An Introduction to Network Modeling and Simulation for the Practicing Engineer

Introduces readers to the field of cyber modeling and simulation and examines current developments in the US and internationally This book provides an overview of cyber modeling and simulation (M&S) developments. Using scenarios, courses of action (COAs), and current M&S and simulation environments, the author presents the overall information assurance process, incorporating the people, policies, processes, and technologies currently available in the field. The author ties up the various threads that currently compose cyber M&S into a coherent view of what is measurable, simulative, and usable in order to evaluate systems for assured operation. An Introduction to Cyber Modeling and Simulation provides the reader with examples of tools and technologies currently available for performing cyber modeling and simulation. It examines how decision-making processes may benefit from M&S in cyber defense. It also examines example emulators, simulators and their potential combination. The book also takes a look at corresponding verification and validation (V&V) processes, which provide the operational community with confidence in knowing that cyber models represent the real world. This book: Explores the role of cyber M&S in decision making Provides a method for contextualizing and understanding cyber risk Shows how concepts such the Risk Management Framework (RMF) leverage multiple processes and policies into a coherent whole Evaluates standards for pure IT operations, «cyber for cyber,» and operational/mission cyber evaluations—"cyber for others" Develops a method for estimating both the vulnerability of the system (i.e., time to exploit) and provides an approach for mitigating risk via policy, training, and technology alternatives Uses a model-based approach An Introduction to Cyber Modeling and Simulation is a must read for all technical professionals and students wishing to expand their knowledge of cyber M&S for future professional work.

Network Modeling and Simulation is a practical guide to using modeling and simulation to solve real-life problems. The authors give a comprehensive exposition of the core concepts in modeling and simulation, and then systematically address the many practical considerations faced by developers in modeling complex large-scale systems. The authors provide examples from computer and telecommunication networks and use these to illustrate the process of mapping generic simulation concepts to domain-specific problems in different industries and disciplines. Key features: Provides the tools and strategies needed to build simulation models from the ground up rather than providing solutions to specific problems. Includes a new simulation tool, CASiNO built by the authors. Examines the core concepts of systems simulation and modeling. Presents code examples to illustrate the implementation process of commonly encountered simulation tasks. Offers examples of industry-standard modeling methodology that can be applied in steps to tackle any modeling problem in practice.

Master modeling and simulation using Modelica, the new powerful, highly versatile object-based modeling language Modelica, the new object-based software/hardware modeling language that is quickly gaining popularity around the world, offers an almost universal approach to high-level computational modeling and simulation. It handles a broad range of application domains, for example mechanics, electrical systems, control, and thermodynamics, and facilitates general notation as well as powerful abstractions and efficient implementations. Using the versatile Modelica language and its associated technology, this text presents an object-oriented, component-based approach that makes it possible for readers to quickly master the basics of computer-supported equation-based object-oriented (EOO) mathematical modeling and simulation. Throughout the text, Modelica is used to illustrate the various aspects of modeling and simulation. At the same time, a number of key concepts underlying the Modelica language are explained with the use of modeling and simulation examples. This book: Examines basic concepts such as systems, models, and simulations Guides readers through the Modelica language with the aid of several step-by-step examples Introduces the Modelica class concept and its use in graphical and textual modeling Explores modeling methodology for continuous, discrete, and hybrid systems Presents an overview of the Modelica Standard Library and key Modelica model libraries Readers will find plenty of examples of models that simulate distinct application domains as well as examples that combine several domains. All the examples and exercises in the text are available via DrModelica. This electronic self-teaching program, freely available on the text's companion website, guides readers from simple, introductory examples and exercises to more advanced ones. Written by the Director of the Open Source Modelica Consortium, Introduction to Modeling and Simulation of Technical and Physical Systems with Modelica is recommended for engineers and students interested in computer-aided design, modeling, simulation, and analysis of technical and natural systems. By building on basic concepts, the text is ideal for students who want to learn modeling, simulation, and object orientation.

Uses mathematical, numerical, and programming tools to solve differential equations for physical phenomena and engineering problems Introduction to Computation and Modeling for Differential Equations, Second Edition features the essential principles and applications of problem solving across disciplines such as engineering, physics, and chemistry. The Second Edition integrates the science of solving differential equations with mathematical, numerical, and programming tools, specifically with methods involving ordinary differential equations; numerical methods for initial value problems (IVPs); numerical methods for boundary value problems (BVPs); partial differential equations (PDEs); numerical methods for parabolic, elliptic, and hyperbolic PDEs; mathematical modeling with differential equations; numerical solutions; and finite difference and finite element methods. The author features a unique “Five-M” approach: Modeling, Mathematics, Methods, MATLAB®, and Multiphysics, which facilitates a thorough understanding of how models are created and preprocessed mathematically with scaling, classification, and approximation and also demonstrates how a problem is solved numerically using the appropriate mathematical methods. With numerous real-world examples to aid in the visualization of the solutions, Introduction to Computation and Modeling for Differential Equations, Second Edition includes: New sections on topics including variational formulation, the finite element method, examples of discretization, ansatz methods such as Galerkin’s method for BVPs, parabolic and elliptic PDEs, and finite volume methods Numerous practical examples with applications in mechanics, fluid dynamics, solid mechanics, chemical engineering, heat conduction, electromagnetic field theory, and control theory, some of which are solved with computer programs MATLAB and COMSOL Multiphysics® Additional exercises that introduce new methods, projects, and problems to further illustrate possible applications A related website with select solutions to the exercises, as well as the MATLAB data sets for ordinary differential equations (ODEs) and PDEs Introduction to Computation and Modeling for Differential Equations, Second Edition is a useful textbook for upper-undergraduate and graduate-level courses in scientific computing, differential equations, ordinary differential equations, partial differential equations, and numerical methods. The book is also an excellent self-study guide for mathematics, science, computer science, physics, and engineering students, as well as an excellent reference for practitioners and consultants who use differential equations and numerical methods in everyday situations.

Providing engineers with the tools and skills to survive and become successful in the work place Gives experience-based, highly realistic guidance to a cross-section of young and even established engineers Delivers practical guidance and acts as a handy resource so that lessons do not have to be learned the hard way with numerous errors, and costly problems Includes real world examples and case studies from a 45 year veteran in the engineering field

This book is a quantitative text, which focuses on the real issues behind serious modeling and analysis of communications networks. The author covers all the necessary mathematics and theory in order for students to understand the tools that optimize computer networks today. Covers both classical (e.g. queueing theory) and modern (e.g. pricing) aspects of networking Integrates material on communication networks with material on modeling/analyzing and designing such networks Includes a Solution Manual

A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques An Introduction to Statistical Computing: Fully covers the traditional topics of statistical computing. Discusses both practical aspects and the theoretical background. Includes a chapter about continuous-time models. Illustrates all methods using examples and exercises. Provides answers to the exercises (using the statistical computing environment R); the corresponding source code is available online. Includes an introduction to programming in R. This book is mostly self-contained; the only prerequisites are basic knowledge of probability up to the law of large numbers. Careful presentation and examples make this book accessible to a wide range of students and suitable for self-study or as the basis of a taught course

This edited book is divided into three parts: Fundamentals of Medical and Health Sciences Modeling and Simulation introduces modeling and simulation in the medical and health sciences; Medical and Health Sciences Models provides the theoretical underpinnings of medical and health sciences modeling; and Modeling and Simulation Applications in Medical and Health Sciences focuses on teaching, training, and research applications. The book begins with a general discussion of modeling and simulation from the modeling and simulation discipline perspective. This discussion grounds the reader in common terminology. It also relates this terminology to concepts found in the medical and health care (MHC) area to help bridge the gap between developers and MHC practitioners. Three distinct modes of modeling and simulation are described: live, constructive, and virtual. The live approach explains the concept of using real (live) people employing real equipment for training purposes. The constructive mode is a means of engaging medical modeling and simulation. In constructive simulation, simulated people and simulated equipment are developed to augment real-world conditions for training or experimentation purposes. The virtual mode is perhaps the most fascinating as virtual operating rooms and synthetic training environments are being produced for practitioners and educators at break-neck speed. In this mode, real people are employing simulated equipment to improve physical skills and decision-making ability.

This highly accessible book provides analytical methods and guidelines for solving vibration problems in industrial plants and demonstrates their practical use through case histories from the author's personal experience in the mechanical engineering industry. It takes a simple, analytical approach to the subject, placing emphasis on practical applicability over theory, and covers both fixed and rotating equipment, as well as pressure vessels. It is an ideal guide for readers with diverse experience, ranging from undergraduate students to mechanics and professional engineers.

An introduction to state-of-the-art modeling and simulation approaches for social and economic determinants of population health New Horizons in Modeling and Simulation for Social Epidemiology and Public Health offers a comprehensive introduction to modeling and simulation that addresses the many complex research questions in social epidemiology and public health. This book highlights a variety of practical applications and illustrative examples with a focus on modeling and simulation approaches for the social and economic determinants of population health. The book contains classic case examples in agent-based modeling (ABM) as well as essential information on ABM applications to public health including for infectious disease modeling, obesity, and tobacco control. This book also surveys applications of microsimulation (MSM) including of tax-benefit policies to project impacts of the social determinants of health. Specifically, this book: Provides an overview of the social determinants of health and the public health significance of addressing the social determinants of health Gives a conceptual foundation for the application of ABM and MSM to study the social determinants of health Offers methodological introductions to both ABM and MSM approaches with illustrative examples Includes cutting-edge systematic reviews of empirical applications of ABM and MSM in the social sciences, social epidemiology, and public health Discusses future directions for empirical research using ABM and MSM, including integrating aspects of both ABM and MSM and implications for public health policies Written for a broad audience of policy analysts, public planners, and researchers and practitioners in public health and public policy including social epidemiologists, New Horizons in Modeling and Simulation for Social Epidemiology and Public Health offers a fundamental guide to the social determinants of health and state-of-the-art applications of ABM and MSM to studying the social and economic determinants of population health.