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    Multi-field variational formulations and mixed finite element approximations for electrostatics and magnetostatics

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    The final publication is available at link.springer.com[EN] In this paper we propose different multi-field variational formulations for electrostatics and magnetostatics, which can provide optimal discrete approximation of any particular vector field. The proposed formulations are constructed by appealing to mechanics point of view amenable to using general constitutive equations, which is quite different from electrostatics and magnetostatics formulations typical of physics and electrical engineering focusing on the corresponding global form suitable only for linear case. In particular, the formulations we propose can be combined with mixed discrete approximations that can ensure the continuity of tangential component of electric ormagnetic field and normal component of electric displacement and magnetic flux even for low order interpolations. The choice of this kind is quite different from currently favorite choice of high order finite element interpolations used for coupling electromagnetism with mechanics. The discrete approximation is based upon Whitney's interpolations representing the vector fields in terms of corresponding differential forms, with electric and magnetic fields as one-form and electric displacement and magnetic flux as two-form. The implementation of interpolations of this kind is made for 3D tetrahedron elements with non-standard approximation parameters defined not only at vertices (for zero-form), but at edges (for one-form) and at facets (for two-form). The results of several numerical simulations are presented to illustrate the performance of different formulations proposed herein.This work was supported jointly by Haut-deFrance Region (CR Picardie) (120-2015-RDISTRUCT-000010 and RDISTRUCT-000010) and EU funding (FEDER) for Chaire-deMecanique (120-2015-RDISTRUCTF-000010 and RDISTRUCTI000004). AI was also supported by IUF.Moreno-Navarro, P.; Ibrahimbegovic, A.; Ospina, A. (2020). Multi-field variational formulations and mixed finite element approximations for electrostatics and magnetostatics. Computational Mechanics. 65(1):41-59. https://doi.org/10.1007/s00466-019-01751-xS4159651Albanese R, Rubinacci G (1997) Finite element methods for the solution of 3d eddy current problems. In: Advances in imaging and electron physics, vol 102, pp 1–86. ElsevierAlotto P, Freschi F, Repetto M, Rosso C (2013) The cell method for electrical engineering and multiphysics problems: an introduction, vol 230. Springer, BerlinAngoshtari A, Shojaei MF, Yavari A (2017) Compatible-strain mixed finite element methods for 2d compressible nonlinear elasticity. Comput Methods Appl Mech Eng 313:596–631Arnold DN, Falk RS, Winther R (2006) Finite element exterior calculus, homological techniques, and applications. Acta Numerica 15:1–155Balanis CA (1999) Advanced engineering electromagnetics. 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    Non-negative mixed finite element formulations for a tensorial diffusion equation

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    We consider the tensorial diffusion equation, and address the discrete maximum-minimum principle of mixed finite element formulations. In particular, we address non-negative solutions (which is a special case of the maximum-minimum principle) of mixed finite element formulations. The discrete maximum-minimum principle is the discrete version of the maximum-minimum principle. In this paper we present two non-negative mixed finite element formulations for tensorial diffusion equations based on constrained optimization techniques (in particular, quadratic programming). These proposed mixed formulations produce non-negative numerical solutions on arbitrary meshes for low-order (i.e., linear, bilinear and trilinear) finite elements. The first formulation is based on the Raviart-Thomas spaces, and is obtained by adding a non-negative constraint to the variational statement of the Raviart-Thomas formulation. The second non-negative formulation based on the variational multiscale formulation. For the former formulation we comment on the affect of adding the non-negative constraint on the local mass balance property of the Raviart-Thomas formulation. We also study the performance of the active set strategy for solving the resulting constrained optimization problems. The overall performance of the proposed formulation is illustrated on three canonical test problems.Comment: 40 pages using amsart style file, and 15 figure

    Breaking spaces and forms for the DPG method and applications including Maxwell equations

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    Discontinuous Petrov Galerkin (DPG) methods are made easily implementable using `broken' test spaces, i.e., spaces of functions with no continuity constraints across mesh element interfaces. Broken spaces derivable from a standard exact sequence of first order (unbroken) Sobolev spaces are of particular interest. A characterization of interface spaces that connect the broken spaces to their unbroken counterparts is provided. Stability of certain formulations using the broken spaces can be derived from the stability of analogues that use unbroken spaces. This technique is used to provide a complete error analysis of DPG methods for Maxwell equations with perfect electric boundary conditions. The technique also permits considerable simplifications of previous analyses of DPG methods for other equations. Reliability and efficiency estimates for an error indicator also follow. Finally, the equivalence of stability for various formulations of the same Maxwell problem is proved, including the strong form, the ultraweak form, and a spectrum of forms in between

    The DPG-star method

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    This article introduces the DPG-star (from now on, denoted DPG^*) finite element method. It is a method that is in some sense dual to the discontinuous Petrov-Galerkin (DPG) method. The DPG methodology can be viewed as a means to solve an overdetermined discretization of a boundary value problem. In the same vein, the DPG^* methodology is a means to solve an underdetermined discretization. These two viewpoints are developed by embedding the same operator equation into two different saddle-point problems. The analyses of the two problems have many common elements. Comparison to other methods in the literature round out the newly garnered perspective. Notably, DPG^* and DPG methods can be seen as generalizations of LL\mathcal{L}\mathcal{L}^\ast and least-squares methods, respectively. A priori error analysis and a posteriori error control for the DPG^* method are considered in detail. Reports of several numerical experiments are provided which demonstrate the essential features of the new method. A notable difference between the results from the DPG^* and DPG analyses is that the convergence rates of the former are limited by the regularity of an extraneous Lagrange multiplier variable

    Some Key Developments in Computational Electromagnetics and their Attribution

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    Key developments in computational electromagnetics are proposed. Historical highlights are summarized concentrating on the two main approaches of differential and integral methods. This is seen as timely as a retrospective analysis is needed to minimize duplication and to help settle questions of attribution
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