@article {2019, title = {Parametric POD-Galerkin Model Order Reduction for Unsteady-State Heat Transfer Problems}, journal = {Communications in Computational Physics}, volume = {27}, year = {2019}, pages = {1{\textendash}32}, abstract = {

A parametric reduced order model based on proper orthogonal decom- position with Galerkin projection has been developed and applied for the modeling of heat transport in T-junction pipes which are widely found in nuclear power plants. Thermal mixing of different temperature coolants in T-junction pipes leads to tem- perature fluctuations and this could potentially cause thermal fatigue in the pipe walls. The novelty of this paper is the development of a parametric ROM considering the three dimensional, incompressible, unsteady Navier-Stokes equations coupled with the heat transport equation in a finite volume approximation. Two different paramet- ric cases are presented in this paper: parametrization of the inlet temperatures and parametrization of the kinematic viscosity. Different training spaces are considered and the results are compared against the full order model.

}, issn = {1991-7120}, doi = {10.4208/cicp.OA-2018-0207}, url = {https://arxiv.org/abs/1808.05175}, author = {Sokratia Georgaka and Giovanni Stabile and Gianluigi Rozza and Michael J. Bluck} }