Impeller design and multi-stage architecture optimisation for turbocompressors operating with a helium-neon gas mixture

Abstract

As part of the design of a new particle accelerator at CERN, a research is conducted to study the challenges and opportunities of multi-stage turbocompressor machines operating with light gases and more specifically with a mixture of helium and neon. First, a 1D stage performance prediction model is implemented and coupled with a genetic algorithm in order to generate an impeller database. Then, a stacking method is developed considering design philoso-phies and technological limitations observed in the industry. This model is coupled with a second loop of the same genetic algorithm, which provides multi-stage architectures optimised for either com-pactness, i.e. number of stages, or efficiency. For both objectives, an ideal number of stages can be determined which increases signif-icantly as the operating gas becomes lighter. The impellers diversity within the database also plays an important role on the overall machine architecture. Finally, in alignment with potential technological improvements, the motor maximum rotational speed is varied to study the achievable reduction in the required number of stages.