Numerical approximation of partial differential equations

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This book delves into the numerical approximation of partial differential equations (PDEs), aiming to illustrate various numerical methods, particularly those derived from the variational formulation of PDEs. It covers stability and convergence analysis, error bounds, and algorithmic implementation aspects, balancing theoretical analysis with practical applications. The text addresses a variety of problems, including linear and nonlinear, steady and time-dependent scenarios, with both smooth and non-smooth solutions. It also explores model equations and several (initial-) boundary value problems relevant to multiple application fields. Part I focuses on general numerical methods for discretizing PDEs, developing a comprehensive theory around Galerkin methods and their variants (such as Petrov Galerkin and generalized Galerkin), alongside collocation methods for spatial discretization. This theoretical framework is then applied to two significant numerical subspace realizations: the finite element method (including conforming, non-conforming, mixed, and hybrid types) and the spectral method (utilizing Legendre and Chebyshev expansions).