Analytical Model for Leakage Prediction in an Axial Labyrinth Seal

Abstract Compact size and efficiency of a radial turbomachine make it a preferred choice for sub-megawatt (MW) scale supercritical CO2 (sCO2) power plants. At sub-megawatt power thresholds, mitigation of parasitic losses stemming from working fluid leakages at the rear facet of turbomachinery emerges as a critical issue. Consequently, it is essential to precisely quantify the leakage rates during the preliminary design of turbomachinery. The present paper introduces a novel, one-dimensional leakage prediction model targeted at a see-through sCO2 labyrinth seal configuration. The proposed model is underpinned by a theoretical framework and corroborated through experimental findings from literature and computational simulations. Parametric examinations of the see-through sCO2 labyrinth seal, spanning diverse geometrical configurations and operational conditions are numerically investigated. A dimensionless leakage function is posited to outline the operational characteristics typical of a sCO2 labyrinth seal. The model demonstrates high accuracy in predicting leakage rates across all examined conditions, with an error margin of within ±10%. This analytical tool exhibits expedited computation capabilities while adeptly ascertaining leakage rate, static pressure distribution within the seal cavities, and temperature drops at individual seal teeth. The utility of this leakage prediction model not only extends to preliminary labyrinth seal designs but also facilitates rotor dynamic analysis to be comprehensively investigated.