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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 for readers to use in model validation and testing exercises 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, emphasizing the practical importance of more theoretical concepts such as identifiability and test input design Offers supplementary material at an associated website, including links for readers without prior experience in this field to expand their background knowledge This highly useful, hands-on work will be of great benefit to practitioners and professionals who use simulation and modeling techniques in their work, as well as to students in graduate-level courses on modeling and simulation. Dr. David Murray-Smith is an Emeritus Professor and Honorary Senior Research Fellow at the University of Glasgow.
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.
For every weapons system being developed, the U.S. Department of Defense (DOD) must make a critical decision: Should the system go forward to full-scale production? The answer to that question may involve not only tens of billions of dollars but also the nation's security and military capabilities. In the milestone process used by DOD to answer the basic acquisition question, one component near the end of the process is operational testing, to determine if a system meets the requirements for effectiveness and suitability in realistic battlefield settings. Problems discovered at this stage can cause significant production delays and can necessitate costly system redesign. This book examines the milestone process, as well as the DOD's entire approach to testing and evaluating defense systems. It brings to the topic of defense acquisition the application of scientific statistical principles and practices.
This unique volume introduces and discusses the methods of validating computer simulations in scientific research. The core concepts, strategies, and techniques of validation are explained by an international team of pre-eminent authorities, drawing on expertise from various fields ranging from engineering and the physical sciences to the social sciences and history. The work also offers new and original philosophical perspectives on the validation of simulations. Topics and features: introduces the fundamental concepts and principles related to the validation of computer simulations, and examines philosophical frameworks for thinking about validation; provides an overview of the various strategies and techniques available for validating simulations, as well as the preparatory steps that have to be taken prior to validation; describes commonly used reference points and mathematical frameworks applicable to simulation validation; reviews the legal prescriptions, and the administrative and procedural activities related to simulation validation; presents examples of best practice that demonstrate how methods of validation are applied in various disciplines and with different types of simulation models; covers important practical challenges faced by simulation scientists when applying validation methods and techniques; offers a selection of general philosophical reflections that explore the significance of validation from a broader perspective. This truly interdisciplinary handbook will appeal to a broad audience, from professional scientists spanning all natural and social sciences, to young scholars new to research with computer simulations. Philosophers of science, and methodologists seeking to increase their understanding of simulation validation, will also find much to benefit from in the text.
Validation of complex computer simulations is considered in the context of the operational test and evaluation of the air launched cruise missile. Published literature on validation is reviewed. Validation is described as a problem-dependent process. The goal of that process is an acceptable level of confidence that the actual and simulated data agree closely enough for an inference about the simulation to be a valid inference about the actual system. The cost of accepting a given level of confidence must be balanced against the cost of obtaining a higher level. Experimental design is seen as the key to obtaining the maximum amount of information from a limited number of test runs and is discussed. The following approach to validity is suggested. Use a screening design to identify the few, most-important variables in the simulation. Use a more complete design to specify parameter/level combinations for simulated and actual data comparison. Finally, explicitly incorporate decision analysis in judging the validity of the model based on that comparison and the use that will be made of the simulation results. A fractional factorial design is used to screen out the important factors from the clutter and multipath sub-model in TAC ZINGER. (Author).
Helps you ensure that your simulations are appropriate representations of real-world systems. The book concentrates on the differentiation between the assessment of a simulation tool and the verification and validation of general software products. It is a systematic, procedural, practical guide that you can use to enhance the credibility of your simulation models. In addition, it is a valuable reference book and a road map for software developers and quality assurance experts, or as a text for simulation methodology and software engineering courses. This book details useful assessment procedures and phases, discusses ways to tailor the methodology for specific situations and objectives, and provides numerous assessment aids. The reader can use these aids to support ongoing assessments over the entire life cycle of the model.
This work began when I was appointed as a Technical Director for Modeling and Simulation (M&S) Verification and Validation (V&V) for a major defense system in 2008. It is intended to provide the nuts and bolts of performing M&S V&V in one volume. It is not intended to provide a holistic approach to M&S V&V, as that can be derived from other sources. As such, this book assumes a basic understanding of V&V, including its place in the lifecycle, its purpose and its scope for ensuring the quality of models and simulations. During the process of developing this text, the Simulation Interoperability Standards Organization (SISO) completed SISO-GUIDE-001.2-2013, Guide for Generic Methodology for Verification and Validation (GM-VV) to Support Acceptance of Models, Simulations, and Data, 2 Volumes, June 2013. The guide does serve the purpose not covered by this book. This text provides procedural details for performing V&V. The procedures are static, dynamic and informal.
"This book explores different applications in V & V that spawn many areas of software development -including real time applications- where V & V techniques are required, providing in all cases examples of the applications"--Provided by publisher.