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Experimental Study and Statistical Modeling of an Injection Scroll Compressor Operating with R407c.
Quoilin, Sylvain
2014
 

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Keywords :
injection compressor; scroll; machine learning; Gaussian Processes; experimental
Abstract :
[en] This working paper describes an experimental study carried out on a refrigeration scroll compressor with and without vapour injection. The test rig designed for that purposed allows evaluating the performance over a wide range of operating conditions, by varying the supply pressure, the injection pressure, the exhaust pressure, the supply superheating and the injection superheating. 97 Steady-state points are measured, with a maximum isentropic efficiency of 64.1% and a maximum consumed electrical power of 13.1 kW. A critical analysis of the experimental results is then carried out to evaluate the quality of the data using a machine learning method. This method based on Gaussian Processes regression, is used to build a statistical operating map of the compressor as a function of the different inputs. This statistical operating map can then be compared to the experimental data points to evaluate their accuracy.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Quoilin, Sylvain  ;  Université de Liège - ULiège > Département d'aérospatiale et mécanique > Systèmes énergétiques
Language :
English
Title :
Experimental Study and Statistical Modeling of an Injection Scroll Compressor Operating with R407c.
Publication date :
January 2014
Version :
1.0
Number of pages :
9
Available on ORBi :
since 16 January 2014

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