Model Engineering For Simulation

Book Description :

Model Engineering for Simulation provides a systematic introduction to the implementation of generic, normalized and quantifiable modeling and simulation using DEVS formalism. It describes key technologies relating to model lifecycle management, including model description languages, complexity analysis, model management, service-oriented model composition, quantitative measurement of model credibility, and model validation and verification. The book clearly demonstrates how to construct computationally efficient, object-oriented simulations of DEVS models on parallel and distributed environments. Guides systems and control engineers in the practical creation and delivery of simulation models using DEVS formalism Provides practical methods to improve credibility of models and manage the model lifecycle Helps readers gain an overall understanding of model lifecycle management and analysis Supported by an online ancillary package that includes an instructors and student solutions manual

Book Description :

This practical book presents fundamental concepts and issues in computer modeling and simulation (M&S) in a simple and practical way for engineers, scientists, and managers who wish to apply simulation successfully to their real-world problems. It offers a concise approach to the coverage of generic (tool-independent) M&S concepts and enables engineering practitioners to easily learn, evaluate, and apply various available simulation concepts. Worked out examples are included to illustrate the concepts and an example modeling application is continued throughout the chapters to demonstrate the techniques. The book discusses modeling purposes, scoping a model, levels of modeling abstraction, the benefits and cost of including randomness, types of simulation, and statistical techniques. It also includes a chapter on modeling and simulation projects and how to conduct them for customer and engineer benefit and covers the stages of a modeling and simulation study, including process and system investigation, data collection, modeling scoping and production, model verification and validation, experimentation, and analysis of results.

Book Description :

This unique text/reference provides a comprehensive review of distributed simulation (DS) from the perspective of Model Driven Engineering (MDE), illustrating how MDE affects the overall lifecycle of the simulation development process. Numerous practical case studies are included to demonstrate the utility and applicability of the methodology, many of which are developed from tools available to download from the public domain. Topics and features: Provides a thorough introduction to the fundamental concepts, principles and processes of modeling and simulation, MDE and high-level architecture Describes a road map for building a DS system in accordance with the MDE perspective, and a technical framework for the development of conceptual models Presents a focus on federate (simulation environment) architectures, detailing a practical approach to the design of federations (i.e., simulation member design) Discusses the main activities related to scenario management in DS, and explores the process of MDE-based implementation, integration and testing Reviews approaches to simulation evolution and modernization, including architecture-driven modernization for simulation modernization Examines the potential synergies between the agent, DS, and MDE methodologies, suggesting avenues for future research at the intersection of these three fields Distributed Simulation – A Model Driven Engineering Approach is an important resource for all researchers and practitioners involved in modeling and simulation, and software engineering, who may be interested in adopting MDE principles when developing complex DS systems.

Book Description :

This comprehensive text presents cutting-edge advances in the theory and methodology of modeling and simulation (M&S) and reveals how this work has been influenced by the fundamental contributions of Prof. Tuncer Ören to this field. Exploring the synergies among the domains of M&S and systems engineering (SE), the book describes how M&S and SE can help to address the complex problems identified as “Grand Challenges” more effectively under a model-driven and simulation-directed systems engineering framework. Features: examines frameworks for the development of advanced simulation methodologies; presents a focus on advanced modeling methodologies; reviews the reliability and quality assurance of models; discusses the specification and simulation of human and social behavior, including models of personality, emotions, conflict management, perception and anticipation; provides a survey of the body of knowledge in M&S; highlights the foundations established by the pioneering work of Prof. Tuncer Ören.

Book Description :

This illuminating text/reference presents a review of the key aspects of the modeling and simulation (M&S) life cycle, and examines the challenges of M&S in different application areas. The authoritative work offers valuable perspectives on the future of research in M&S, and its role in engineering complex systems. Topics and features: reviews the challenges of M&S for urban infrastructure, healthcare delivery, automated vehicle manufacturing, deep space missions, and acquisitions enterprise; outlines research issues relating to conceptual modeling, covering the development of explicit and unambiguous models, communication and decision-making, and architecture and services; considers key computational challenges in the execution of simulation models, in order to best exploit emerging computing platforms and technologies; examines efforts to understand and manage uncertainty inherent in M&S processes, and how these can be unified under a consistent theoretical and philosophical foundation; discusses the reuse of models and simulations to accelerate the simulation model development process. This thought-provoking volume offers important insights for all researchers involved in modeling and simulation across the full spectrum of disciplines and applications, defining a common research agenda to support the entire M&S research community.

Book Description :

Computer simulation is the key to comprehending and controlling the full-scale industrial plant used in the chemical, oil, gas and electrical power industries. Simulation of Industrial Processes for Control Engineers shows how to use the laws of physics and chemistry to produce the equations to simulate dynamically all the most important unit operations found in process and power plant. The book explains how to model chemical reactors, nuclear reactors, distillation columns, boilers, deaerators, refrigeration vessels, storage vessels for liquids and gases, liquid and gas flow through pipes and pipe networks, liquid and gas flow through installed control valves, control valve dynamics (including nonlinear effects such as static friction), oil and gas pipelines, heat exchangers, steam and gas turbines, compressors and pumps, as well as process controllers (including three methods of integral desaturation). The phenomenon of markedly different time responses ("stiffness") is considered and various ways are presented to get around the potential problem of slow execution time. The book demonstrates how linearization may be used to give a diverse check on the correctness of the as-programmed model and explains how formal techniques of model validation may be used to produce a quantitative check on the simulation model's overall validity. The material is based on many years' experience of modelling and simulation in the chemical and power industries, supplemented in recent years by university teaching at the undergraduate and postgraduate level. Several important new results are presented. The depth is sufficient to allow real industrial problems to be solved, thus making the book attractive to engineers working in industry. But the book's step-by-step approach makes the text appropriate also for post-graduate students of control engineering and for undergraduate students in electrical, mechanical and chemical engineering who are studying process control in their second year or later.

Book Description :

This comprehensive book examines a range of examples, prepared by a diverse group of academic and industry practitioners, which demonstrate how cloud-based simulation is being extensively used across many disciplines, including cyber-physical systems engineering. This book is a compendium of the state of the art in cloud-based simulation that instructors can use to inform the next generation. It highlights the underlying infrastructure, modeling paradigms, and simulation methodologies that can be brought to bear to develop the next generation of systems for a highly connected society. Such systems, aptly termed cyber-physical systems (CPS), are now widely used in e.g. transportation systems, smart grids, connected vehicles, industrial production systems, healthcare, education, and defense. Modeling and simulation (M&S), along with big data technologies, are at the forefront of complex systems engineering research. The disciplines of cloud-based simulation and CPS engineering are evolving at a rapid pace, but are not optimally supporting each other’s advancement. This book brings together these two communities, which already serve multi-disciplinary applications. It provides an overview of the simulation technologies landscape, and of infrastructure pertaining to the use of cloud-based environments for CPS engineering. It covers the engineering, design, and application of cloud simulation technologies and infrastructures applicable for CPS engineering. The contributions share valuable lessons learned from developing real-time embedded and robotic systems deployed through cloud-based infrastructures for application in CPS engineering and IoT-enabled society. The coverage incorporates cloud-based M&S as a medium for facilitating CPS engineering and governance, and elaborates on available cloud-based M&S technologies and their impacts on specific aspects of CPS engineering.

Book Description :

The capability modeling and simulation (M&S) supplies for managing systems complexity and investigating systems behaviors has made it a central activity in the development of new and existing systems. However, a handbook that provides established M&S practices has not been available. Until now. Modeling and Simulation-Based Systems Engineering Handbook details the M&S practices for supporting systems engineering in diverse domains. It discusses how you can identify systems engineering needs and adapt these practices to suit specific application domains, thus avoiding redefining practices from scratch. Although M&S practices are used and embedded within individual disciplines, they are often developed in isolation. However, they address recurring problems common to all disciplines. The editors of this book tackled the challenge by recruiting key representatives from several communities, harmonizing the different perspectives derived from individual backgrounds, and lining them up with the book’s vision. The result is a collection of M&S systems engineering examples that offer an initial means for cross-domain capitalization of the knowledge, methodologies, and technologies developed in several communities. These examples provide the pros and cons of the methods and techniques available, lessons learned, and pitfalls to avoid. As our society moves further in the information era, knowledge and M&S capabilities become key enablers for the engineering of complex systems and systems of systems. Therefore, knowledge and M&S methodologies and technologies become valuable output in an engineering activity, and their cross-domain capitalization is key to further advance the future practices in systems engineering. This book collates information across disciplines to provide you with the tools to more efficiently design and manage complex systems that achieve their goals.

Book Description :

Chemical Engineering Process Simulation, Second Edition guides users through chemical processes and unit operations using the main simulation software used in the industrial sector. The book helps predict the characteristics of a process using mathematical models and computer-aided process simulation tools, as well as how to model and simulate process performance before detailed process design takes place. Content coverage includes steady-state and dynamic simulation, process design, control and optimization. In addition, readers will learn about the simulation of natural gas, biochemical, wastewater treatment and batch processes. Provides an updated and expanded new edition that contains 60-70% new content Guides readers through chemical processes and unit operations using the primary simulation software used in the industrial sector Covers the fundamentals of process simulation, theory and advanced applications Includes case studies of various difficulty levels for practice and for applying developed skills Features step-by-step guides to using UniSim Design, SuperPro Designer, Symmetry, Aspen HYSYS and Aspen Plus for process simulation novices

Book Description :

Commissioned by the Society for Modeling and Simulation International (SCS), this needed, useful new ‘Body of Knowledge’ (BoK) collects and organizes the common understanding of a wide collection of professionals and professional associations. Modeling and simulation (M&S) is a ubiquitous discipline that lays the computational foundation for real and virtual experimentation, clearly stating boundaries—and interactions—of systems, data, and representations. The field is well known, too, for its training support via simulations and simulators. Indeed, with computers increasingly influencing the activities of today’s world, M&S is the third pillar of scientific understanding, taking its place along with theory building and empirical observation. This valuable new handbook provides intellectual support for all disciplines in analysis, design and optimization. It contributes increasingly to the growing number of computational disciplines, addressing the broad variety of contributing as well as supported disciplines and application domains. Further, each of its sections provide numerous references for further information. Highly comprehensive, the BoK represents many viewpoints and facets, captured under such topics as: Mathematical and Systems Theory Foundations Simulation Formalisms and Paradigms Synergies with Systems Engineering and Artificial Intelligence Multidisciplinary Challenges Ethics and Philosophy Historical Perspectives Examining theoretical as well as practical challenges, this unique volume addresses the many facets of M&S for scholars, students, and practitioners. As such, it affords readers from all science, engineering, and arts disciplines a comprehensive and concise representation of concepts, terms, and activities needed to explain the M&S discipline. Tuncer Ören is Professor Emeritus at the University of Ottawa. Bernard Zeigler is Professor Emeritus at the University of Arizona. Andreas Tolk is Chief Scientist at The MITRE Corporation. All three editors are long-time members and Fellows of the Society for Modeling and Simulation International. Under the leadership of three SCS Fellows, Dr. Ören, University of Ottawa, Dr. Zeigler, The University of Arizona, and Dr. Tolk, The MITRE Corporation, more than 50 international scholars from 15 countries provided insights and experience to compile this initial M&S Body of Knowledge.

Book Description :

For the first time, this up-to-date text combines the main issues of the hardware description language VHDL-AMS aimed at model representation of mixed-signal circuits and systems, characterization methods and tools for the extraction of model parameters, and modelling methodologies for accurate high-level behavioural models.

Book Description :

"Today, the majority of engineers in many varied fields must utilize CAD/CAM systems in their work, but due to the increasing number and sophistication of programs and methods available, no one engineer can possibly be an expert in all of them. This book

Book Description :

The development of new and effective analytical and numerical models is essential to understanding the performance of a variety of structures. As computational methods continue to advance, so too do their applications in structural performance modeling and analysis. Modeling and Simulation Techniques in Structural Engineering presents emerging research on computational techniques and applications within the field of structural engineering. This timely publication features practical applications as well as new research insights and is ideally designed for use by engineers, IT professionals, researchers, and graduate-level students.

Book Description :

This book is a definitive introduction to models of computation for the design of complex, heterogeneous systems. It has a particular focus on cyber-physical systems, which integrate computing, networking, and physical dynamics. The book captures more than twenty years of experience in the Ptolemy Project at UC Berkeley, which pioneered many design, modeling, and simulation techniques that are now in widespread use. All of the methods covered in the book are realized in the open source Ptolemy II modeling framework and are available for experimentation through links provided in the book. The book is suitable for engineers, scientists, researchers, and managers who wish to understand the rich possibilities offered by modern modeling techniques. The goal of the book is to equip the reader with a breadth of experience that will help in understanding the role that such techniques can play in design.

Book Description :

Knowledge-Based Simulation: Methodology and Application represents a recent compilation of research material that reviews fundamental concepts of simulation methodology and knowledge-based simulation applications. Knowledge-based simulation represents a new and exciting bridge area linking the fields of computer simulation and artificial intelligence. This book will appeal to both theorists and practitioners who require simulation to solve complex problems. A primary attraction of the book is its emphasis on both methodology and applications. In this way, the reader can explore new methods for encoding knowledge-inten- sive information into a simulation model, and new applications that utilize these methods.

Book Description :

Simulation based on mathematical models plays a major role in computer aided design of integrated circuits (ICs). Decreasing structure sizes, increasing packing densities and driving frequencies require the use of refined mathematical models, and to take into account secondary, parasitic effects. This leads to very high dimensional problems which nowadays require simulation times too large for the short time-to-market demands in industry. Modern Model Order Reduction (MOR) techniques present a way out of this dilemma in providing surrogate models which keep the main characteristics of the device while requiring a significantly lower simulation time than the full model. With Model Reduction for Circuit Simulation we survey the state of the art in the challenging research field of MOR for ICs, and also address its future research directions. Special emphasis is taken on aspects stemming from miniturisations to the nano scale. Contributions cover complexity reduction using e.g., balanced truncation, Krylov-techniques or POD approaches. For semiconductor applications a focus is on generalising current techniques to differential-algebraic equations, on including design parameters, on preserving stability, and on including nonlinearity by means of piecewise linearisations along solution trajectories (TPWL) and interpolation techniques for nonlinear parts. Furthermore the influence of interconnects and power grids on the physical properties of the device is considered, and also top-down system design approaches in which detailed block descriptions are combined with behavioral models. Further topics consider MOR and the combination of approaches from optimisation and statistics, and the inclusion of PDE models with emphasis on MOR for the resulting partial differential algebraic systems. The methods which currently are being developed have also relevance in other application areas such as mechanical multibody systems, and systems arising in chemistry and to biology. The current number of books in the area of MOR for ICs is very limited, so that this volume helps to fill a gap in providing the state of the art material, and to stimulate further research in this area of MOR. Model Reduction for Circuit Simulation also reflects and documents the vivid interaction between three active research projects in this area, namely the EU-Marie Curie Action ToK project O-MOORE-NICE (members in Belgium, The Netherlands and Germany), the EU-Marie Curie Action RTN-project COMSON (members in The Netherlands, Italy, Germany, and Romania), and the German federal project System reduction in nano-electronics (SyreNe).

Book Description :

This easy to read text provides a broad introduction to the fundamental concepts of modeling and simulation (M&S) and systems engineering, highlighting how M&S is used across the entire systems engineering lifecycle. Features: reviews the full breadth of technologies, methodologies and uses of M&S, rather than just focusing on a specific aspect of the field; presents contributions from specialists in each topic covered; introduces the foundational elements and processes that serve as the groundwork for understanding M&S; explores common methods and methodologies used in M&S; discusses how best to design and execute experiments, covering the use of Monte Carlo techniques, surrogate modeling and distributed simulation; explores the use of M&S throughout the systems development lifecycle, describing a number of methods, techniques, and tools available to support systems engineering processes; provides a selection of case studies illustrating the use of M&S in systems engineering across a variety of domains.

Book Description :

This must-read text/reference provides a practical guide to processes involved in the development and application of dynamic simulation models, covering a wide range of issues relating to testing, verification and validation. Illustrative example problems in continuous system simulation are presented throughout the book, supported by extended case studies from a number of interdisciplinary applications. Topics and features: provides an emphasis on practical issues of model quality and validation, along with questions concerning the management of simulation models, the use of model libraries, and generic models; contains numerous step-by-step examples; presents detailed case studies, often with accompanying datasets; includes discussion of hybrid models, which involve a combination of continuous system and discrete-event descriptions; examines experimental modeling approaches that involve system identification and parameter estimation; offers supplementary material at an associated website.

Book Description :

Explore the military and combat applications of modeling and simulation Engineering Principles of Combat Modeling and Distributed Simulation is the first book of its kind to address the three perspectives that simulation engineers must master for successful military and defense related modeling: the operational view (what needs to be modeled); the conceptual view (how to do combat modeling); and the technical view (how to conduct distributed simulation). Through methods from the fields of operations research, computer science, and engineering, readers are guided through the history, current training practices, and modern methodology related to combat modeling and distributed simulation systems. Comprised of contributions from leading international researchers and practitioners, this book provides a comprehensive overview of the engineering principles and state-of-the-art methods needed to address the many facets of combat modeling and distributed simulation and features the following four sections: Foundations introduces relevant topics and recommended practices, providing the needed basis for understanding the challenges associated with combat modeling and distributed simulation. Combat Modeling focuses on the challenges in human, social, cultural, and behavioral modeling such as the core processes of "move, shoot, look, and communicate" within a synthetic environment and also equips readers with the knowledge to fully understand the related concepts and limitations. Distributed Simulation introduces the main challenges of advanced distributed simulation, outlines the basics of validation and verification, and exhibits how these systems can support the operational environment of the warfighter. Advanced Topics highlights new and developing special topic areas, including mathematical applications fo combat modeling; combat modeling with high-level architecture and base object models; and virtual and interactive digital worlds. Featuring practical examples and applications relevant to industrial and government audiences, Engineering Principles of Combat Modeling and Distributed Simulation is an excellent resource for researchers and practitioners in the fields of operations research, military modeling, simulation, and computer science. Extensively classroom tested, the book is also ideal for courses on modeling and simulation; systems engineering; and combat modeling at the graduate level.

Book Description :

This book provides a rigorous treatment of the fundamental concepts and techniques involved in process modeling and simulation. The book allows the reader to: (i) Get a solid grasp of “under-the-hood” mathematical results (ii) Develop models of sophisticated processes (iii) Transform models to different geometries and domains as appropriate (iv) Utilize various model simplification techniques (v) Learn simple and effective computational methods for model simulation (vi) Intensify the effectiveness of their research Modeling and Simulation for Chemical Engineers: Theory and Practice begins with an introduction to the terminology of process modeling and simulation. Chapters 2 and 3 cover fundamental and constitutive relations, while Chapter 4 on model formulation builds on these relations. Chapters 5 and 6 introduce the advanced techniques of model transformation and simplification. Chapter 7 deals with model simulation, and the final chapter reviews important mathematical concepts. Presented in a methodical, systematic way, this book is suitable as a self-study guide or as a graduate reference, and includes examples, schematics and diagrams to enrich understanding. End of chapter problems with solutions and computer software available online at www.wiley.com/go/upreti/pms_for_chemical_engineers are designed to further stimulate readers to apply the newly learned concepts.