Understanding Model Characteristics in .NET

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Understanding Model Characteristics
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Models are generally developed to satisfy speci c needs of the analyst. Although models may appear to match two different analysis needs, they may not satisfy the requirements. Consider the following example:
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EXAMPLE 51.3
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Let s suppose Analyst A requires a sensor model to investigate a technical issue. Analyst A develops a functional model of Sensor XYZ to meet their needs of understanding the behavioral responses to external stimuli. Later, Analyst B in another organization researches the marketplace and learns that Analyst A has already developed a sensor model that may be available. However, Analyst B soon learns that the model describes the functional behavior of Sensor XYZ whereas Analyst B is interested in the physical model of Sensor XYZ. As a result, Analyst B either creates their own physical model of Sensor XYZ or translates the functional domain model into the physical domain.
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Understanding Model Fidelity
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One of the challenges of modeling and simulation is determining the type of model you need. Ideally, you would want a perfect model readily available so that you could provide simple inputs and conduct WHAT IF games with reliable results. Due to the complexities and practicalities of modeling, among which are cost and schedule constraints, models are estimates or approximations of reality termed levels of delity. For example, is a rst-order approximation suf cient Second-order Third-order etc. The question we have to answer is: WHAT minimum level of delity do we need for a speci c area of investigation Consider the following examples:
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EXAMPLE 51.4
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Hypothetically, a mechanical gear system has a transfer function that can be described mathematically as y = 0.1x where x = input and y = output. You may nd a simple analytical math model may be suf cient for some applications. In other applications the area of analytical investigation might require a physical model of each component within the gear train, including the frictional losses due to the loading effects on axle bearings.
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51.3 Models
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EXAMPLE 51.5
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Let s assume you are developing an aircraft simulator. The key questions are:
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1. Are computer-generated graphic displays of cockpit instruments with simulated moving needle instruments and touch screen switches suf cient, or do you need the actual working hardware used in the real cockpit to conduct training 2. What level of delity in the instruments do you need to provide pilot trainees with the look and feel of ying the actual aircraft 3. Is a static cockpit platform suf cient for training, or do you need a three-axis motion simulator to provide the level of delity in realistic training The point of these examples is: SEs, in collaboration with analysts, the Acquirer, and Users, must be able to determine WHAT levels of delity are required and then be able to specify it. In the case of simulator training systems, various levels of delity may be acceptable. Where this is the case, create a matrix to specify the level of delity required for each physical item and include scoping de nitions of each level of delity. To illustrate this point, consider the following example:
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EXAMPLE 51.6
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The level of delity required for some switches may indicate computer-generated images are suf cient. Touch screen displays that enable switch activation by touch may be acceptable to create the effects of ipping switches.
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EXAMPLE 51.7
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In other instances hand controls, brake pedals, and other mechanisms may require actual working devices that provide the tactile look and feel of devices of the actual system.
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Specifying Model Fidelity
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Understanding model delity is often a challenge. One of the objectives of modeling and simulation is being able to realistically model the real world. In the case of training simulators that require visual representations of the environment inside and outside the simulated vehicle, what level of delity in the terrain and trees and cultural features such as roads, bridges, and buildings is necessary and suf cient for training purposes Are computer-generated images with synthetic texture suf cient for landscapes Do you require photographic images with computer-generated texture The answer to these questions depends on trade-offs between resources available and the positive or negative impacts to training. Increasing the level of delity typically requires signi cantly more resources such as data storage or computer processing performance. Concepts such as cost as an independent variable (CAIV) enable Acquirer decision makers to assess WHAT level of CAPABILITY can be achieved at WHAT cost.
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