Abstract: Processes for optimizing the geometry of a blade for use in a propeller are disclosed. In one exemplary process, an optimization routine that generates new blade geometries based on structural parameters and calculates performance parameters of each blade geometry, including aerodynamic performance parameters, farfield acoustic parameters, and/or electrical power requirements to operate a propeller having the blade geometry, is performed. The optimization routine receives design parameters and weightings from a user and can use one or more surrogate algorithms to map a design space of the weighted values of the design parameters to find their local minima. The optimization routine then determines an optimized blade geometry using a gradient-based algorithm to generate new blade geometries to explore the minima until the weighted values of the design parameters converge at an optimized blade geometry representing the global minima of the design space.

Abstract: Processes for optimizing the geometry of a blade for use in a propeller are disclosed. In one exemplary process, an optimization routine that generates new blade geometries based on structural parameters and calculates performance parameters of each blade geometry, including aerodynamic performance parameters, farfield acoustic parameters, and/or electrical power requirements to operate a propeller having the blade geometry, is performed. The optimization routine receives design parameters and weightings from a user and can use one or more surrogate algorithms to map a design space of the weighted values of the design parameters to find their local minima. The optimization routine then determines an optimized blade geometry using a gradient-based algorithm to generate new blade geometries to explore the minima until the weighted values of the design parameters converge at an optimized blade geometry representing the global minima of the design space.