摘要
针对我国航天领域某重点项目的研制任务,设计了一台氦气体轴承低温透平膨胀机,并对其热力性能进行了分析和讨论.提出了一种考虑膨胀机整体热力性能及机械性能的透平膨胀机系统多目标优化方法.解决了透平膨胀机使用不同工质时相似准则的选取方法,进而在自行开发的较为完善的透平膨胀机一元流动性能预测程序的基础上,获得了模化时所应遵循的相似准则数.以人工神经网络为基础实现了透平膨胀机的性能转换问题.试验结果表明,所研制的氦气体轴承透平膨胀机的绝热效率大于71%;在出口温度为12 8K时,膨胀机效率已达到75%;膨胀机的最大制冷量接近2kW.
To accomplish the research task of helium turbo-expander used in the space area, a helium turbo-expander using gas bearings has been designed. The thermal performance of this helium turbo-expander is discussed, and a multiple object optimization design for the whole performance of a radial-axial flow cryogenic turbo-expander is developed. A method of selecting similarity criteria for different working fluids in turbo-expander is proposed. In theoretical research on predicting the thermal performance of expansion turbine, an effective performance prediction program is developed based on a one-dimensional analysis of expansion turbine, and the similarity criteria used to simulate modeling tests are obtained. Furthermore, the artificial neural network is used to deal with the transforming problem of turbine performance. The efficiency of this turbine has been increased to 75% at the exit temperature of 12.8 K, and the system cooling capacity of 2 kW has been obtained.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2003年第7期666-669,共4页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(50 2 0 60 1 5)
真空低温技术与物理国防科技重点实验室基金资助项目 .
