Recent Advances in Numerical Methods features contributions from distinguished researchers, focused on significant aspects of current numerical methods and computational mathematics. The increasing necessity to present new computational methods that can solve complex scientific and engineering problems requires the preparation of this volume with actual new results and innovative methods that provide numerical solutions in effective computing times. Each chapter will present new and advanced methods and modern variations on known techniques that can solve difficult scientific problems efficiently.
Numerical analysis forms a cornerstone of numeric computing and optimization, in particular recently, interval numerical computations play an important role in these topics. The interest of researchers in computations involving uncertain data, namely interval data opens new avenues in coping with real-world problems and deliver innovative and efficient solutions. This book provides the basic theoretical foundations of numerical methods, discusses key technique classes, explains improvements and improvements, and provides insights into recent developments and challenges. The theoretical parts of numerical methods, including the concept of interval approximation theory, are introduced and explained in detail. In general, the key features of the book include an up-to-date and focused treatise on error analysis in calculations, in particular the comprehensive and systematic treatment of error propagation mechanisms, considerations on the quality of data involved in numerical calculations, and a thorough discussion of interval approximation theory. Moreover, this book focuses on approximation theory and its development from the perspective of linear algebra, and new and regular representations of numerical integration and their solutions are enhanced by error analysis as well. The book is unique in the sense that its content and organization will cater to several audiences, in particular graduate students, researchers, and practitioners.
In January 1992, the Sixth Workshop on Optimization and Numerical Analysis was held in the heart of the Mixteco-Zapoteca region, in the city of Oaxaca, Mexico, a beautiful and culturally rich site in ancient, colonial and modern Mexican civiliza tion. The Workshop was organized by the Numerical Analysis Department at the Institute of Research in Applied Mathematics of the National University of Mexico in collaboration with the Mathematical Sciences Department at Rice University, as were the previous ones in 1978, 1979, 1981, 1984 and 1989. As were the third, fourth, and fifth workshops, this one was supported by a grant from the Mexican National Council for Science and Technology, and the US National Science Foundation, as part of the joint Scientific and Technical Cooperation Program existing between these two countries. The participation of many of the leading figures in the field resulted in a good representation of the state of the art in Continuous Optimization, and in an over view of several topics including Numerical Methods for Diffusion-Advection PDE problems as well as some Numerical Linear Algebraic Methods to solve related pro blems. This book collects some of the papers given at this Workshop.
This volume contains the proceedings of the 4th International Conference on Numerical Methods and Applications. The major topics covered include: general finite difference, finite volume, finite element and boundary element methods, general numerical linear algebra and parallel computations, numerical methods for nonlinear problems and multiscale methods, multigrid and domain decomposition methods, CFD computations, mathematical modeling in structural mechanics, and environmental and engineering applications. The volume reflects the current research trends in the specified areas of numerical methods and their applications.
Positive functions and some applications to stability questions for numerical methods; Constructive polynomial approximation in sobolev spaces; Questions of numerical condition related to polynomials; Global homotopies and newton methods; Problems with different time scales; Accuracy and resolution in the computation of solutions of linear and nonlinear equations; Finite element approximation to the one-dimensional stefan problem; The hodie method and its performance for solving elliptic partial differential equations; Solving ODE's with discrete data in SPEAKEASY; Perturbation theory for the generalized eigenvalue problem; Some remarks on good, simple, and optimal quadrature formulas; Linear differential equations and kronecker's canonical form.
This volume contains the proceedings of the Eighth International Conference on Scientific Computing and Applications, held April 1-4, 2012, at the University of Nevada, Las Vegas. The papers in this volume cover topics such as finite element methods, multiscale methods, finite difference methods, spectral methods, collocation methods, adaptive methods, parallel computing, linear solvers, applications to fluid flow, nano-optics, biofilms, finance, magnetohydrodynamics flow, electromagnetic waves, the fluid-structure interaction problem, and stochastic PDEs. This book will serve as an excellent reference for graduate students and researchers interested in scientific computing and its applications.
A numerical simulation is a computing calculation following a program that develops a mathematical model for a physical, social, economic, or biological system. Numerical simulations are required for analyzing and studying the behavior of systems whose mathematical models are very complex, as in the case of nonlinear systems. Capturing the resulting uncertainty of models based on uncertain parameters and constraints in confidence intervals (1-D), or more generally (>1-D) confidence regions, is very common for expressing to which degree the computed result is believed to be consistent with possible values of the targeted observable. This book examines the different methods used in numerical simulations, including adaptive and stochastic methods as well as finite element analysis research. This work is accompanied by studies of confidence regions, often utilized to express the credibility of such calculations and simulations.
Computational science is fundamentally changing how technological questions are addressed. The design of aircraft, automobiles, and even racing sailboats is now done by computational simulation. The mathematical foundation of this new approach is numerical analysis, which studies algorithms for computing expressions defined with real numbers. Emphasizing the theory behind the computation, this book provides a rigorous and self-contained introduction to numerical analysis and presents the advanced mathematics that underpin industrial software, including complete details that are missing from most textbooks. Using an inquiry-based learning approach, Numerical Analysis is written in a narrative style, provides historical background, and includes many of the proofs and technical details in exercises. Students will be able to go beyond an elementary understanding of numerical simulation and develop deep insights into the foundations of the subject. They will no longer have to accept the mathematical gaps that exist in current textbooks. For example, both necessary and sufficient conditions for convergence of basic iterative methods are covered, and proofs are given in full generality, not just based on special cases. The book is accessible to undergraduate mathematics majors as well as computational scientists wanting to learn the foundations of the subject. Presents the mathematical foundations of numerical analysis Explains the mathematical details behind simulation software Introduces many advanced concepts in modern analysis Self-contained and mathematically rigorous Contains problems and solutions in each chapter Excellent follow-up course to Principles of Mathematical Analysis by Rudin
Ch. 1. Model for fully nonlinear ocean wave simulations derived using Fourier inversion of integral equations in 3D / J. Grue and D. Fructus -- ch. 2. Two-dimensional direct numerical simulations of the dynamics of rogue waves under wind action / J. Touboul and C. Kharif -- ch. 3. Progress in fully nonlinear potential flow modeling of 3D extreme ocean waves / S.T. Grilli [und weitere] -- ch. 4. Time domain simulation of nonlinear water waves using spectral methods / F. Bonnefoy [und weitere] -- ch. 5. QALE-FEM method and its application to the simulation of free-responses of floating bodies and overturning waves / Q.W. Ma and S. Yan -- ch. 6. Velocity calculation methods in finite element based MEL formulation / V. Sriram, S.A. Sannasiraj and V. Sundar -- ch. 7. High-order Boussinesq-type modelling of nonlinear wave phenomena in deep and shallow water / P.A. Madsen and D.R. Fuhrman -- ch. 8. Inter-comparisons of different forms of higher-order Boussinesq equations / Z.L. Zou, K.Z. Fang and Z.B. Liu -- ch. 9. Method of fundamental solutions for fully nonlinear water waves / D.-L. Young, N.-J. Wu and T.-K. Tsay -- ch. 10. Application of the finite volume method to the simulation of nonlinear water waves / D. Greaves -- ch. 11. Developments in multi-fluid finite volume free surface capturing method / D.M. Causon, C.G. Mingham and L. Qian -- ch. 12. Numerical computation methods for strongly nonlinear wave-body interactions / M. Kashiwagi, C. Hu and M. Sueyoshi -- ch. 13. Smoothed particle hydrodynamics for water waves / R.A. Dalrymple [und weitere] -- ch. 14. Modelling nonlinear water waves with RANS and LES SPH models / R. Issa [und weitere] -- ch. 15. MLPG_R method and Its application to various nonlinear water waves / Q.W. Ma -- ch. 16. Large Eddy simulation of the hydrodynamics generated by breaking waves / P. Lubin and J.-P. Caltagirone -- ch. 17. Recent advances in turbulence modeling for unsteady breaking waves / Q. Zhao and S.W. Armfield -- ch. 18. Freak waves and their interaction with ships and offshore structures / G.F. Clauss
A numerical simulation is a computing calculation following a program that develops a mathematical model for a physical, social, economic, or biological system. Numerical simulations are required for analyzing and studying the behavior of systems whose mathematical models are very complex, as in the case of nonlinear systems. Capturing the resulting uncertainty of models based on uncertain parameters and constraints in confidence intervals (1-D), or more generally (>1-D) confidence regions, is very common for expressing to which degree the computed result is believed to be consistent with possible values of the targeted observable. This book examines the different methods used in numerical simulations, including adaptive and stochastic methods as well as finite element analysis research. This work is accompanied by studies of confidence regions, often utilized to express the credibility of such calculations and simulations.
