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The selection of a life support system for a lunar base depends on many interrelated factors, both programmatic and technical. Many factors are identifiable through the application of a systems engineering approach to the lunar base design, in which base and mission requirements are determined. In addition, there is a range of evolving technology options whose cost and maturity affect their potential for inclusion in base designs. Results of ongoing lunar base design are presented with emphasis on the selection of promising approaches for advanced life support systems that decrease overall cost for a single, permanently inhabited lunar base. We identify critical technology areas that inhibit the selection of closed life support systems and propose alternative basing scenarios to alleviate development and operational costs. In particular, we quantify the cost savings associated with establishing a base at a lunar pole in a region of permanent sunlight.

McDonnell Douglas Aerospace and Shimizu Corporation are jointly designing and laboratory testing critical elements of an integrated physical-chemical and biological regenerative life support system with food production. The primary target application is a manned lunar base. Component computer models for selected processing technologies have been developed and integrated into a detailed regenerative life support system computer model. The models are used for performing systems analysis. The component models include physical-chemical air revitalization and water recycling, physical-chemical and microbial waste treatment components, and plant growth units. Based on the component modeling and analysis, requirements have been identified for bioregenerative life support systems of decreased size and power consumption. These requirements in turn have been used to develop specific hardware design approaches, including microalgae-based gas regeneration and food production.

This paper describes the approach and results of an effort to characterize plant growth under various environmental conditions at the Johnson Space Center variable pressure growth chamber. Using a field of applied mathematics and statistics known as design of experiments (DOE), we developed a test plan for varying environmental parameters during a lettuce growth experiment. The test plan was developed using a Box-Behnken approach to DOE. As a result of the experimental runs, we have developed empirical models of both the transpiration process and carbon dioxide assimilation for Waldman's Green lettuce over specified ranges of environmental parameters including carbon dioxide concentration, light intensity, dew-point temperature, and air velocity. This model also predicts transpiration and carbon dioxide assimilation for different ages of the plant canopy.

A canopy of plants may become a vital component of advanced controlled ecological life support systems (CELSS). The interactions of the canopy with its environment need to be modeled so that designers can properly assess alternate configurations and operating strategies. Collective behavior of an entire canopy can sometimes be more expeditiously modeled than microscopic processes while preserving the robustness of the model for analysis of a CELSS. Water transpiration is a particularly important canopy process for which it is possible to link underlying microscopic processes and arrive at a description of canopy-level aggregated behavior. The underlying fundamental processes driving transpiration are relatively well understood. Unfortunately, the usual characterization of transpiration relies on parameters such as stomatal and boundary layer conductivities that are not directly measurable in typical CELSS designs.

An approach to plant modeling that incorporates plant and environment interactions and that is driven by the requirements of designing and evaluating controlled ecological life support systems (CELSS) has been developed. The objective of this modeling approach is to permit the development of CELSS designs that optimize the performance of systems in which plant growth units are embedded. The approach described in this paper takes advantage of well-known analytical features of smoothly varying functions to construct an empirical model of the physiological response of plants to their environment. The model combines an emphasis on empirical data gathering to specify the plant response to nominal and near-nominal values of environmental control variables with general analytical relations that strictly hold for well-defined and behaved functions.