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This book is devoted to the study of partial differential equation problems both from the theoretical and numerical points of view. After presenting modeling aspects, it develops the theoretical analysis of partial differential equation problems for the three main classes of partial differential equations: elliptic, parabolic and hyperbolic. Several numerical approximation methods adapted to each of these examples are analyzed: finite difference, finite element and finite volumes methods, and they are illustrated using numerical simulation results. Although parts of the book are accessible to Bachelor students in mathematics or engineering, it is primarily aimed at Masters students in applied mathematics or computational engineering. The emphasis is on mathematical detail and rigor for the analysis of both continuous and discrete problems.
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Partial Differential Equations: Modeling, Analysis and Numerical Approximation, Herve Le Dret
- Sprache
- Erscheinungsdatum
- 2018
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- Titel
- Partial Differential Equations: Modeling, Analysis and Numerical Approximation
- Sprache
- Englisch
- Autor*innen
- Herve Le Dret
- Verlag
- Birkhäuser
- Erscheinungsdatum
- 2018
- ISBN10
- 3319800663
- ISBN13
- 9783319800660
- Kategorie
- Mathematik
- Beschreibung
- This book is devoted to the study of partial differential equation problems both from the theoretical and numerical points of view. After presenting modeling aspects, it develops the theoretical analysis of partial differential equation problems for the three main classes of partial differential equations: elliptic, parabolic and hyperbolic. Several numerical approximation methods adapted to each of these examples are analyzed: finite difference, finite element and finite volumes methods, and they are illustrated using numerical simulation results. Although parts of the book are accessible to Bachelor students in mathematics or engineering, it is primarily aimed at Masters students in applied mathematics or computational engineering. The emphasis is on mathematical detail and rigor for the analysis of both continuous and discrete problems.