Abstract

In this study, a fast numerical method for solving the forced convection conjugate heat transfer problem was developed. The method first proposes a new dimensionless number (Fs) that represents the degree of influence of convection on the temperature field in the flow field. It delineates the stage of development of the flow field by monitoring the change in Fs to determine the moment when the flow field suspends updating and improve the computational efficiency of the transient temperature field. The accuracy of the algorithm is verified by taking the fluid–solid conjugate heat transfer under forced convection conditions as an example, which can accurately capture the changes of the flow field for a given monitoring step number of 100, and classify the flow field into E3, E4 and E5 development stages according to the judgment criteria. The results show that the higher development stages correspond to smaller levels of root mean square error (RMSE) of monitoring point temperatures within 3600 s of physical simulation time, and stages E3, E4, and E5 can reach the levels of E-2, E-3, and E-4, which are 3.4, 3.3, and 3.1 times faster than the traditional coupled calculations, respectively. The algorithm is still applicable at variable time steps, but it will require a higher number of determinations compared to a fixed step. The initial error of the quasi-steady algorithm can be reduced from the E-1 level to E-4 by choosing a higher stage of development. Finally the algorithm is tested under a variety of conditions by varying the inlet temperature and flow rate and is found to be robust to both device warming and cooling.

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