New Data-Driven Models of Mass Flow Rate and Isentropic Efficiency of Dynamic Compressors

IF 2.1 3区 工程技术 Q2 ENGINEERING, AEROSPACE
Xiande Fang, Yuxiang Fang, Yang Yang, Zhiqiang He, Bei Yang
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Abstract

Dynamic compressors are widely used in many industrial sectors, such as air, land, and marine vehicle engines, aircraft environmental control systems (ECS), air-conditioning and refrigeration, gas turbines, gas compression and injection, etc. The data-driven formulas of mass flow rate and isentropic efficiency of dynamic compressors are required for the design, energy analysis, performance simulation, and control- and/or diagnosis-oriented dynamic simulation of such compressors and the related systems. This work develops data-driven models for predicting the performance of dynamic compressors, including empirical models for mass flow rate and isentropic efficiency, which have high prediction accuracy and broad application range. The performance maps of two multi-stage axial compressors of an aero engine and a centrifugal compressor of an aircraft ECS were chosen for evaluation of the existing empirical formulas and testing of the new models. There are 16 empirical models of mass flow rate and 14 empirical models of isentropic efficiency evaluated, and the results show that it is necessary to develop highly accurate empirical formulas both for mass flow rate and isentropic efficiency. With the data-driven method, two empirical models for mass flow rate and one for isentropic efficiency are developed. They are in general form, with some terms removable to make them simple while enhancing their applicability and prediction accuracy. The new models have much higher prediction accuracy than the best existing counterparts. The new mass flow rate models predict for the three compressors a mean absolute relative deviation (MAD) not greater than 1.3%, while the best existing models all have MAD > 2.0%. The new efficiency model predicts for the three compressors an MAD of 1.0%, 0.4%, and 1.9%, respectively, while the best existing model predicts for the three compressors an MAD of 1.8%, 0.8%, and 3.2%, respectively.
数据驱动的动态压缩机质量流量和等熵效率新模型
动态压缩机广泛应用于许多工业领域,如航空、陆地和海洋车辆发动机、飞机环境控制系统 (ECS)、空调和制冷、燃气轮机、气体压缩和喷射等。在对此类压缩机及相关系统进行设计、能量分析、性能仿真以及以控制和/或诊断为导向的动态仿真时,需要使用数据驱动的动态压缩机质量流量和等熵效率公式。本研究建立了数据驱动的动态压缩机性能预测模型,包括质量流量和等熵效率的经验模型,这些模型具有较高的预测精度和广泛的应用范围。我们选择了两台航空发动机多级轴向压缩机和一台飞机 ECS 离心压缩机的性能图,用于评估现有经验公式和测试新模型。共评估了 16 个质量流量经验模型和 14 个等熵效率经验模型,结果表明有必要为质量流量和等熵效率开发高精度的经验公式。利用数据驱动法,建立了两个质量流量经验模型和一个等熵效率经验模型。这两个模型采用一般形式,其中一些术语可以去除,使其变得简单,同时提高了其适用性和预测精度。新模型的预测精度远远高于现有的最佳模型。新的质量流量模型预测三台压缩机的平均绝对相对偏差 (MAD) 不大于 1.3%,而现有最佳模型的 MAD 均大于 2.0%。新效率模型预测三台压缩机的平均绝对相对偏差(MAD)分别为 1.0%、0.4% 和 1.9%,而现有最佳模型预测三台压缩机的平均绝对相对偏差(MAD)分别为 1.8%、0.8% 和 3.2%。
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来源期刊
Aerospace
Aerospace ENGINEERING, AEROSPACE-
CiteScore
3.40
自引率
23.10%
发文量
661
审稿时长
6 weeks
期刊介绍: Aerospace is a multidisciplinary science inviting submissions on, but not limited to, the following subject areas: aerodynamics computational fluid dynamics fluid-structure interaction flight mechanics plasmas research instrumentation test facilities environment material science structural analysis thermophysics and heat transfer thermal-structure interaction aeroacoustics optics electromagnetism and radar propulsion power generation and conversion fuels and propellants combustion multidisciplinary design optimization software engineering data analysis signal and image processing artificial intelligence aerospace vehicles'' operation, control and maintenance risk and reliability human factors human-automation interaction airline operations and management air traffic management airport design meteorology space exploration multi-physics interaction.
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