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Multidisciplinary Preliminary Sizing of Advanced Life Support Systems for Space

机译:空间高级寿命支持系统的多学科初探

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This paper describes a multidisciplinary strategy for designing and preliminary sizing of advanced life support systems for space applications, ranging from open-loop solutions to more advanced physico-chemical and bioregenerative systems. The strategy, based on the use of transient simulation, heuristic techniques, and realtime integrated control has been implemented into a Matlab-Simulink tool, letting large numbers of system configurations to be rapidly tested and evaluated. The tool has been built aiming to easy expandability and updating. The optimization approach for selection of design solutions is based on a MOPSO (Multi Objective Particle Swarm Optimization) algorithm, which presented optimum convergence properties. Different test cases have been considered, both to evaluate tool's capacity to select proper life support system configurations, and to verify sizing accuracy.Once validated, the strategy has been tested on CAB (Bioregenerative Environmental Control), a project of the Italian Space Agency and Thales Alenia Space Italia for the development of a closed-loop bioregenerative system.
机译:本文介绍了用于空间应用的高级寿命支持系统的设计和初步规模的多学科策略,从开环解决方案到更先进的物理化学和生物加工系统。该策略基于使用瞬态仿真,启发式技术和实时集成控制已经实现了Matlab-Simulink工具,让大量的系统配置快速测试和评估。该工具旨在旨在简单可扩展和更新。选择设计解决方案的优化方法是基于MOPSO(多目标粒子群优化)算法,其呈现了最佳的收敛性。已经考虑了不同的测试用例,以评估工具的能力选择适当的寿命支持系统配置,并验证大小精度。验证,该策略已经在驾驶室(生物根环境控制),意大利空间机构项目Alenia Space Italia用于开发闭环生物根系系统。

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