analysis
  • Linearization procedure for controls and stability analysis
  • Preprocessor for building turbine models in MSC.ADAMS


  • A MATLAB®-based postprocessor for data analysis
  • Processes all data files together
  • Scales, offsets, and calculated channels
  • Statistics and extreme events
  • Probability density functions
  • Power spectral density
  • Rainflow counting, DELs, and life estimates
  • Plotting


  • A MATLAB®-based postprocessor for generating extreme-event tables
  • Processes all data files independently (requires less memory than MCrunch)
  • Scales, offsets, and calculated channels
  • Peak finding


  • A MATLAB®-based postprocessor for Multi-Blade-Coordinate transformation
  • Transforms the cumulative dynamics of spinning rotor blades into the non-rotating frame
  • Handles system, controls, and disturbance matrices for states and outputs
  • Applicable to controls design and stability analysis for 3-bladed rotors