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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.

This paper describes the DC bus regulation control algorithm for the NASA flywheel energy storage system during charge, charge reduction and discharge modes of operation. The algorithm was experimentally verified in [1] and this paper presents the necessary models for simulation. Detailed block diagrams of the controller algorithm are given. It is shown that the flywheel system and the controller can be modeled in three levels of detail depending on the type of analysis required. The three models are explained and then compared using simulation results.

From November 2010 until May of 2011, NASA's Icing Remote Sensing System was positioned at Platteville, Colorado between the National Science Foundation's S-Pol radar and Colorado State University's CHILL radar (collectively known as FRONT, or ‘Front Range Observational Network Testbed’). This location was also underneath the flight-path of aircraft arriving and departing from Denver's International Airport, which allowed for comparison to pilot reports of in-flight icing. This work outlines how the NASA Icing Remote Sensing System's derived liquid water content and in-flight icing hazard profiles can be used to provide in-flight icing verification and validation during icing and non-icing scenarios with the purpose of comparing these times to profiles of polarized moment data from the two nearby research radars.

Nowadays, optimization of manufacturing and assembly operations requires taking into account the inherent processes variations. Geometric and dimensional metrology of mechanical parts is very crucial for the aerospace industry and contributes greatly to its. In a free-state condition, non-rigid parts (or compliant parts) may have a significant different shape than their nominal geometry (CAD model) due to gravity loads and residual stress. Typically, the quality control of such parts requires a special approach where expensive and specialized fixtures are needed to constrain dedicated and follow the component during the inspection. Inspecting these parts without jig will have significant economic impacts for aerospace industries, reducing delays and the cost of product quality inspection. The Iterative Displacement Inspection (IDI) algorithm has been developed to deal with this problem.

This paper summarizes the techniques used during a microphone array test campaign performed at Pierre-Elliott-Trudeau Airport in Montréal, Québec (Canada) during the summer of 2012. Emphasis is put on the actual measurement campaign as only a limited amount of analysis has been performed at this stage. An aircraft position tracking tool is presented along with the beamforming algorithms that were used. Over 500 aircraft were recorded during this test. A comparison of known tonal sources associated to a specific aircraft type is made between different airlines in order to evaluate the repeatability of the method.

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.

Two high voltage, Series Connected Boost Regulators (SCBR) were developed to demonstrate the benefits of the SCBR topology for low Earth orbit communication satellites. The resulting breadboards had a power density of 1,200 W/kg and a measured efficiency of 95-99%. Several peak power tracking methods and algorithms were implemented to demonstrate the ability of the SCBR to peak power track a solar array. The peak power tracker derived maximum power at all times and reduced the number of sunlight battery discharges necessary. The breadboards also demonstrated several modularity techniques, which will allow a common SCBR module to be used in several applications. The breadboards were tested in an end-to-end high voltage test facility using high fidelity solar array simulators, an actual NiH2 battery, and simulated constant power loads. Design details and test results are presented.

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.