Research Paper Assessment and prediction of component efficiencies in supersonic ejector with friction losses Hailun Zhang, Lei Wang ⇑ , Lei Jia ⇑ , Xinli Wang School of Control Science and Engineering, Shandong University, Jinan, PR China highlights  Efficiencies of each part in ejector are investigated by considering friction losses.  Friction in different components represent diverse impacts on ejector efficiency.  An efficiency assessment correlation is established.  Proposed correlation benefits for ejector refrigerant system design. article info Article history: Received 23 May 2017 Revised 12 September 2017 Accepted 9 October 2017 Available online 16 October 2017 Keywords: Ejector Roughness Efficiency prediction CFD abstract In this paper, the influences of friction losses on ejector efficiencies are investigated by the computational fluid dynamics (CFD) technique. Roughness values factor is introduced to analyze ejector performance by considering the components efficiencies. Efficiencies of each component are assessed with different levels of roughness. Validation is given through comparisons between the calculated and experimental values obtained from the ejector refrigerant platform with diverse levels of surface roughness. Results indicate that the efficiency of the ejector decreases with the increase of roughness values and friction losses in constant-area section and diffuser have the most significant impact on ejector performance. By analyzing the relationship between efficiencies and roughness values, an efficiency correlation is built with a coef- ficient of determination over 0.9654. It is shown that proposed correlations for ejector component effi- ciencies can be utilized more accurately in system design of ejector based refrigerant system considering the friction losses. Ó 2017 Elsevier Ltd. All rights reserved. 1. Introduction With the ongoing increase of refrigeration demands and envi- ronmental deterioration, novel and energy efficient technologies are attracting more attention. The ejector refrigeration system (ERS) is currently considered as one of the most innovative and promising technologies in the area of refrigeration, due to its sim- ple structure, low energy consumption, and reliability. Since it was first realized that the major weak point of an ERS is its relatively low COP (coefficient of performance), when compared with conventional refrigeration systems. An enormous amount of numerical, experimental and theoretical studies were performed to enhance ejector performance and to establish the ERS as being more economically attractive. In recent years, the computational fluid dynamics (CFD) method has been widely employed to numerically investigate complex transonic flow inside the ejector. Rusly et al. [1] discovered that the maximum entrainment ratio (Er, the ratio between the sec- ondary and primary mass flow rates.) occurs just before a shock- wave; thus, the nozzle position is an important design parameter for the ejector. Ariafar et al. [2,3] presented a simulation method to research the mixing layer effects on the Er under different con- ditions. Above researches demonstrate that the CFD is a reliable method to study and simulate the fluid flow in ejector. However, there can be certain errors between the simulation results and experimental data. Hemidi et al. [4,5] compared the classical K-e model with the K-e-sst model with an air ejector and the overall deviation of the Er was below 10%, as compared with experimental data. Comparisons were also made between results from experi- ments, such as the CFD model and a theoretical 1-D model by Ouz- zane and Aidoun [6]. The results confirmed that the CFD model provided a more acceptable agreement (difference of less than 16%) than the 1-D model. Nevertheless, one important factor, the roughness of the ejector, has been ignored by most ejector simula- tions which may have caused aforementioned errors. https://doi.org/10.1016/j.applthermaleng.2017.10.054 1359-4311/Ó 2017 Elsevier Ltd. All rights reserved. ⇑ Corresponding author. E-mail addresses: leiwang@sdu.edu.cn (L. Wang), jialei@sdu.edu.cn (L. Jia). Applied Thermal Engineering 129 (2018) 618–627 Contents lists available at ScienceDirect Applied Thermal Engineering journal homepage: www.elsevier.com/locate/apthermeng