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A prototype packed bed convective dryer has been studied for use in an energy-efficient closed air-loop heat-pump drying system for astronaut cabin waste. This paper presents a transient continuum model for the heat and mass transfer between the air and wet ersatz trash in the cylindrical drying vessel. The model is based on conservation equations for energy and moisture applied to the air and solid phases and its formulation includes the unique waste characteristic of having both dry and wet solids. It incorporates heat and mass transfer coefficients for the system measured on an ersatz trash in the dryer vessel, and experimentally determined moisture sorption equilibrium relationship for the wet material. The resulting system of differential equations is solved by the finite-volume method as implemented by the commercial software COMSOL. The validated model will be used in the optimization of the entire closed-loop system consisting of dryer, condenser, and heat-recovery modules.

Food preparation labor, minimal for the individually packaged food system used on ISS, represents a significant allocation of crew time in a bulk-packaged or bioregenerative food system. Direct measurements of active preparation time for individual dishes are insufficient to construct accurate estimates of food preparation labor costs when “cooking ahead” and “planned leftovers” strategies are employed, because active food preparation labor is not proportional to the number of servings of food prepared. Food preparation time was modeled as a function of batch size, based on the principle of fixed time requirements for quantity-independent preparation tasks and fixed plus marginal time requirements for quantity-dependent tasks. Videotapes of food preparation operations were used to measure the average duration of tasks such as measuring and stirring which are roughly independent of the amount of material processed.

The crew diet in a bioregenerative lifesupport system will be a combination of foods grown and processed in’situ with resupplied prepackaged foods and ingredients. The ideal diet should be palatable, nutritionally adequate, varied and low in cost. This diet can be obtained by adopting an optimization strategy combining panel acceptance data, nutritional analyses and mission specific ESM (equivalent system mass) cost estimates for a large selection of foods and ingredients. A linear programming routine selects the lowest cost diet from the foods surveyed, subject to constraints on nutrient content, food acceptability, and variety. The rigor of these constraints is a key factor in determining the cost of the diet (s) they define. By varying individual constraints over several optimizations, we can estimate sensitivity of overall costs to a particular nutrient, or even an intangible quality such as acceptability, while controlling other aspects of the diet.