This research aims to find the optimal standard k-e turbulence model constants (cµ, c1e, and c2e) for better predicting compressible fluid dynamics in an air jet ejector. The turbulence field in a jet flow plays an important role in influencing the performance of the momentum transfer process at a shear layer in nozzle application for momentum source and mixing process. In this research, some activities have been done before analyzing and optimizing the turbulence model constants, including preliminary turbulence modeling study for compressible flow in the air-jet ejector, verification, and validation with primary experimental data as well as by other secondary data. The preliminary studies in turbulence modeling presented that the turbulence modeling of a 3mm air jet-ejector resulted in a similar trend of the relation between entrainment ratio and motive fluid pressure. The results showed that the sensitive parameters in the standard k-emodel dissipation and diffusion terms, cµ, c1e, and c2e, strongly affected the optimum value of turbulence kinetic energy (k) and dissipation rate (e), compared to the reference model. Better k and e could be obtained by changing the c2e into positively proportional, but the cµ and c1e must be changed with opposite proportionality. It was found that the optimum standard k-e model constants in the case of air-jet ejector with 3 mm nozzle diameter for cµ, c1e, and c2e are 0.05, 1.48, and 1.88, respectively, with the error values for k being -8.88% and e being -17.44%.
Despite the successful use of the Standard model in simulating turbulent flow for many industrially relevant flows, the model is still less accurate for a range of important problems, such as unconfined flows, curved boundary layers, rotating flows, and recirculating flows. As part of the authors’ effort to extend the model applicability and reliability, this paper aims to study the effects of diffusivity parameter called the turbulent Prandtl number of dissipation rate () on the Standard model performance for predicting recirculating flow in a crossflow water turbine. The value of this parameter was varied from 0.5 to 1.5 in the CFD simulations, and the results were compared to the more sophisticated model, namely the RNG , which has been first qualitatively validated by an experimental result. In addition, the parameter value was also adjusted using the Multi-Linear Regression (MLR) method ranging from 0.42 to 1.5 to complement the CFD simulations. It was observed that reducing the value is effective in minimizing the average deviation of the turbulence properties concerning the RNG model. However, the adjusted model still faces difficulty in accurately predicting the pressure and velocity field. Based on this result, adjusting the constant in the Standard turbulence model has the potential to improve the model performance for modelling recirculating flow in terms of the turbulence properties, but still needs further investigation for the flow properties.
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