A novel looped-freezing mean approach based on Detached Eddy Simulation (DES)
approach is developed in context of assessing underhood cooling performance in
heavy-duty vehicles. The method involves computing a temporally averaged flow
field from DES simulations, which is then frozen and used by the energy solver
to predict temperature distributions. This process is iteratively repeated until
a statistically steady-state temperature field is achieved.
It is demonstrated that traditional DES approach demonstrates superior accuracy
in capturing forced convection heat transfer compared to the Reynolds-Averaged
Navier–Stokes (RANS) method. The validation against experimental data for flow
over a heated sphere at a Reynolds number of 105 shows that DES
yields Nusselt numbers with better correlation than RANS. However, it is
observed that DES approach captures unsteady flow features that introduce
temporal fluctuations in heat transfer. In the context of underhood cooling
evaluations where properties of the fluid are strong functions of temperature
and coupled with iterative processes such as dual-stream heat-exchanger
modeling, these instabilities can frequently lead to numerical divergence of the
simulation.
The novel looped-freezing mean DES method is then applied to a reduced underhood
model, including the heat exchanger and fan assembly, bounded by walls
representing adjacent vehicle components. The study show that the novel
looped-freezing mean DES approach provides stable and converged thermal
predictions for the reduced underhood model. This approach is particularly
beneficial for simulations involving highly transient flow fields coupled with
thermal phenomena, enabling accurate and reportable temperature evaluations in
critical regions.
