Machine Learning Application to Centrifugal Compressor Design

Abstract The compressor design process starts with a concept that demonstrates key features required to meet the design objectives, and then the design matures through the process to the final manufacture of the engineered product. An important step in this process is the initial conceptual design, often referred to as preliminary machine selection. It’s called a selection since the design solution is a sum of selected, pre-engineered solutions for aerodynamic performance, mechanical integrity, etc. In this work, the authors present results from a study to leverage all previous industrial compressor builds (already known to be successful designs) to inform a digital library. This library is then used as training data for a ML model capable of presenting the application engineer with a plausible design solution within minutes.