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A significant amount of software has been developed to model the advanced life support aspects of a Mars surface habitat. Models, such as the BIO-Plex Baseline Simulation Model (Finn, 1999), have been useful in studying advanced life support systems. These models have been used to conduct trade study comparisons to determine which Advanced Life Support (ALS) technologies should currently be used in a habitat design. However, the present models and approaches require significant overhead to exchange one technology for another mostly because the models are mission centric and assume either that the habitat will be stationary or that the life of the habitat will be same as the mission duration. In other words, these models lack the desired level of modularity necessary to quickly complete multiple trade studies of different missions as the habitat evolves from mission to mission.

In this paper, optimum crop planting schedule that would minimize the equivalent system mass (ESM) of a bio-regenerative advanced life support system (ALSS) is determined using an advanced crop scheduling model in conjunction with a diet optimization model. Mixed-integer linear programming (MILP) models are developed to determine crop scheduling and optimum diet for the crew-members. Given the activity schedule of the crew members, the diet optimization module constructs a diet cycle of 20–30 days that would meet the necessary nutritional requirements observing a predetermined diet variety. In doing so the diet optimization tries to minimize the overall system ESM. Necessary biomass amounts calculated by this model are fed into the crop scheduling model as the demands. Given these demands and growth parameters for these crops, the crop scheduling model determines the best planting schedule that will optimize the system behavior, i.e., the one that would minimize ESM.

In this paper, an aggregate system level modeling and analysis framework is proposed to facilitate the integration and design of advanced life support systems (ALSS). As in process design, the goal is to choose values for the degrees of freedom that achieve the best overall ALSS behavior without violating any system constraints. At the most fundamental level, this effort will identify the constraints and degrees of freedom associated with each subsystem and provide estimates of the system behavior and interactions involved in ALSS. This work is intended to be a starting point for developing insights into ALSS from a systems engineering point of view. At this level, simple aggregate static input/output mapping subsystem models from existing data and the NASA ALS BVAD document are used to debug the model and demonstrate feasibility.

In this work, a mixed-integer linear programming (MILP) model is developed for advanced scheduling of crop production in bio-regenerative ALS systems. The main objective of the model is to meet the edible biomass demand of the crew diet. In the meantime, it tries to minimize the variation in oxygen generated by crops via controlling planting areas and the planting timetable of the crops taking into account the variability in oxygen released by crops arising from different photoperiod requirements. The model tries to minimize the cost of regulating the level of oxygen and carbon dioxide within the tolerable range in the crew cabin. If, for example, there is excess oxygen in the crew cabin, then it should be removed at a cost, which may/should be different than re-supplying oxygen if there is a deficit. A similar scenario will apply for carbon dioxide.