000			02149nam a22003617a 4500
003			OSt
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020			_a9783319790411
040			_aNISER LIBRARY _beng _cNISER LIBRARY
082	0	4	_a519.6 _bDRO-G
245	1	0	_aGradient discretisation method
260			_aCham : _bSpringer, _c2018.
300			_axxiv, 497 pages : _b19 b/w illustrations, 14 illustrations in colour
490	0		_aMathématiques et applications, _x1154-483X ; _v82
504			_aIncludes bibliographical references and index
520			_aThis monograph presents the Gradient Discretisation Method (GDM), which is a unified convergence analysis framework for numerical methods for elliptic and parabolic partial differential equations. The results obtained by the GDM cover both stationary and transient models; error estimates are provided for linear (and some non-linear) equations, and convergence is established for a wide range of fully non-linear models (e.g. Leray–Lions equations and degenerate parabolic equations such as the Stefan or Richards models). The GDM applies to a diverse range of methods, both classical (conforming, non-conforming, mixed finite elements, discontinuous Galerkin) and modern (mimetic finite differences, hybrid and mixed finite volume, MPFA-O finite volume), some of which can be built on very general meshes.
650		0	_aDiscretization (Mathematics)
650		0	_aComputer mathematics
650		0	_aElliptic partial differential equations
650		0	_aGradient discretisation method
650		0	_aParabolic partial differential equations
650		0	_aGradient schemes
650		0	_aDiscrete Aubin-Simon compactness theorems
700	1		_aDroniou, Jérôme
700	1		_aEymard, Robert
700	1		_aGallouët, Thierry
700	1		_aGuichard, Cindy
700	1		_aHerbin, Raphaèle
856			_3Table of content _uhttps://link.springer.com/content/pdf/bfm:978-3-319-79042-8/1
856			_3Reviews _uhttps://www.goodreads.com/book/show/95432726-the-gradient-discretisation-method?ref=nav_sb_ss_1_13#CommunityReviews
942			_2udc _cBK
999			_c35775 _d35775