CFD-Machine Learning Driven Pod Optimization and Staged Pressure-Area Management for Supersonic Evacuated Tube Transport
CFD
This paper presents an integrated CFD-machine learning framework for optimizing pod geometry in supersonic evacuated tube transport, using composite cubic Bezier curves with seven design variables and Latin Hypercube Sampling to evaluate 200 configurations across subsonic and supersonic regimes.
See LICENSE file evacuated tube transportsupersonic aerodynamicspod optimization