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The accuracy of centrifugal compressors performance and flow field prediction by Computational Fluid Dynamics (CFD) is a serious problem facing in the design and analysis process due to its complex flow feature inside. Different turbulence models choosing in the Reynolds-Averaged Navier-Stokes Equations (RANS) leads to different simulation results. In this paper, a high-pressure-ratio centrifugal compressor was used as the simulation object to discuss the effect of common turbulence models, including a one-equation model (Spalart-Allmaras model), a two-equation linear model (Shear Stress Transport model) and a two-equation nonlinear model (Explicit Algebraic RSM model), on performance prediction under design speed. By introducing the calculation method of local entropy generation rate, an improved method of dividing different types of loss in centrifugal compressors was proposed. After comparing with the experiment results, the effect of turbulence models on loss prediction inside the compressor was quantitative investigated. Further, the flow mechanism underlying was discussed. The results show that the secondary flow loss have the largest impact on the components' prediction performance, also, the reasons for different magnitudes of secondary flow loss inside the impeller and the diffuser are different. These comparisons hope to help designers choose an appropriate turbulence model in further compressor design process and may benefit future turbulence modelling development. • The predicted performance of SA, SST and EARSM models and the experimental results were compared. • An improved losses dividing method in centrifugal compressors was introduced. • Combining with the local entropy generation rate computation method, difference in predicted value of various types of loss under different turbulence models were quantitative analyzed. • The decisive role of secondary flow losses in performance prediction was revealed. • The different reasons for the different prediction of secondary flow loss in the impeller and diffuser were discussed linking to the flow mechanism respectively. [ABSTRACT FROM AUTHOR]

Microchannel heatsinks with porous media, wavy and multi-layered configurations introduce compact designs and high efficiencies in cooling applications. Current Computational Fluid Dynamics (CFD) based study bridges the concept by introducing a novel double layered microchannel heatsink with wavy up-down and porous ribs alongside each other. Since Artificial Neural Network (ANN) trained by CFD results reveals designs with better thermal and hydraulic performance with an insignificant computational time, ANN is employed for finding the best performers and effects of waviness on Nusselt number, pressure drop, and maximum temperature difference at the bottom of the microchannel for a Reynold number range of 100 < Re < 800 by defining a thermal efficiency factor. Even though the pressure drop increases in the wavy design, the thermal performance is affected positively. Nusselt number increases more than 55% for Re = 800. The thermal performance increases with the introduction of Dean vortices, especially at higher Re. The best design provides maximum bottom temperature difference of 1.2 °C, with a Thermal Efficiency Factor of 1.34. However, it is observed that better thermal efficiency factors are attained by using a wavy channel at the top layer and keeping the bottom layer straight for the final design. [ABSTRACT FROM AUTHOR]