Abstract
Computational analysis of nucleate boiling occurring in liquid cooled applications, such as internal combustion engines is often implemented within a single phase Computational Fluid Dynamics (CFD) framework, owing to low vapor fractions involved. With increase in specific power and the resulting higher thermal loads, accounting for the presence of the vapor phase using a multiphase framework is required in certain conditions, despite the higher computational costs. While detailed resolution of the liquid and vapor phases in nucleate boiling using a two fluid model is excessively computationally expensive, the homogeneous mixture multiphase framework is a good compromise between resolution and computational cost. In this article a numerical wall boiling model is implemented within both, a single phase and the mixture multiphase frameworks. Results from the two approaches are compared with measurements in a channel flow. The results from both approaches are in good agreement with experiments. The single phase approximation is valid when the vapor generation is low. The sensitivity of the results to the computational grid is also discussed in detail. Further the two frameworks are used to simulate the heat transfer in the coolant jacket of a four-cylinder petrol engine. The results from the numerical simulations are compared with measurements. Both computational frameworks compare reasonably well with the measurements in terms of local metal temperature. However, the advantage of accounting for the vapor phase using the mixture multiphase framework is evident when the parameter related to vapor bubble interactions is analysed in detail. • The Blended Boiling Model is implemented within single phase and mixture multiphase frameworks in CFD. • Numerical results are validated with relevant experimental data in the literature. • The mixture multiphase framework is more accurate with increase in net vapor generation. • Excessive grid refinement leads to inaccurate results in both frameworks. • Heat transfer in passenger car engine is analysed using both frameworks and results are validated with test data.
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