Open AccessComputation of Nonlinear Thermoelectric Effects with Adaptive Methods
Author(s) -
Aizuddin Mohamed,
Razi Abdul-Rahman
Publication year - 2020
Publication title -
journal of advanced research in fluid mechanics and thermal sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.247
H-Index - 13
ISSN - 2289-7879
DOI - 10.37934/arfmts.76.3.7584
Subject(s) - nonlinear system , computation , finite element method , discretization , convergence (economics) , mathematics , algorithm , computer science , a priori and a posteriori , adaptive mesh refinement , mesh generation , polynomial , acceleration , mathematical optimization , computational science , mathematical analysis , physics , classical mechanics , philosophy , epistemology , quantum mechanics , economics , thermodynamics , economic growth
An implementation for a fully automatic adaptive finite element method (AFEM) for computation of nonlinear thermoelectric problems in three dimensions is presented. Adaptivity of the nonlinear solvers is based on the well-established hp-adaptivity where the mesh refinement and the polynomial order of elements are methodically controlled to reduce the discretization errors of the coupled field variables temperature and electric potential. A single mesh is used for both fields and the nonlinear coupling of temperature and electric potential is accounted in the computation of a posteriori error estimate where the residuals are computed element-wise. Mesh refinements are implemented for tetrahedral mesh such that conformity of elements with neighboring elements is preserved. Multiple nonlinear solution steps are assessed including variations of the fixed-point method with Anderson acceleration algorithms. The Barzilai-Borwein algorithm to optimize the nonlinear solution steps are also assessed. Promising results have been observed where all the nonlinear methods show the same accuracy with the tendency of approaching convergence with more elements refining. Anderson acceleration is the most efficient among the nonlinear solvers studied where its total computing time is less than half of the more conventional fixed-point iteration.