"4"^^ . . "Kur\u00E1\u017E, Michal" . "41330" . . . "19"^^ . . "70348" . "I, P(TA02021249), S" . "Domain Decomposition Adaptivity for the Richards Equation Model" . "CZ - \u010Cesk\u00E1 republika" . . "RIV/60460709:41330/14:57170!RIV15-TA0-41330___" . . "RIV/60460709:41330/14:57170" . . . . "Havl\u00ED\u010Dek, Vojt\u011Bch" . . . . . . . . "Pech, Pavel" . "poor conditioning, slow convergence of the Picard method, highly heterogeneous material properties, multiplicative Schwarz method, diagonal scaling"@en . . "Mayer, Petr" . "This paper presents a study on efficient and economical domain decomposition adaptivity for Richards equation problems.Many real world applications of the Richards equation model typically involve solving systems of linear equations of huge dimensions. Multi-thread methods are therefore often preferred in order to reduce the required computation time.Multi-thread (parallel) execution is typically achieved by domain decomposition methods. In the case of non-homogeneous materials, the problem conditioning can be significantly improved if the computational domain is split efficiently, as each subdomain can cover only a certain material set within some defined parameter range. For linear problems, e.g. heat conduction, it is very easy to split the domain in this way. A problem arises for the nonlinear Richards equation, where the values of the constitutive functions, even over a homogeneous material, can vary within several orders of magnitude, see e.g.~\\cite{mojeamc}. If the Rothe method is" . . "Domain Decomposition Adaptivity for the Richards Equation Model"@en . "000338630100029" . . . "[74D801A5EEC0]" . . "1" . "This paper presents a study on efficient and economical domain decomposition adaptivity for Richards equation problems.Many real world applications of the Richards equation model typically involve solving systems of linear equations of huge dimensions. Multi-thread methods are therefore often preferred in order to reduce the required computation time.Multi-thread (parallel) execution is typically achieved by domain decomposition methods. In the case of non-homogeneous materials, the problem conditioning can be significantly improved if the computational domain is split efficiently, as each subdomain can cover only a certain material set within some defined parameter range. For linear problems, e.g. heat conduction, it is very easy to split the domain in this way. A problem arises for the nonlinear Richards equation, where the values of the constitutive functions, even over a homogeneous material, can vary within several orders of magnitude, see e.g.~\\cite{mojeamc}. If the Rothe method is"@en . "Domain Decomposition Adaptivity for the Richards Equation Model"@en . "0010-485X" . "Domain Decomposition Adaptivity for the Richards Equation Model" . "COMPUTING" . "3"^^ . "95" .