• Journal of the Korean Society of Propulsion Engineers
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• v.13 no.2
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• pp.54-63
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• 2009

Large eddy simulation was conducted for flow development in a chamber with wall injection which simulates the cold flow in an idealized hybrid rocket motor. It was found that a peculiar timescale, roughly corresponding to St~0.5, resides in the flowfield resulting from the interaction between the main oxidizer and wall injected flows. However, the fact that this time characteristics is absent in the temperature field in the vicinity of the wall indicates that even a small regression rate renders the passive scalar, such as temperature, dissimilar to the velocity field. This implies that a classical approach, which assumes that constant turbulent Prandtl number, should be replaced by a more sophisticated turbulence models to accurately predict the temperature field in the hybrid motor.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.10
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• pp.1255-1263
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• 2004

An a priori test has been conducted for the dynamic mixed model which was generalized for the prediction of passive scalar field in a turbulent channel flow The results from a priori tests indicated that dynamic mixed model is capable of predicting both subgrid-scale heat flux and dissipation rather accurately. The success is attributed to the explicitly calculated resolved term incorporated into the model. The actual test of the model in a LES a posteriori showed that dynamic mixed model is superior to the widely used dynamic Smagorinsky model in the prediction of temperature statistics.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.6
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• pp.628-637
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• 2004

The present study investigates the performance of dynamic mixed model (DMM; Zang et ai.) in a channel with strong wall injection through a Large eddy simulation (LES) technique. The DMM results are compared with those of DNS and the results obtained with popular dynamic Smagorinsky model (DSM). Better agreement is achieved when using the DMM with box filter than DSM and coarse DNS in predicting the first and second order statistics as well as large-scale structures of velocity and temperature fields. Such favorable features of DMM are attributed to the fact that it explicitly calculates the modified Leonard stress term and only models the remaining cross and the SGS Reynolds stress terms and, thus, it reduces the excessive burden put on the model coefficient of DSM. Also it is demonstrated that the DMM can be successfully extended to the prediction of temperature (passive scalar) field where strong streamwise inhomogeneity exists.