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A Tool for Automated Design and Evaluation of Habitat Interior Layouts

机译:人居室内布局的自动设计和评估工具

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The objective of space habitat design is to minimize mass and system size while providing adequate space for all necessary equipment and a functional layout that supports crew health and productivity. Unfortunately, development and evaluation of interior layouts is often ignored during conceptual design because of the subjectivity and long times required using current evaluation methods (e.g., human-in-the-loop mockup tests and in-depth CAD evaluations). Early, more objective assessment could prevent expensive design changes that may increase vehicle mass and compromise functionality. This paper describes a new interior design evaluation method to enable early, structured consideration of habitat interior layouts. This interior layout evaluation method features a comprehensive list of quantifiable habitat layout evaluation criteria, automatic methods to measure these criteria from a geometry model, and application of systems engineering tools and numerical methods to construct a multi-objective value function measuring the overall habitat layout performance. In addition to a detailed description of this method, a C++/OpenGL software tool which has been developed to implement this method is also discussed. This tool leverages geometry modeling coupled with collision detection techniques to identify favorable layouts subject to multiple constraints and objectives (e.g., minimize mass, maximize contiguous habitable volume, maximize task performance, and minimize crew safety risks). Finally, a few habitat layout evaluation examples are described to demonstrate the effectiveness of this method and tool to influence habitat design.
机译:空间栖息地设计的目标是最大程度地减少质量和系统尺寸,同时为所有必需的设备和功能布局提供足够的空间,以支持机组人员的健康和生产力。不幸的是,由于使用当前的评估方法(例如,在环模型测试和深入的CAD评估)需要主观性和长时间,因此在概念设计期间经常会忽略内部布局的开发和评估。尽早进行更客观的评估可以避免进行昂贵的设计更改,而这些更改可能会增加车辆的质量并损害功能。本文介绍了一种新的室内设计评估方法,可以及早,结构化地考虑栖息地的内部布局。这种内部布局评估方法具有可量化的栖息地布局评估标准的全面列表,从几何模型测量这些标准的自动方法,以及系统工程工具和数值方法的应用,以构建可测量总体栖息地布局性能的多目标价值函数。除了对该方法的详细描述之外,还讨论了为实现该方法而开发的C ++ / OpenGL软件工具。该工具利用几何建模和碰撞检测技术来识别受多种约束和目标约束的有利布局(例如,最小化质量,最大化连续可居住空间,最大化任务性能以及最小化机组安全风险)。最后,描述了一些栖息地布局评估示例,以证明此方法和工具影响栖息地设计的有效性。

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