Large Eddy Simulation of Complex Engineering and Geophysical Flows

Large Eddy Simulation of Complex Engineering and Geophysical Flows Review

Originally published in 1993, this book was the first to offer a comprehensive review of large eddy simulations (LES) - the history, state of the art, and promising directions for research. Among topics covered are fundamentals of LES; LES of incompressible, compressible, and reacting flows; LES of atmospheric, oceanic, and environmental flows; and LES and massivelt parallel computing. The book grew out of an international workshop that, for the first time, brought together leading researchers in engineering and geophysics to discuss developments and applications of LES models in their respective fields. It will be of value to anyone with an interest in turbulence modelling.

Simulation-Based Econometric Methods (Core Lectures)

Simulation-Based Econometric Methods (Core Lectures) Review

This book introduces a new generation of statistical econometrics. After linear models leading to analytical expressions for estimators, and non-linear models using numerical optimization algorithms, the availability of high- speed computing has enabled econometricians to consider econometric models without simple analytical expressions. The previous difficulties presented by the presence of integrals of large dimensions in the probability density functions or in the moments can be circumvented by a simulation-based approach.

After a brief survey of classical parametric and semi-parametric non-linear estimation methods and a description of problems in which criterion functions contain integrals, the authors present a general form of the model where it is possible to simulate the observations. They then move to calibration problems and the simulated analogue of the method of moments, before considering simulated versions of maximum likelihood, pseudo-maximum likelihood, or non-linear least squares. The general principle of indirect inference is presented and is then applied to limited dependent variable models and to financial series.

Clinical Trial Simulations: Applications and Trends (AAPS Advances in the Pharmaceutical Sciences Series)

Clinical Trial Simulations: Applications and Trends (AAPS Advances in the Pharmaceutical Sciences Series) Review

This edition includes both updates and new uses and issues concerning CTS, along with case studies of how clinical trial simulations are being applied in various therapeutic and application areas. Importantly, the book expands on the utility of CTS for informing decisions during drug development and regulatory review. Each chapter author was selected on the basis of demonstrated expertise in state-of-the-art application of CTS. The target audience for this volume includes researchers and scientists who wish to consider use of simulations in the design, analysis, or regulatory review and guidance of clinical trials. This book does not embrace all aspects of trial design, nor is it intended as a complete recipe for using computers to design trials. Rather, it is an information source that enables the reader to gain understanding of essential background and knowledge for practical applications of simulation for clinical trial design and analysis. It is assumed that the reader has a working understanding of pharmacokinetics and pharmacodynamics, modeling, pharmacometric analyses, and/or the drug development and regulatory processes.

Introduction to Computational Science: Modeling and Simulation for the Sciences

Introduction to Computational Science: Modeling and Simulation for the Sciences Review

Computational science is a quickly emerging field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. However, limited educational materials exist in this field. Introduction to Computational Science fills this void with a flexible, readable textbook that assumes only a background in high school algebra and enables instructors to follow tailored pathways through the material. It is the first textbook designed specifically for an introductory course in the computational science and engineering curriculum.

The text embraces two major approaches to computational science problems: System dynamics models with their global views of major systems that change with time; and cellular automaton simulations with their local views of how individuals affect individuals. While the text is generic, an extensive author-generated Web-site contains tutorials and files in a variety of software packages to accompany the text.

• Generic software approach in the text
• Web site with tutorials and files in a variety of software packages
• Engaging examples, exercises, and projects that explore science
• Additional, substantial projects for students to develop individually or in teams
• Consistent application of the modeling process
• Quick review questions and answers
• Projects for students to develop individually or in teams
• Reference sections for most modules, as well as a glossary
• Online instructor's manual with a test bank and solutions

Simulation of Dynamic Systems with MATLAB and Simulink, Second Edition

Simulation of Dynamic Systems with MATLAB and Simulink, Second Edition Review

"… a seminal text covering the simulation design and analysis of a broad variety of systems using two of the most modern software packages available today. … particularly adept [at] enabling students new to the field to gain a thorough understanding of the basics of continuous simulation in a single semester, and [also provides] a more advanced treatment of the subject for researchers and simulation professionals."

—From the Foreword by Chris Bauer, PhD, PE, CMSP

Continuous-system simulation is an increasingly important tool for optimizing the performance of real-world systems, and a massive transformation has occurred in the application of simulation in fields ranging from engineering and physical sciences to medicine, biology, economics, and applied mathematics. As with most things, simulation is best learned through practice—but explosive growth in the field requires a new learning approach.

A response to changes in the field, Simulation of Dynamic Systems with MATLAB® and Simulink®, Second Edition has been extensively updated to help readers build an in-depth and intuitive understanding of basic concepts, mathematical tools, and the common principles of various simulation models for different phenomena.

Includes an abundance of case studies, real-world examples, homework problems, and equations to develop a practical understanding of concepts

Accomplished experts Harold Klee and Randal Allen take readers through a gradual and natural progression of important topics in simulation, introducing advanced concepts only after they construct complete examples using fundamental methods. Presented exercises incorporate MATLAB® and Simulink®—including access to downloadable M-files and model files—enabling both students and professionals to gain experience with these industry-standard tools and more easily design, implement, and adjust simulation models in their particular field of study.

More universities are offering courses—as well as masters and Ph.D programs—in both continuous-time and discrete-time simulation, promoting a new interdisciplinary focus that appeals to undergraduates and beginning graduates from a wide range of fields. Ideal for such courses, this classroom-tested introductory text presents a flexible, multifaceted approach through which simulation can play a prominent role in validating system design and training personnel involved.

Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics)

Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics) Review

This accessible new edition explores the major topics in Monte Carlo simulation

Simulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences.

The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including:

• Markov Chain Monte Carlo
• Variance reduction techniques such as the transform likelihood ratio method and the screening method
• The score function method for sensitivity analysis
• The stochastic approximation method and the stochastic counter-part method for Monte Carlo optimization
• The cross-entropy method to rare events estimation and combinatorial optimization
• Application of Monte Carlo techniques for counting problems, with an emphasis on the parametric minimum cross-entropy method

An extensive range of exercises is provided at the end of each chapter, with more difficult sections and exercises marked accordingly for advanced readers. A generous sampling of applied examples is positioned throughout the book, emphasizing various areas of application, and a detailed appendix presents an introduction to exponential families, a discussion of the computational complexity of stochastic programming problems, and sample MATLAB programs.

Requiring only a basic, introductory knowledge of probability and statistics, Simulation and the Monte Carlo Method, Second Edition is an excellent text for upper-undergraduate and beginning graduate courses in simulation and Monte Carlo techniques. The book also serves as a valuable reference for professionals who would like to achieve a more formal understanding of the Monte Carlo method.

Discrete-Event System Simulation (5th Edition)

Discrete-Event System Simulation (5th Edition) Review

Discrete Event System Simulationis ideal for junior- and senior-level simulation courses in engineering, business, or computer science. It is also a  useful reference for professionals in operations research, management science, industrial engineering, and information science.

While most books on simulation focus on particular software tools, Discrete Event System Simulation examines the principles of modeling and analysis that translate to all such tools. This language-independent text explains the basic aspects of the technology, including the proper collection and analysis of data, the use of analytic techniques, verification and validation of models, and designing simulation experiments. It offers an up-to-date treatment of simulation of manufacturing and material handling systems, computer systems, and computer networks.

Students and instructors will find a variety of resources at the associated website, www.bcnn.net/, including simulation source code for download, additional exercises and solutions, web links and errata.