@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 = {<p>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.</p>},
	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}
}
@conference {StarStabileGeorgakaBelloniRozzaDegroote2019,
	title = {POD-Galerkin Reduced Order Model of the Boussinesq Approximation for Buoyancy-Driven Enclosed Flows},
	booktitle = {International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M and C 2019},
	year = {2019},
	isbn = {9780894487699},
	author = {Kelbij Star and Giovanni Stabile and Sokratia Georgaka and Francesco Belloni and Gianluigi Rozza and Joris Degroote}
}
