A coarse grid projection method for accelerating heat transfer computations
Ali Kashefi

TL;DR
This paper introduces a Coarse Grid Projection (CGP) method to accelerate heat transfer simulations by solving linear equations on coarser meshes, demonstrating good accuracy and significant computational savings in natural convection and heat transfer cases.
Contribution
The study extends the CGP methodology to thermal fields, validating its effectiveness for unsteady heat transfer problems with unstructured finite element meshes.
Findings
CGP achieves good agreement with non-CGP results for velocity and temperature fields.
The phase lag in temperature and Nusselt number predictions is minimal with one or two levels of coarsening.
CGP significantly reduces CPU time while maintaining accuracy in heat transfer simulations.
Abstract
Coarse Grid Projection (CGP) methodology is used to accelerate the computations of sets of decoupled nonlinear evolutionary and linear static equations. In CGP, the linear equations are solved on a coarsened mesh compared to the nonlinear equations, leading to a reduction in central processing unit (CPU) time. The accuracy of the CGP scheme has been assessed for the advection-diffusion equation along with the pressure Poisson equation. Here we add another decoupled equation to this set: the energy equation. In this article, we examine the influence of CGP methodology for the first time on thermal fields. To this purpose, a semi-implicit-time-integration unstructured-triangular-finite-element CGP version is selected. The CGP platform is validated with two different test cases: first, natural convection induced by a hot circular cylinder located in the center of a cold square cylinder,…
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Taxonomy
TopicsAdvanced Numerical Methods in Computational Mathematics · Fluid Dynamics and Turbulent Flows · Computational Fluid Dynamics and Aerodynamics
