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CCBlade.jl

Summary: A blade element momentum method for propellers and turbines.

Author: Andrew Ning

Features:

  • Methodology is provably convergent (see http://dx.doi.org/10.1002/we.1636 although multiple improvements have been made since then)
  • Prandtl hub/tip losses (or user-defined losses)
  • Glauert/Buhl empirical region for high thrust turbines
  • Convenience functions for inflow with shear, precone, yaw, tilt, and azimuth
  • Can do airfoil corrections beforehand or on the fly (Mach, Reynolds, rotation)
  • Allows for flow reversals (negative inflow/rotation velocities)
  • Allows for a hover condition (only rotation, no inflow) and rotor locked (no rotation, only inflow)
  • Compatible with AD tools like ForwardDiff

Installation:

] add CCBlade

Documentation:

The documentation contains

  • A quick start tutorial to learn basic usage,
  • Guided examples to address specific or more advanced tasks,
  • A reference describing the API,
  • Theory in full detail.

Run Unit Tests:

pkg> activate .
pkg> test

Citing:

Ning, A., “Using Blade Element Momentum Methods with Gradient-Based Design Optimization,” Structural and Multidisciplinary Optimization, Vol. 64, No. 2, pp. 994–1014, May 2021. doi:10.1007/s00158-021-02883-6

Python / OpenMDAO users

In the openmdao folder there is a Python wrapper to this package to enable usage from OpenMDAO. This wrapper was developed/maintained by Daniel Ingraham and Justin Gray at NASA Glenn.