Performance Prediction Model of Dynamic Pressure Oil-Air Separator

Autor: Xiaobin Zhang, Lei Lang, Xiaofeng Zhang, Hongqing Lv, Na Gao
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: International Journal of Aerospace Engineering, Vol 2021 (2021)
Druh dokumentu: article
ISSN: 1687-5966
1687-5974
DOI: 10.1155/2021/6665869
Popis: Based on the aeroengine lubricating oil system test bench, this paper used a dimensional analysis method to establish a mathematical model for predicting the separation efficiency and resistance of a dynamic pressure oil-air separator suitable for engineering. The analysis of the multivariate nonlinear fitting error and the experimental data showed that the established separation efficiency and resistance model could accurately predict the separation and resistance performance of the dynamic pressure oil-air separator within a certain range; the average error of the four separation characteristic prediction models was 3.5%, and the maximum error was less than 16%. The model that was established by the least square method had the highest accuracy; the average error of the multivariate nonlinear fitting of the four resistance characteristic prediction models was less than 4%, and the maximum error was less than 15%, which could be used to predict the resistance performance of the separator. The applicable working condition of the model is lubricating oil flow rate 4.3~8.5 L/min and oil-air ratio 0.5~3.
Databáze: Directory of Open Access Journals
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje