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Capturing Experimental Design Insights in Support of the Model-based System Engineering Approach

机译：捕获实验设计见解以支持基于模型的系统工程方法

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摘要

Model-Based Systems Engineering (MBSE) continues to mature into a popular approach as systems become more complex. Integrating MBSE architectural diagrams with external simulations that model a variety of different domains allows designers to perform sophisticated engineering design and analysis. To better understand how these external models support design decisions, we can leverage the statistical methods of design of experiments to identify insights into a complex system design problem. These insights include identifying the most important design parameters, the nature of their behaviour, their synergies between them, their diminishing or increasing rates of change, and thresholds that achieve a desired level of effectiveness. The purpose of this paper is to propose a MBSE methodology that captures the insights identified during an experimental design study within the integrated system model while applying the MBSE approach.
机译：随着系统变得越来越复杂，基于模型的系统工程（MBSE）继续成熟成为一种流行的方法。通过将MBSE体系结构图与可对各种不同领域建模的外部仿真相集成，设计人员可以执行复杂的工程设计和分析。为了更好地理解这些外部模型如何支持设计决策，我们可以利用实验设计的统计方法来识别对复杂系统设计问题的见解。这些见解包括确定最重要的设计参数，其行为的性质，它们之间的协同作用，其减小或增加的变化率以及达到所需效果水平的阈值。本文的目的是提出一种MBSE方法，该方法可以在应用MBSE方法的同时，在集成系统模型中捕获在实验设计研究期间确定的见解。

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