2014
DOI: 10.1016/j.cma.2014.08.003
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A multiscale thermo-fluid computational model for a two-phase cooling system

Abstract: In this paper, we describe a mathematical model and a numerical simulation method for the condenser component of a novel two-phase thermosiphon cooling system for power electronics applications. The condenser consists of a set of roll-bonded vertically mounted fins among which air flows by either natural or forced convection. In order to deepen the understanding of the mechanisms that determine the performance of the condenser and to facilitate the further optimization of its industrial design, a multiscale ap… Show more

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Cited by 8 publications
(9 citation statements)
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“…Numerical techniques are used to obtain approximate solutions of the system. Lowest order finite elements in primal-mixed form on the network curvilinear axial coordinate are used to discretize the PDE model for VTN-blood and O 2 (Sacco et al 2014). The PDE system for O 2 , in the physiological range of parameters, is strongly dominated by convection, and this leads to a large local Péclet number if the spatial discretization parameter is not extremely small.…”
Section: Numerical Approachmentioning
confidence: 99%
“…Numerical techniques are used to obtain approximate solutions of the system. Lowest order finite elements in primal-mixed form on the network curvilinear axial coordinate are used to discretize the PDE model for VTN-blood and O 2 (Sacco et al 2014). The PDE system for O 2 , in the physiological range of parameters, is strongly dominated by convection, and this leads to a large local Péclet number if the spatial discretization parameter is not extremely small.…”
Section: Numerical Approachmentioning
confidence: 99%
“…9), because in the present model the variable p is not a Lagrange multiplier (as in the Stokes system), rather, it is the solution of the elliptic Darcy problem (1b)-(1c). In the case of the ADR equation we employ for the approximation of the concentration and of the cellular volume fractions the primal-mixed finite element discretization scheme with exponential fitting stabilization proposed and investigated in [26]. This choice is taken because it ensures that the computed numerical solutions satisfy a strict positivity property even in the case of a strongly advective regime.…”
Section: Numerical Approximation Of the 1d Mechanobiological Modelmentioning
confidence: 99%
“…As such, computational models in neuroscience have gained a great deal of traction because they allow rapid prototyping and testing without the need for live human subjects, thereby reducing the risk of patient harm while advancing the device’s iterative designing process [ 1 , 2 ]. In addition, computational models allow for theoretical testing of completely novel devices, highlighting yet unexplored avenues for device production [ 3 , 4 ].…”
Section: Introductionmentioning
confidence: 99%