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HDBK-1120. 1993. Failure Modes, Effects, and Criticality Analysis, Rome, NY: Reliability Analysis Center (RAC). HDBK-1140. 1991. Fault Tree Analysis Application Guide, Rome, NY: Reliability Analysis Center (RAC). HDBK-1610. 1999. Evaluating the Reliability of Commercial Off-the-Shelf (COTS) Items, Rome, NY: Reliability Analysis Center (RAC). HDBK-1190. 2002. A Practical Guide to Developing Reliable Human-Machine Systems and Processes, Rome, NY: Reliability Analysis Center (RAC). HDBK-3180. 2004. Operational Availability Handbook, Rome, NY: Reliability Analysis Center (RAC). Leitch, R.D. 1988. BASIC Reliability Engineering Analysis. Stoneham, MA: Butterworth. MIL-HDBK-0217. 1991. Reliability Prediction of Electronic Equipment. Washington, DC: Department of Defense (DoD). MIL-HDBK-470A. 1997. Designing and Developing Maintainable Products and Systems. Washington, DC: Department of Defense (DoD). MIL-HDBK-1908B. 1999. DoD De nitions of Human Factors Terms. Washington, DC: Department of Defense (DOD). MIL-HDBK-2155. 1995. (Cancelled) Failure Reporting, Analysis, and Corrective Action System. Washington, DC: Department of Defense (DoD). MIL-STD-721C. 1981. De nition of Terms for Reliability and Maintainability. Washington, DC: Department of Defense (DoD). MIL-STD-882D. 2000. DoD Standard Practice for System Safety. Washington, DC: Department of Defense (DOD). National Aeronautics and Space Administration (NASA). 1994. Systems Engineering Toolbox for DesignOriented Engineers. NASA Reference Publication 1358. Washington, DC.
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System Modeling and Simulation
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51.1 INTRODUCTION
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Analytically, System Engineering requires several types of technical decision-making activities: 1. Mission Analysis Understanding the User s problem space to identify and bound a solution space that provides operational utility, suitability, availability, and effectiveness. 2. Architecture Development Hierarchical organization, decomposition, and bounding of operational problem space complexity into manageable levels of solutions spaces, each with a bounded set of requirements. 3. Requirements Allocation Informed appropriation and assignment of capabilities and quanti able performance to each of the solution spaces. 4. System Optimization The evaluation and re nement of system performance to maximize ef ciency and effectiveness in achieving solution space mission objectives. Depending on the size and complexity of the system, most of these decisions require tools to facilitate the decision making. Because of the complex interacting parameters of the SYSTEM OF INTEREST (SOI) and its OPERATING ENVIRONMENT, humans are often unable of internalize solutions on a personal level. For this reason engineers as a group tend to employ and exploit decision aids such as models and simulations to gain insights into the system interactions for a prescribed set of operating scenarios and conditions. Assimilation and synthesis of this knowledge and interdependencies via models and simulations enable SEs to collectively make these decisions. This chapter provides an introductory overview of how SEs employ models and simulations to implement the SE Process Model. Our discussions are not intended to instruct you in model or simulation development; numerous textbooks are available on this topic. Instead, we focus on the application of models and simulations to facilitate SE decision making. We begin our discussion with an introduction to the fundamentals of models and simulations. We identify various types of models, de ne model delity, address the need to certify models, and describe the integration of models into a simulation. Then, we explore HOW SEs employ models and simulations to support technical decisions involving architecture evaluations, performance requirement allocations, and validating the performance.
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What You Should Learn from This Section
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1. What is a model 2. What are the various types of models 3. How are models employed in SE decision making
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System Analysis, Design, and Development, by Charles S. Wasson Copyright 2006 by John Wiley & Sons, Inc.
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51
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System Modeling and Simulation
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What is a simulation How are simulations employed in SE decision making What is a mock-up What is a prototype What is a testbed How is a testbed employed in SE decision making
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De nitions of Key Terms
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Accreditation The formal certi cation that a model or simulation is acceptable for use for a speci c purpose. Accreditation is conferred by the organization best positioned to make the judgment that the model or simulation in question is acceptable. That organization may be an operational user, the program of ce, or a contractor, depending upon the purposes intended. (DSMC SE Fundamentals, Section 13.4 Veri cation, Validation, and Accreditation; p. 120) Certi ed Model A formal designation by an of cially recognized decision authority for validating the products and performance of a model. Deterministic Model A model in which the results are determined through known relationships among the states and events, and in which a given input will always produce the same output; for example, a model depicting a known chemical reaction. Contrast with: stochastic model. (DIS Glossary of M&S Terms, and IEEE STD 610.3, (references (b) and (c)) (Source: DoD 5000.59-M Modeling and Simulation (M&S) Glossary, Part II, item 153, p. 102) Event A change of object attribute value, an interaction between objects, an instantiation of a new object, or a deletion of an existing object that is associated with a particular point on the federation time axis. Each event contains a time stamp indicating when it is said to occur. (High Level Architecture Glossary, (reference (m)). (Source: DoD 5000.59-M Modeling and Simulation (M&S) Glossary, Part II, item 193, p. 107) Fidelity The accuracy of the representation when compared to the real world. (DoD Publication 5000.59-P, (reference (g)). (Source: DoD 5000.59-M Modeling and Simulation (M&S) Glossary, Part II, item 218, p. 112) Initial Condition The values assumed by the variables in a system, model, or simulation at the beginning of some speci ed duration of time. Contrast with: boundary condition; nal condition. (DIS Glossary of M&S Terms, (reference (b)). (Source: DoD 5000.59-M Modeling and Simulation (M&S) Glossary, Part II, item 270, p. 123) Initial State The values assumed by the state variables of a system, component, or simulation at the beginning of some speci ed duration of time. Contrast with: nal state. (DIS Glossary of M&S Terms, (reference (b)). (Source: DoD 5000.59-M Modeling and Simulation (M&S) Glossary, Part II, item 271, p. 123) Model A virtual or physical representation of an entity for purposes of presenting, studying, and analyzing its characteristics such as appearance, behavior, or performance for a prescribed set of OPERATING ENVIRONMENT conditions and scenarios. Model-Test-Model An integrated approach to using models and simulations in support of pre-test analysis and planning; conducting the actual test and collecting data; and post-test
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