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1. Finite element methods for the Laplace-Beltrami operator
Andrea Bonito, Alan Demlow and Ricardo H. Nochetto
2. The Monge–Ampère equation
Michael Neilan, Abner J. Salgado and Wujun Zhang
3. Finite element simulation of nonlinear bending models for thin elastic rods and plates
4. Parametric finite element approximations of curvature-driven interface evolutions
John W. Barrett, Harald Garcke and Robert Nürnberg
5. The phase field method for geometric moving interfaces and their numerical approximations
Qiang Du and Xiaobing Feng
6. A review of level set methods to model interfaces moving under complex physics: Recent challenges and advances
Robert I. Saye and James A. Sethian
7. Free boundary problems in fluids and materials
Eberhard Bänsch and Alfred Schmidt
8. Discrete Riemannian calculus on shell space
Behrend Heeren, Martin Rumpf, Max Wardetzky and Benedikt Wirth
Besides their intrinsic mathematical interest, geometric partial differential equations (PDEs) are ubiquitous in many scientific, engineering and industrial applications. They represent an intellectual challenge and have received a great deal of attention recently. The purpose of this volume is to provide a missing reference consisting of self-contained and comprehensive presentations. It includes basic ideas, analysis and applications of state-of-the-art fundamental algorithms for the approximation of geometric PDEs together with their impacts in a variety of fields within mathematics, science, and engineering.
- About every aspect of computational geometric PDEs is discussed in this and a companion volume. Topics in this volume include stationary and time-dependent surface PDEs for geometric flows, large deformations of nonlinearly geometric plates and rods, level set and phase field methods and applications, free boundary problems, discrete Riemannian calculus and morphing, fully nonlinear PDEs including Monge-Ampere equations, and PDE constrained optimization
- Each chapter is a complete essay at the research level but accessible to junior researchers and students. The intent is to provide a comprehensive description of algorithms and their analysis for a specific geometric PDE class, starting from basic concepts and concluding with interesting applications. Each chapter is thus useful as an introduction to a research area as well as a teaching resource, and provides numerous pointers to the literature for further reading
- The authors of each chapter are world leaders in their field of expertise and skillful writers. This book is thus meant to provide an invaluable, readable and enjoyable account of computational geometric PDEs
Mathematically trained research scientists and engineers with basic knowledge in partial differential equations and their numerical approximations
- No. of pages:
- © North Holland 2020
- 16th January 2020
- North Holland
- Hardcover ISBN:
- eBook ISBN:
Andrea Bonito is professor in the Department of Mathematics at Texas A&M University. Together with Ricardo H. Nochetto they have more than forty years of experience in the variational formulation and approximation of a wide range of geometric partial differential equations (PDEs). Their work encompass fundamental studies of numerical PDEs: the design, analysis and implementation of efficient numerical algorithms for the approximation of PDEs; and their applications in modern engineering, science, and bio-medical problems.
Department of Mathematics, Texas A&M University, USA
Ricardo H. Nochetto is professor in the Department of Mathematics and the Institute for Physical Science and Technology at the University of Maryland, College Park. Together with Andrea Bonito they have more than forty years of experience in the variational formulation and approximation of a wide range of geometric partial differential equations (PDEs). Their work encompass fundamental studies of numerical PDEs: the design, analysis and implementation of efficient numerical algorithms for the approximation of PDEs; and their applications in modern engineering, science, and bio-medical problems.
Institute for Physical Science and Technology, University of Maryland, USA
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