Searching for the Most Suitable Loss Model Set for Subsonic Centrifugal Compressors Using an Improved Method for Off-Design Performance Prediction

Patrik Kovář, Adam Tater, Pavel Mačák and Tomáš Vampola
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Patrik Kovář: Center of Advanced Aerospace Technology, Faculty of Mechanical Engineering, Czech Technical University in Prague, Technická Street 4, 16607 Prague, Czech Republic
Adam Tater: Center of Advanced Aerospace Technology, Faculty of Mechanical Engineering, Czech Technical University in Prague, Technická Street 4, 16607 Prague, Czech Republic
Pavel Mačák: Center of Advanced Aerospace Technology, Faculty of Mechanical Engineering, Czech Technical University in Prague, Technická Street 4, 16607 Prague, Czech Republic
Tomáš Vampola: Center of Advanced Aerospace Technology, Faculty of Mechanical Engineering, Czech Technical University in Prague, Technická Street 4, 16607 Prague, Czech Republic

Energies, 2021, vol. 14, issue 24, 1-22

Abstract: This work investigates loss model sets based on empirical loss correlations for subsonic centrifugal compressors. These loss models in combination with off-design performance prediction algorithms make up an essential tool in predicting off-design behaviour of turbomachines. This is important since turbomachines rarely work under design conditions. This study employs an off-design performance prediction algorithm based on an iterative process from Galvas. Modelling of ten different loss mechanisms and physical phenomena is involved in this approach and is thoroughly described in this work. Geometries of two subsonic compressors were reconstructed and used in the evaluation of individual loss correlations in order to obtain a suitable loss model. Results of these variations are compared to experimental data. In addition, 4608 loss model sets were created by taking all possible combinations of individual loss estimations from which three promising candidates were selected for further investigation. Finally, off-design performance of both centrifugal compressors was computed. These results were compared to experimental data and to other loss model sets from literature. The newly composed loss model set No. 2137 approximates experimental data over a 21.2% better in relative error than the recent Zhang set and nearly a 36.7% better than the outdated Oh’s set. Therefore, set No. 2137 may contribute to higher precision of centrifugal turbomachines’ off-design predictions in the upcoming research.

Keywords: centrifugal compressor; performance prediction; empirical loss correlations; Eckardt’s compressors (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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