Efficient one-dimensional turbomachinery design method based on transfer learning and Bayesian optimization

Abstract

Article highlights A weighting-based transfer optimization learning framework is proposed. The evaluation cost required for the optimization is reduced by 30%. Selecting optimal source samples and preventing weight dilution can improve performance.

Keywords

• One-dimensional turbomachinery design
• Gaussian process
• Transfer learning
• Bayesian optimization