A Comprehensive Optimizer for Multi-Objective and Multidisciplinary Applications

As the CLEAN initiative continues to drive development toward the goal of carbon neutral aviation, it is imperative to address the need for a comprehensive optimization structure. Multiple teams, including Aerodynamics, Structure, and Propulsion, are all working to provide their own novel solutions to unique problems proposed by carbon-neutral aviation. Realizing this, one can recognize the demand for a multi-objective, multidisciplinary optimizer that is capable of compiling design objectives and constraints from each respective team, thus allowing the provision of complete solutions to the design space. Our optimization team proposes a biologically inspired Genetic Algorithm optimizer to ensure the “survival of the fittest” or best-performing designs are generated. Through Python and ANSYS Fluent, we wrap together a design manipulation-CAD generation-CFD simulation-optimization evaluation process in which “chromosomes,” or solutions, are mated continually until performance criteria are met by a final, optimized design. At this point in time, we have operational 2D and 3D airfoil optimization codes in which L/D is evaluated as the design objective. Moving forward, we look to involve data from Propulsion to maximize flight range and minimize NOX emissions. Also, we are working to include information of how static stability of the generated airfoil is changed due to mutations of various “genes,” or design variables in the optimization process.

Elijah Barritt, University South Florida