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We consider the heat transfer characteristics of an ideal concentric disk used in the Wiped-Film Rotating-Disk (WFRD) evaporator for the Vapor Phase Catalytic Ammonia Removal (VPCAR) water recovery system. A mathematical model is derived to predict the radial temperature distribution and its average over the surface of the disk as a function of system parameters. The model shows self-similarity of the temperature distribution and the existence of a dimensionless parameter S (ratio of heat flux to convection) that can be used as a criterion to optimize the thermal characteristics of the disk in order to approach uniform surface temperature. Comparison of the model to experimental data using global (infrared imager) and local (resistive temperature devices) measurements shows that agreement with the model depends on the ambient condition denoted by the local heat transfer coefficient.

Design, operations and maintenance activities in aviation involve analysis of variety of aviation data. This data is typically in disparate formats making it difficult to use with different software packages. Use of a self-describing and extensible standard called XML provides a solution to this interoperability problem. While self-describing nature of XML makes it easy to reuse, it also increases the size of data significantly. A natural solution to the problem is to compress the data using suitable algorithm and transfer it in the compressed form. We found that XML-specific compressors such as Xmill and XMLPPM generally outperform traditional compressors. However, optimal use of Xmill requires of discovery of optimal options to use while running Xmill. Manual discovery of optimal setting can require an engineer to experiment for weeks.

An energy-efficient lyophilization technique is being developed to recover water from highly contaminated spacecraft waste streams. In the lyophilization process, water in an aqueous waste is frozen and then sublimed, separating the waste into a dried solid material and liquid water. This technology is ideally suited to applications such as the Mars Reference Mission, where water recovery rates approaching 100% are desirable but production of CO2 is not. Candidate wastes include feces, concentrated brines from water processors, and other solid wastes that contain water. To operate in microgravity, and to minimize power consumption, thermoelectric heat pumps can be used in place of traditional fluid cycle heat pumps. A mathematical model of a thermoelectric lyophilizer is described and used to generate energy use and processing rate estimates.

The paper describes an approach to the integration of qualitative and quantitative modeling techniques for advanced life support (ALS) systems. Developing reliable control strategies that scale up to fully integrated life support systems requires augmenting quantitative models and control algorithms with the abstractions provided by qualitative, symbolic models and their associated high-level control strategies. This will allow for effective management of the combinatorics due to the integration of a large number of ALS subsystems. By focusing control actions at different levels of detail and reactivity we can use faster, simpler responses at the lowest level and predictive but complex responses at the higher levels of abstraction. In particular, methods from model-based planning and scheduling can provide effective resource management over long time periods.

This paper describes the initial results of applying two machine-learning-based unsupervised anomaly detection algorithms, Orca and GritBot, to data from two rocket propulsion testbeds. The first testbed uses historical data from the Space Shuttle Main Engine. The second testbed uses data from an experimental rocket engine test stand located at NASA Stennis Space Center. The paper describes four candidate anomalies detected by the two algorithms.

NASA and the FAA conducted two flight campaigns to quantify onboard weather radar measurements with in-situ measurements of high concentrations of ice crystals found in deep convective storms. The ultimate goal of this research was to improve the understanding of high ice water content (HIWC) and develop onboard weather radar processing techniques to detect regions of HIWC ahead of an aircraft to enable tactical avoidance of the potentially hazardous conditions. Both HIWC RADAR campaigns utilized the NASA DC-8 Airborne Science Laboratory equipped with a Honeywell RDR-4000 weather radar and in-situ microphysical instruments to characterize the ice crystal clouds. The purpose of this paper is to summarize how these campaigns were conducted and highlight key results. The first campaign was conducted in August 2015 with a base of operations in Ft. Lauderdale, Florida.