Evaluation and automation of space habitat interior layouts
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Future human exploration missions beyond Earth vicinity will be demanding, requiring highly efficient, mass-constrained systems to reduce overall mission costs and complexity. Additionally, long duration transits in space and lack of Earth abort opportunities will increase the physiological and psychological needs of the crew, which will require larger, more capable systems to ensure astronaut well-being. As a result, the objective of habitat design for these missions is to minimize mass and vehicle size while providing adequate space for all necessary equipment and a functional layout for crew health and productivity. Unfortunately, a literature review of methods for evaluating the performance of habitat interior layout designs (including human-in-the-loop mockup tests, in-depth computer-aided design evaluations, and subjective design evaluation studies) found that they are not currently compatible with the conceptual phase of design or optimization because of the qualitative nature of the comparisons and the significant time required to generate and evaluate each layout. Failure to consider interior layout design during conceptual design can lead to increased mass, compromised functionality, and increased risk to crew; particularly for the mass, cost, and volume-constrained long duration human missions to cislunar space and Mars currently being planned by NASA. A comprehensive and timely quantitative method to measure the effectiveness of interior layouts and track the complex, conflicting habitat design objectives earlier in the design process is desired. A new, structured method and modeling framework to quickly measure the effectiveness of habitat interior designs is presented. This method allows for comparison of layouts at conceptual design and advances research in the previously unavailable capability to automate the generation of habitat interiors. This evaluation method features the development of a comprehensive list of quantifiable habitat layout evaluation criteria, the development of automatic methods to measure these criteria from a geometry model and designer inputs, and the application of systems engineering tools and numerical methods to construct a multi-objective value function measuring the overall habitat layout performance. In particular, this method featured the separation of subjective designer preferences and quantitative evaluation criteria measurements to speed layout evaluations and enable automation of interior layout design subject to a set of designer preferences. This method was implemented through the construction of a software tool utilizing 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 efficiency). Notional cis-lunar habitat layouts were evaluated to demonstrate the effectiveness of the method. Furthermore, stochastic optimization was applied to understand and address difficulties with automated layout design, particularly constraint implementation and convergence behavior. Findings from these investigations and implications for future research are discussed.