Mechanical Engineering Commons^™

Mission-Driven Inverse Design Of Blended Wing Body Aircraft With Machine Learning, Rohan S. Sharma, Serhat Hosder

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The intent of this work was to investigate the feasibility of developing machine learning models for calculating values of airplane configuration design variables when provided time-series, mission-informed performance data. Shallow artificial neural networks were developed, trained, and tested using data pertaining to the blended wing body (BWB) class of aerospace vehicles. Configuration design parameters were varied using a Latin-hypercube sampling scheme. These data were used by a parametric-based BWB configuration generator to create unique BWBs. Performance for each configuration was obtained via a performance estimation tool. Training and testing of neural networks were conducted using a K-fold cross-validation scheme. A …