Model Order Reduction of Turbulent Mixed Heat Transfer Problems by Projection Method

Computational fluid dynamics modeling has been widely applied to study flow and heat transfer problems in nuclear engineering. However, due to the prohibitively high computation cost, fast or real-time solution of nontrivial problems is still a challenging task under context of many-quires. Model order reduction is an efficient way to achieve significant speedup. For the turbulent mixed heat transfer problems, the Proper Orthogonal Decomposition (POD)-Galerkin projection method is introduced and then applied to solve the problem of non-isothermal mixing in a T-junction pipe with the inlet velocities treated as parameters. It is shown that a speedup of two orders of magnitude has been achieved. For new parameters out of the scope of the samples, the reduced order model still can give satisfactory results.