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High costs and extreme risks prevent the life testing of NASA hardware. These unavoidable limitations prevent the determination of sound reliability bounds for NASA hardware; thus the true risk assumed in future missions is unclear. A simulation infrastructure for determining these risks is developed in a configurable format here. Positive preliminary results in preparation for validation testing are reported. A stochastic filter simulates non-deterministic output from the various unit processes. A maintenance and repair module has been implemented with several levels of complexity. Two life testing approaches have been proposed for use in future model validation.

BioSim is a simulation tool which captures many basic life support functions in an integrated simulation. Conventional analyses can not efficiently consider all possible life support system configurations. Heuristic approaches are a possible alternative. In an effort to demonstrate efficacy, a validating experiment was designed to compare the configurational optima discovered by heuristic approaches and an analytical approach. Thus far, it is clear that a genetic algorithm finds reasonable optima, although an improved fitness function is required. Further, despite a tight analytical fit to data, optimization produces disparate results which will require further validation.

A reconfigurable control system is an intelligent control system that detects faults within the system and adjusts its performance automatically to avoid mission failure, save lives, and reduce system maintenance costs. The concept was first successfully demonstrated by NASA between December 1989 and March 1990 on the F-15 flight control system (SRFCS), where software was integrated into the aircraft's digital flight control system to compensate for component loss by reconfiguring the remaining control loop. This was later adopted in the Boeing X-33. Other applications include modular robotics, reconfigurable computing structure, and reconfigurable helicopters. The motivation of this work is to test such control system designs for future long term space missions, more explicitly, the automation of life support systems.

Environmental control and life support systems are usually associated with high demands for performance robustness and cost efficiency. However, considering the complexity of such systems, determining the balance between those two design factors is nontrivial for even the simplest space missions. Redundant design is considered as a design optimization dilemma since it usually means higher system reliability as well as system cost. Two coupled fundamental questions need to be answered. First, to achieve certain level of system reliability, what is the corresponding system cost? Secondly, given a budget to improve system reliability, what is the most efficient design for component or subsystem redundancy? The proposed analysis will continue from previous work performed on series systems by expanding the scope of the analysis and testing parallel systems. Namely, the online and offline redundancy designs for a Lunar Outpost Mission are under consideration.