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 CCBladeDocumentation:
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> testCiting:
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.