Quantifying ECLSS Robustness for Deep Space Exploration

Human exploration of deep space will require Environmental Control and Life Support Systems of increasing robustness as mission duration and distance from Earth increases. As crews travel to distant unexplored environments, designers will need heightened confidence in life support availability under increasing levels of uncertainty and risk. Variation in system performance, environmental conditions, resource consumption, waste generation, and even mission characteristics will lead to unexpected responses, increased likelihood of failures, and even design obsolescence. The cost of system failures will also rise, due to launch mass and volume constraints, time and cost of resupply, and reduced ability to abort to Earth. If not accounted for early in design, this increased risk and cost of uncertainty might preclude human deep space exploration. We have previously defined ECLSS robustness as “the ability to maintain habitable conditions for crew survival and productivity over the mission lifetime under a wide range of conditions.” This wide range of conditions includes ordinary usage, finite occasional environmental disturbances or disruptions, and sustained changes in the system or mission context. ECLSS robustness must be quantifiable for design evaluation, comparison, improvement, and optimization. A robustness metric must quantify the system’s ability to maintain consistent performance (i.e. conditions necessary for crew productivity) in time, under perturbation of state, and in the event of system disturbance (failure or other shock). A robustness metric should address spacecraft habitability, not just crew survival; apply to all levels of system abstraction; apply to all design phases or levels of fidelity; be practical for use, relevant, and objective; and be compatible with existing assessment tools and all technology types. In this paper we assess several potential robustness metrics with respect to these criteria. Finally, an ECLSS robustness metric is proposed and discussed for future use in design evaluation and improvement.