Frontiers in Applied Mathematics – serie

This book delves into the rapidly changing area of combustion, in which asymptotic methods and bifurcation theory have made a significant impact as have the constant density, small heat release models and other important contributions.

Provides the user with a step by step introduction to Fortran 77, BLAS, LINPACK, and MATLAB. It is a reference that spans several levels of practical matrix computations with a strong emphasis on examples and ""hands on"" experience.

Here is a monograph that describes current research efforts in the application of symbolic computation to several areas, including dynamical systems, differential geometry, Lie algebra’s, numerical analysis, fluid dynamics, perturbation theory, control theory, and mechanics. The chapters, which illustrate how symbolic computations can be used to study various mathematical structures, are outgrowths of the invited talks that were presented at the NASA Ames Workshop on The Use of Symbolic Methods to Solve Algebraic and Geometric Problems Arising in Engineering. More than 100 people participated in the two-day conference, which took place in January 1987 at the NASA Ames Research Center in Moffett Field, California.The field of symbolic computation is becoming increasingly important in science, engineering, and mathematics. The availability of powerful computer algebra systems on workstations has made symbolic computation an important tool for many researchers.

A practical handbook for understanding and using fast adaptive composite grid (FAC) methods for discretization and solution of partial differential equations (PDEs). Contains fundamental concepts.These so called FAC are characterized by their use of a composite grid, which is nominally the union of various uniform grids. FAC is capable of producing a composite grid with tailored resolution, and a corresponding solution with commensurate accuracy, at a cost proportional to the number of composite grid points. Moreover, special asynchronous versions of the fast adaptive composite grid methods (AFAC) studied here have seemingly optimal complexity in a parallel computing environment.Most of the methods treated in this book were discovered only within the last decade, and in many cases their development is still in its infancy. While this book is therefore not meant to be comprehensive, it does provide a theoretical and practical guide to multilevel adaptive methods and relevant discretization techniques. It also contains new material, which is included to fill in certain gaps and to expose new avenues of research. Also, because adaptive refinement seems to demand a lot of attention to philosophical issues, personal perspectives are often brought freely into the discussion.

Numerical grid generation plays a critical role in any scientific computing problem when the geometry of the underlying region is complex or when the solution has a complex structure. The mathematical aspects of grid generation are discussed here to provide a deeper understanding of the algorithms and their limitations. Variational methods are emphasized because they are more robust, but elliptic and transcendental algebraic methods are also considered.

This is the first book devoted entirely to total least squares. The authors give a unified presentation of the TLS problem. A description of its basic principles are given, the various algebraic, statistical and sensitivity properties of the problem are discussed, and generalizations are presented. Applications are surveyed to facilitate uses in an even wider range of applications. Whenever possible, comparison is made with the well-known least squares methods.A basic knowledge of numerical linear algebra, matrix computations, and some notion of elementary statistics is required of the reader; however, some background material is included to make the book reasonably self-contained.

The most comprehensive treatment of FFTs to date. Van Loan captures the interplay between mathematics and the design of effective numerical algorithms - a critical connection as more advanced machines become available. A stylized MATLAB notation, which is familiar to those engaged in high-performance computing, is used.The Fast Fourier Transform (FFT) family of algorithms has revolutionized many areas of scientific computation. The FFT is one of the most widely used algorithms in science and engineering, with applications in almost every discipline. This volume is essential for professionals interested in linear algebra as well as those working with numerical methods. The FFT is also a great vehicle for teaching key aspects of scientific computing.

Research in control and estimation of distributed parameter systems encompasses a wide range of applications including both fundamental science and emerging technologies. The latter include smart materials (piezoceramics, shape memory alloys, magnetostrictives, electrorheological fluids) fabrication and testing, design of high-pressure chemical vapor deposition (CVD) reactors for production of microelectronic surfaces (e.g., semiconductors), while the former include groundwater contamination cleanup and other environmental modeling questions, climatology, flow control, and fluid-structure interactions as well as more traditional topics in biology, mechanics, and acoustics. These expository papers provide substantial stimulus to both young researchers and experienced investigators in control theory.Includes a comprehensive and lucid presentation that relates frequency domain techniques to state-space or time domain approaches for infinite-dimensional systems including design of robust stabilizing and finite-dimensional controllers for infinite-dimensional systems. It focuses on these two approaches to control design in an integrated system theoretic framework. This is excellent reading for researchers in both the frequency domain and time domain control communities. In other articles, topics considered include pointwise control of distributed parameter systems, bounded and unbounded sensors and actuators, stabilization issues for large flexible structures, and an overview discussion of damping models for flexible structures.

Transonic aerodynamics, the study of the aerodynamics of flight at speeds near the speed of sound, warrants a great deal of attention from industry and science. As an airplane approaches Mach one, the drag steeply increases. This has prompted scientists to study transonic range of flight and to design reduced wing drag. Asymptotic theory of transonic aerodynamics forms the basis for this monograph. The equations governing transonic flow are inherently nonlinear and must ultimately be solved numerically. Asymptotic analysis simplifies and enriches both the theory and the computations of these flows. It reduces the number of parameters involved, can simplify the geometry, and clarifies near and fluid conditions.Transonic Aerodynamics offers exciting results, perspectives, and case studies for the treatment of problems arising in transonic aerodynamics. New advances including triple deck theory, analysis of stagnation at the nose of a body, transonic choked flow, and the transonic area rule are presented.Interest in analyzing the transonic range of flight, its stability properties, and especially the question of designing reduced drag (shockless or weak shock) airfoils keeps growing. Present day commercial aircraft cruise in the transonic range. Mechanical and aeronautical engineers interested in compressible fluid flows, design of optimal wings, and an understanding of transonic flow held about wings and airfoils will find the book invaluable.

Multilevel adaptive methods play an increasingly important role in the solution of many scientific and engineering problems. Fast adaptive methods techniques are widely used by specialists to execute and analyze simulation and optimization problems. This monograph presents a unified approach to adaptive methods, addressing their mathematical theory, efficient algorithms, and flexible data structures.Rüde introduces a well-founded mathematical theory that leads to intelligent, adaptive algorithms, and suggests advanced software techniques. This new kind of multigrid theory supports the so-called ""BPX"" and ""multilevel Schwarz"" methods, and leads to the discovery of faster more robust algorithms. These techniques are deeply rooted in the theory of function spaces. This book examines this development together with its implications for relevant algorithms for adaptive PDE methods. The author shows how abstract data types and object-oriented programming can be used for improved implementation.Special Features:Theory of multilevel (including additive) methods based on concepts in approximation theory and the theory of function spaces.Fully adaptive multigrid, based on the ""virtual global grid"" refinement technique and the ""multilevel adaptive relaxation"" algorithm.

Developments in optimization theory, including emphasis on large problems and on interior-point methods for linear programming, have begun to appear in production software. Here is a reference tool that includes discussions of these areas and names software packages that incorporate the results of theoretical research. After an introduction to the major problem areas in optimization and an outline of the algorithms used to solve them, a data sheet is presented for each of the 75 software packages and libraries in the authors' survey. These include information on the capabilities of the packages, how to obtain them, and addresses for further information.Standard optimization paradigms are addressed - linear, quadratic, and nonlinear programming; network optimization; unconstrained and bound-constrained optimization; least-squares problems; nonlinear equations; and integer programming. The most practical algorithms for the major fields of numerical optimization are outlined, and the software packages in which they are implemented are described. This format will aid current and potential users of optimization software in classifying the optimization problem to be solved, determining appropriate algorithms, and obtaining the software that implements those algorithms. Readers need only a basic knowledge of vector calculus and linear algebra to understand this book.

This book is devoted to giving a modern view of iterative methods for solving linear and nonlinear equations, which are the basis for many, if not most, of the models of phenomena in science and engineering; their efficient numerical solution is critical to progress in these areas. The text provides motivating examples mainly from boundary value problems with partial differential equations, and many of the chapters contain links to MATLAB code, which is provided per anonymous ftp by the author.This is the first book to be published on nonlinear equations since the mid-1980s. Although it stresses recent developments in this area, considerable material on linear equations has been incorporated. It focuses on a small number of methods and treats them in depth. The author provides a complete analysis of the conjugate gradient and generalized minimum residual iterations as well as recent advances including Newton-Krylov methods, incorporation of inexactness and noise into the analysis, new proofs and implementations of Broyden's method, and globalization of inexact Newton methods.Examples, methods, and algorithmic choices are based on applications to infinite dimensional problems such as partial differential equations and integral equations. The analysis and proof techniques are constructed with the infinite dimensional setting in mind and the computational examples and exercises are based on the MATLAB environment.

Much recent research has concentrated on the efficient solution of large sparse or structured linear systems using iterative methods. A language loaded with acronyms for a thousand different algorithms has developed, and it is often difficult even for specialists to identify the basic principles involved. Here is a book that focuses on the analysis of iterative methods. The author includes the most useful algorithms from a practical point of view and discusses the mathematical principles behind their derivation and analysis. Several questions are emphasized throughout: Does the method converge? If so, how fast? Is it optimal, among a certain class? If not, can it be shown to be near-optimal? The answers are presented clearly, when they are known, and remaining important open questions are laid out for further study.Greenbaum includes important material on the effect of rounding errors on iterative methods that has not appeared in other books on this subject. Additional important topics include a discussion of the open problem of finding a provably near-optimal short recurrence for non-Hermitian linear systems; the relation of matrix properties such as the field of values and the pseudospectrum to the convergence rate of iterative methods; comparison theorems for preconditioners and discussion of optimal preconditioners of specified forms; introductory material on the analysis of incomplete Cholesky, multigrid, and domain decomposition preconditioners, using the diffusion equation and the neutron transport equation as example problems. A small set of recommended algorithms and implementations is included.

This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality, and while it provides pointers to the literature for the most general theoretical results and robust software, the author thinks it is more important that readers have a complete understanding of special cases that convey essential ideas. A companion to Kelley’s book, Iterative Methods for Linear and Nonlinear Equations (SIAM, 1995), this book contains many exercises and examples and can be used as a text, a tutorial for self-study, or a reference.Iterative Methods for Optimization does more than cover traditional gradient-based optimization: it is the first book to treat sampling methods, including the Hooke–Jeeves, implicit filtering, MDS, and Nelder–Mead schemes in a unified way, and also the first book to make connections between sampling methods and the traditional gradient-methods. Each of the main algorithms in the text is described in pseudocode, and a collection of MATLAB codes is available. Thus, readers can experiment with the algorithms in an easy way as well as implement them in other languages.

Questions about stability arise in almost every control problem. There are many physical problems in which exponential stability is too strong and for which the concept of strong stability is appropriate. This book provides a solid mathematical framework for a structured approach to strongly stabilizable systems through integration of fundamental theory, physical applications, and numerical results. The author includes a mathematical framework for studying PDE models of large flexible structures, an important class of applications.The author's structured approach focuses on two themes: the development of system theoretic results for strongly stable systems, and the formulation of these results for a class of dissipative systems with collocated actuators and sensors. The tools set forth in this book extend the scope of applicability of PDE control techniques, including the important aspect of numerical approximation. Most importantly, the author justifies all theory by providing physical examples for which the theory is relevant.The book encompasses basic system theoretic notions, such as stability, stabilizability, detectability, coprime factorizations, and control related topics like Riccati equations, LQ optimal control, robust stabilization, nonlinear perturbations, and numerical approximation.

Electromagnetic theory offers fascination and challenge from both a physical and a mathematical perspective. This monograph contains the newest results on the use of electromagnetic probes to interrogate dielectric material structures for material properties and geometry. This volume systematically exploits interface phenomena, the electrodynamics of material responses, and time dependent interrogating signals in an integrated manner. The authors begin with basic electromagnetics, such as Maxwell's equations, and present modeling, theory, and computational results.The book's strengths include a clear discussion of materials properties from the electromagnetic point of view, a careful formulation of the imaging problems addressed, rigorous treatment of mathematical issues, and useful illustration of computational methods and results. While confined to internal vision in one-dimensional settings, this volume will stimulate further developments in internal vision to include two- and three-dimensional interior assessments. It is an excellent and robust source of applied mathematics and engineering research challenges for the future.Imaging technology stands to benefit much from this research on low energy electromagnetic radiation. The use of electromagnetic pulses interacting with specially placed reflective surfaces, whether solid or acoustic, is a new dimension that will substantively impact medical imaging, subsoil investigation, and structure evaluation.

This volume addresses recent developments in mathematical modeling in three areas of optical science: diffractive optics, photonic band gap structures, and waveguides. Particular emphasis is on the formulation of mathematical models and the design and analysis of new computational approaches. The book contains cutting-edge discourses on emerging technology in optics that provides significant challenges and opportunities for applied mathematicians, researchers, and engineers.Each of the three topics is presented through a series of survey papers to provide a broad overview focusing on the mathematical models. Chapters present model problems, physical principles, mathematical and computational approaches, and engineering applications corresponding to each of the three areas. Although some of the subject matter is classical, the topics presented are new and represent the latest developments in their respective fields.

Neural networks and fuzzy systems are model free control design approaches that represent an advantage over classical control when dealing with complicated nonlinear actuator dynamics. This book brings neural networks and fuzzy logic together with dynamical control systems. Each chapter presents powerful control approaches for the design of intelligent controllers to compensate for actuator nonlinearities such as time delay, friction, deadzone, and backlash that can be found in all industrial motion systems, plus a thorough development, rigorous stability proofs, and simulation examples for each design. In the final chapter, the authors develop a framework to implement intelligent control schemes on actual systems.Rigorous stability proofs are further verified by computer simulations, and appendices contain the computer code needed to build intelligent controllers for real-time applications. Neural networks capture the parallel processing and learning capabilities of biological nervous systems, and fuzzy logic captures the decision-making capabilities of human linguistics and cognitive systems.

Recent and ongoing improvements in computer technology have increased the need for efficient and reliable design tools; computational methods have opened the door to making sensitivity analysis a tractable design tool for industries that design and manufacture high-performance products. These industries are increasingly interested in exploiting the advantages of computer-aided design, numerical analysis, and optimal design methods. This book provides an understandable introduction to one approach to design sensitivity computation and illustrates some of the important mathematical and computational issues inherent in using the sensitivity equation method (SEM) for partial differential equations.The authors use basic models to illustrate the computational issues that one might encounter when applying the SEM in a laboratory or research setting, while providing an overview of applications and computational issues regarding sensitivity calculations performed by way of continuous sensitivity equation methods. Here they focus on the construction and analysis of algorithms for computing sensitivities. For readers already acquainted with the concept of a sensitivity equation, the authors include mathematical background for a deeper understanding of their approach. Finally, the book explores the use of SEMs for applications in the area of computational fluid dynamics, demonstrating that the early examples readers encounter in the book can be observed in the context of a more realistic physical setting. Several color figures are included.

This book is composed of eleven chapters, written by experts in their respective fields, on topics ranging from control of the Navier-Stokes equations to nondestructive evaluation – all of which are modeled by distributed parameters systems. Written by the plenary speakers for the Conference on Future Directions in Distributed Parameter Systems (October 2000), the volume addresses the state of the art, open questions, and important research directions in applications modeled by partial differential equations and delay systems, with the ultimate goal of passing along these perspectives to researchers in the field.This book compiles a broad range of material, much of which is available only in research journals. Its goal is to disseminate to the research community the perspectives and challenges posed for a variety of current research applications. Topics include electromagnetic theory for dielectric and conductive materials, flow control, cardiovascular and respiratory models, homogenization and systems theory, optimal and geometric control, reduced-order models for large-scale systems, smart materials, and nondestructive evaluation and structural health monitoring for systems, including nuclear power plants. A unifying theme throughout the book focuses on the necessity of considering model development, numerical approximation, parameter estimation through inverse problem techniques, and control design in concert to achieve the stringent design criteria dictated by present applications.Research Directions in Distributed Parameter Systems is intended for graduate students, academic and industrial research scientists, and program managers from funding agencies supporting research focused on distributed parameter systems.

Globalization and the possibility of bioterrorist acts have highlighted the pressing need for the development of theoretical and practical mathematical frameworks that may be useful in our systemic efforts to anticipate, prevent, and respond to acts of destabilization.This book collects the detailed contributions of selected groups of experts from the fields of biostatistics, control theory, epidemiology, and mathematical biology who have engaged in the development of frameworks, models, and mathematical methods needed to address some of the pressing challenges posed by acts of terror. The ten chapters of this volume touch on a large range of issues in the subfields of biosurveillance, agroterrorism, bioterror response logistics, deliberate release of biological agents, impact assessment, and the spread of fanatic behaviours.

Bioconsensus is a rapidly evolving scientific field in which consensus methods, often developed for use in social choice theory, are adapted for such areas of the biological sciences as taxonomy, systematics, and evolutionary and molecular biology. Typically, after several alternatives are produced using different data sets, methods or algorithms, one needs to find a consensus solution.The axiomatic approach of this book explores the existence or nonexistence of consensus rules that satisfy particular sets of desirable well-defined properties. The axiomatic research reviewed here focuses first on the area of group choice, then in areas of biomathematics where the objects of interest represent partitions of a set, hierarchical structures, phylogenetic trees, or molecular sequences.This book provides a unique comprehensive review of axiomatic consensus theory in biomathematics as it has developed over the past 30 years. Established here are the theory’s basic results using standard terminology and notation and with uniform attention to rigor and detail. This book cites both traditional and current literature and poses open problems that remain to be solved. The bibliographic notes in each chapter place the described work within a general context while providing useful pointers to relevant research. The bibliographic references are a valuable resource for both students and experts in the field.

Here is a book for anyone who would like to become better acquainted with the modern tools of numerical analysis for several significant computational problems arising in finance. The authors review some important aspects of finance modeling involving partial differential equations and focus on numerical algorithms for the fast and accurate pricing of financial derivatives and for the calibration of parameters.Option pricing has become a technical topic that requires sophisticated numerical methods for robust and fast numerical solutions. This book explores the best numerical algorithms and discusses them in depth, from their mathematical analysis up to their implementation in C with efficient numerical libraries. Much of this information is not available elsewhere. In particular, this is one of the few books that gives detailed coverage of the following topics:Mathematical results and efficient algorithms for pricing American options.Modern algorithms with adaptive mesh refinement for European and American options. Regularity and error estimates are derived and give strong support to the mesh adaptivity, an essential tool for speeding up the numerical implementations.Calibration of volatility with European and American options. The use of automatic differentiation of computer codes for computing gree.

Gender-Structured Population Modeling gives a unified presentation of and mathematical framework for modeling population growth by couple formation. It provides an overview of both past and present modeling results. The authors focus on pair formation (marriage) and two-sex models with different forms of the marriage function - the basis of couple formation - and discuss which of these forms might make a better choice for a particular population (the United States). It also provides results on model analysis, gives an up-to-date review of mathematical demography, discusses numerical methods, and puts deterministic modeling of human populations into historical perspective.The authors describe several models and derive the theoretical results that demonstrate the validity of these models. The numerical methods for approximating the solutions of the differential models - the equivalent of creating discrete simulators - are delineated. Simulation results are compared with actual demographic data to show some of the difficulties concerning the availability of data and to show that mathematical demography provides reasonable qualitative and quantitative estimates. The models in this book can be applied to different sets of data.

Smart Material Systems describes several novel applications currently under investigation that exploit the unique actuator and sensor capabilities of smart material compounds. In addition to present and projected applications, this book provides comprehensive coverage of both linear and nonlinear modeling techniques necessary to characterize materials in a manner that facilitates transducer design and control development. The author focuses on ferroelectric, magnetic, and shape memory compounds and also addresses applications exploiting amorphous and ionic polymers, magnetorheological compounds, and fiber optic sensors.Three classes of nonlinear models are discussed, all of which provide unified characterization frameworks for the broad class of combined compounds. An extensive discussion of structural models based on linear and nonlinear constitutive models is included, as is a chapter on numerical techniques for approximating solutions to the structural systems. The author also provides a synergistic treatment of material characterization, including significant discussion of the physics underlying nonlinear behavior, the development of nonlinear constitutive relations, the development of system models based on these constitutive relations, and the formulation of numerical techniques for approximating solutions to the resulting system models. To aid the understanding of both mathematical and physical terminology, an extensive glossary of terms is provided in an appendix. Furthermore, MATLAB software for representative models is provided at an accompanying website.By providing a unified treatment of both linear and nonlinear characterization frameworks, Smart Material Systems encompasses both low to moderate drive levels, which constitute the primary focus of most present texts, and the high drive regimes dictated by present and future applications. This will significantly enhance the design of transducers and control systems which exploit the unique actuator and sensor capabilities provided by smart material compounds.

Interface problems arise when there are two different materials, such as water and oil, or the same material at different states, such as water and ice. If partial or ordinary differential equations are used to model these applications, the parameters in the governing equations are typically discontinuous across the interface separating the two materials or states, and the source terms are often singular to re?ect source/sink distributions along codimensional interfaces. Because of these irregularities, the solutions to the differential equations are typically nonsmooth or even discontinuous. As a result, many standard numerical methods based on the assumption of smoothness of solutions do not work or work poorly for interface problems.The Immersed Interface Method provides an introduction to the immersed interface method (IIM), a powerful numerical method for solving interface problems and problems defined on irregular domains for which analytic solutions are rarely available. This book gives a complete description of the IIM, discusses recent progress in the area, and describes numerical methods for a number of classic interface problems. It also contains many numerical examples that can be used as benchmark problems for numerical methods designed for interface problems on irregular domains.The IIM is a sharp interface method that has been coupled with evolution schemes such as the level set and front tracking methods and has been used in both finite difference and finite element formulations to solve several moving interface and free boundary problems. In particular, the authors discuss the IIM’s applications to Stefan problems and unstable crystal growth, incompressible Stokes and Navier–Stokes flows with moving interfaces, an inverse problem identifying unknown shapes in a region, a nonlinear interface problem of magnetorheological ?uids containing iron particles, and other problems. The book also contains several applications of free boundary and moving interface problems, including examples from physics, computational fluid mechanics, mathematical biology, material science, and other fields.The IIM, which is based on uniform or adaptive Cartesian/polar/spherical grids or triangulations, is simple enough to be implemented by researchers and graduate students with a reasonable background in differential equations and numerical analysis yet powerful enough to solve complicated problems with high-order accuracy. Since interfaces or irregular boundaries are one dimension lower than solution domains, the extra costs in dealing with interfaces or irregular boundaries are generally insigni?cant, and many software packages based on uniform Cartesian/polar/spherical grids, such as the FFT and fast Poisson solvers, can be applied easily with the IIM. The most recent IIM computer codes and packages are available online.

The human cardiovascular and respiratory control systems represent an important focal point for developing physiological control theory because of the complexity of the control mechanisms involved, the interaction between cardiovascular and respiratory func¬tion, and the importance of this interaction in many clinical situations. This volume brings together the range of control processes involved in the effective regulation of these systems and develops modeling themes, strategies, and key clinical applications using contemporary mathematical and control methodologies. The reader will gain an appreciation of how analytical techniques and ideas from optimal control theory, systems theory, and numerical analysis can be utilized to better understand the regulation processes in human cardiovascular and respiratory systems.Cardiovascular and Respiratory Systems uses a principle-based modeling approach and analysis of feedback control regulation to elucidate the physiological relationships. Models are arranged around specific questions or conditions, such as exercise or sleep transition, and are generally based on physiological mechanisms rather than on formal descriptions of input-output behavior. The authors ask open questions relevant to medical and clinical applications and clarify underlying themes of physiological control organization. Current problems, key issues, developing trends, and unresolved questions are highlighted.

Discontinuous Galerkin (DG) methods for solving partial differential equations, developed in the late 1990s, have become popular among computational scientists. This book covers both theory and computation as it focuses on three primal DG methods - the symmetric interior penalty Galerkin, incomplete interior penalty Galerkin, and nonsymmetric interior penalty Galerkin - which are variations of interior penalty methods. The author provides the basic tools for analysis and discusses coding issues, including data structure, construction of local matrices, and assembling of the global matrix. Computational examples and applications to important engineering problems are also included.Discontinuous Galerkin Methods for Solving Elliptic and Parabolic Equation is divided into three parts: Part I focuses on the application of DG methods to second order elliptic problems in one dimension and in higher dimensions. Part II presents the time-dependent parabolic problems—without and with convection. Part III contains applications of DG methods to solid mechanics (linear elasticity), ?uid dynamics (Stokes and Navier–Stokes), and porous media ?ow (two-phase and miscible displacement).Appendices contain proofs and MATLAB® code for one-dimensional problems for elliptic equations and routines written in C that correspond to algorithms for the implementation of DG methods in two or three dimensions.

The emergence of complex enhanced recovery procedures in the field of hydrocarbon extraction techniques has emphasized the need for sophisticated mathematical tools, capable of modeling intricate chemical and physical phenomena and sharply changing fluid interfaces. This volume explains which problems need to be addressed, why they are difficult, what has been done previously to treat these difficulties, and which new techniques appear to possess potential for obtaining good simulation results.