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Waste management is a vital function of spacecraft life support systems as it is necessary to meet crew health and safety and quality of life requirements. Depending on the specific mission requirements, waste management operations can include waste collection, segregation, containment, processing, storage and disposal. For the Crew Exploration Vehicle (CEV), addressing volume and mass constraints is paramount. Reducing the volume of trash prior to storage is a viable means to recover habitable volume, and is therefore a particularly desirable waste management function to implement in the CEV, and potentially in other spacecraft as well. Research is currently being performed at NASA Ames Research Center to develop waste compaction systems that can provide both volume and mass savings for the CEV and other missions.

Some selected segments of the ascent and the on-orbit data from the Space Shuttle flight, STS114, as well as some selected laboratory test article data have been analyzed using wavelets, power spectrum and autocorrelation function. Additionally, a simple approximate noise test was performed on these data segments to confirm the presence or absence of white noise behavior in the data. This study was initially directed at characterizing the on-orbit background against which a signature due to an impact during on-orbit operation could be identified. The laboratory data analyzed here mimic low velocity impact that the Orbiter may be subjected to during the very initial stages of ascent.

Linear regression is the primary data analysis method used in the development of air traffic delay models. When the data being studied does indeed have an underlying linear model, this approach would produce the best-fitting model as expected. However, it has been argued by ATM researchers [Wieland2005, Evans2004] that the underlying delay models are primarily non-linear. Furthermore, the delays being modeled often depend not only on the observable independent variables being studied but also on other variables not being considered. The traditional regression approach alone may not be best suited to study these type of problems. In this paper, we propose an alternate methodology based on partitioning the data using statistical and decision tree learning methods. We then show the utility of this model in a variety of different ATM modeling problems.

This paper offers a concept for a regenerable, low-power system for purifying exhaust from a solid waste processor. The innovations in the concept include the use of a closed-loop regeneration cycle for the adsorber, which prevents contaminants from reaching the breathable air before they are destroyed, and the use of a humidity-swing desorption cycle, which uses less power than a thermal desorption cycle and requires no venting of air and water to space vacuum or planetary atmosphere. The process would also serve well as a trace contaminant control system for the air in the closed environment. A systems-level design is presented that shows how both the exhaust and air purification tasks could be performed by one processor. Data measured with a fixed-bed apparatus demonstrate the effects of the humidity swing on regeneration of the adsorbent.

The Plant Generic BioProcessing Apparatus (PGBA), a plant growth facility developed for commercial space biotechnology research, has flown successfully on 3 spaceflight missions for 4, 10 and 16 days. The environmental control systems of this plant growth chamber (28 liter/0.075 m2) provide atmospheric, thermal, and humidity control, as well as lighting and nutrient supply. Typical performance profiles of water transpiration and dehumidification, carbon dioxide absorption (photosynthesis) and respiration rates in the PGBA unit (on orbit and ground) are presented. Data were collected on single and mixed crops. Design options and considerations for the different sub-systems are compared with those of similar hardware.

Training to operate and manage Constellation vehicles, which include a crewed spacecraft and the lunar lander, is an essential part of the Constellation program. This paper discusses the on-going preparations for a Constellation Training Facility (CxTF). CxTF will be compromised of training simulators that will be used, in part, to prepare crew and flight controllers for vehicle operations. Current training simulators are reviewed to identify and outline key CxTF elements, i.e., part-task and full-task trainers. These trainers are further discussed within the context of the Constellation missions.

The “low power-CO2 removal (LPCOR) system” is an advanced air revitalization system that is under development at NASA Ames Research Center. The LPCOR utilizes the fundamental design features of the ‘four bed molecular sieve’ (4BMS) CO2 removal technology of the International Space Station (ISS). LPCOR improves power efficiency by replacing the desiccant beds of the 4BMS with a membrane dryer and a state-of-the-art, structured adsorbent device that collectively require 25% of the thermal energy required by the 4BMS desiccant beds for regeneration. Compared to the 4BMS technology, it has the added functionality to deliver pure, compressed CO2 for oxygen recovery. The CO2 removal and recovery functions are performed in a two-stage adsorption compressor. CO2 is removed from the cabin air and partially compressed in the first stage. The second stage performs further compression and delivers the compressed CO2 to a reduction unit such as a Sabatier reactor for oxygen recovery.

The Mission Operations Directorate (MOD) of the Johnson Space Center is responsible for providing continuous operations support for the International Space Station (ISS). Operations support requires flight controllers who are skilled in team performance as well as the technical operations of the ISS. ISS flight controller certification has evolved to include a balanced focus on the development of team performance and technical expertise. The latest challenge the ISS team faces is how to certify an ISS flight controller to the required level of effectiveness in one year. Space Flight Resource Management (SFRM) training, a NASA adapted variant of Crew Resource Management (CRM), is expanding the role of senior flight controllers as mentors to help meet that challenge. This paper explains our mentoring approach and discusses its effectiveness and future applicability in promoting SFRM/CRM skills.

Aviation training has remained largely untouched by decades of development in cognitive science. In aviation, people must be trained to perform complicated tasks and make good operational decisions in complex dynamic environments. However, traditional approaches to professional aviation training are not well designed to accomplish this goal. Aviation training has been based mainly on relatively rigid classroom teaching of factual information followed by on-the-job mentoring. This approach tends to compartmentalize knowledge. It is not optimal for teaching operational decision-making, and it is costly in time and personnel. The effectiveness of training can be enhanced by designing programs that support the psychological processes involved in learning, retention, retrieval, and application. By building programs that are informed by current work in cognitive science and that utilize modern technological advances, efficient training programs can be created.

This paper describes recent work on developing an extensible information grid for risk management at NASA — a RISK INFORMATION GRID. This grid is being developed by integrating information grid technology with risk management processes for a variety of risk related applications. To date, RISK GRID applications are being developed for three main NASA processes: risk management — a closed-loop iterative process for explicit risk management, program/project management — a proactive process that includes risk management, and mishap management — a feedback loop for learning from historical risks that ‘escaped’ other processes. This is enabled through an architecture involving an extensible database, structuring information with XML, ‘schema-less’ mapping of XML, and secure server-mediated communication using standard protocols.

A number of airlines have FOQA programs that analyze archived flight data. Although this analysis process is extremely useful for assessing airline concerns in the areas of aviation safety, operations, training, and maintenance, looking at flight data in isolation does not always provide the context necessary to support a comprehensive analysis. To improve the analysis process, the Aviation Data Integration Project (ADIP) has been developing techniques for integrating flight data with auxiliary sources of relevant aviation data. ADIP has developed an aviation data integration system (ADIS) comprised of a repository and associated integration middleware that provides rapid and secure access to various data sources, including weather data, airport operating condition (ATIS) reports, radar data, runway visual range data, and navigational charts.

The Rotating Disk Analytical System (R-DAS) is an in-situ, bio-analytical technology, which utilizes a micro-fluidic disk with similar form factor as an audio compact disc to enhance and augment microgravity-based cellular and molecular biology research. The current micro-fluidic assay performs live cell/dead cell analysis using fluorescent microscopy. Image acquisition and analysis are performed for each of the selected microscope slide windows. All images are stored for later download and possible further post analysis. The flight version of the R-DAS will occupy a double mid-deck shuttle locker or one quarter of an ISS rack. The control system for the R-DAS consists of a set of interactive software components. These components interact with one another to control disk rotation, vertical and horizontal stage motion, sample incubation, image acquisition and analysis, and human interface.

The animal habitat under development for the International Space Station (ISS) provides a unique opportunity for the physiological and biological science community to perform controlled experiments in microgravity on rats and mice. This paper discusses the complexities that arise in developing a new animal habitat to be flown aboard the ISS. Such development is incremental and moves forward by employing the past successes, learning from experienced shortcomings, and utilizing the latest technologies. The standard vivarium cage on the ground can be a very simple construction, however the habitat required for rodents in microgravity on the ISS is extremely complex. This discussion presents an overview of the system requirements and focuses on the unique scientific and engineering considerations in the development of the controlled animal habitat parameters. In addition, the challenges to development, specific science, animal welfare, and engineering issues are covered.

The Elytron 2S is a prototype aircraft concept to allow VTOL capabilities together with fixed wing aircraft performance. It has a box wing design with a centrally mounted tilt-wing supporting two rotors. This paper explores the aerodynamic characteristics of the aircraft using computational fluid dynamics in hover and low speed forward flight, as well as analyzing the unique control system in place for hover. The results are then used to build an input set for NASA Design and Analysis if Rotorcraft software allowing trim and flight stability and control estimations to be made with SIMPLI-FLYD.

The Spacelab Life Sciences-2 (SLS-2) mission provided scientists with the unique opportunity of obtaining inflight rodent tissue and blood samples during a 14-day mission flown in October, 1993. In order to successfully obtain these samples, Ames Research Center's Space Life Sciences Payloads Office has developed an innovative, modular approach to packaging the instruments used to obtain and preserve the inflight tissue and blood samples associated with the hematology experiments on SLS-2. The design approach organized the multitude of instruments into 12 different 5x6x1 inch kits which were each used to accomplish a particular experiment functional objective on any given day during the mission. The twelve basic kits included blood processing, isotope and erythropoietin injection, body mass measurement, and microscope slides.

The Controlled Environment Research Chamber (CERC) at the NASA Ames Research Center was created for early-on investigation of promising new technologies for life support of advanced space exploration missions. The CERC facility is being used to address the advanced technology requirements necessary to implement an integrated working and living environment for a planetary habitat. The CERC, along with a human-powered centrifuge, a planetary terrain simulator, advanced displays, and a virtual reality capability, is able to develop and demonstrate applicable technologies for future planetary exploration. There will be several robotic mechanisms performing exploration tasks external to the habitat that will be controlled through the virtual environment to provide representative workloads for the crew.

This paper summarizes the results to date of an on-going research program being conducted by NASA in conjunction with the FAA vertical flight program office. The goal of the program is to reduce pilot workload and increase safety for rotorcraft category A terminal area procedures. Two piloted simulations were conducted on the NASA Ames Vertical Motion Simulator to examine the benefits of optimal procedures, cockpit displays, and alternate cueing methods. Measures of performance, handling qualities ratings and pilot comments indicate that such enhancements can greatly assist a pilot in handling an engine failure in the terminal area.

Pyrolysis is a very versatile waste processing technology which can be tailored to produce a variety of solid liquid and/or gaseous products. The main disadvantages of pyrolysis processing are: (1) the product stream is more complex than for many of the alternative treatments; (2) the product gases cannot be vented directly into the cabin without further treatment because of the high CO concentrations. One possible solution is to combine a pyrolysis step with catalytic oxidation (combustion) of the effluent gases. This integration takes advantage of the best features of each process, which is insensitivity to product mix, no O2 consumption, and batch processing, in the case of pyrolysis, and simplicity of the product effluent stream in the case of oxidation. In addition, this hybrid process has the potential to result in a significant reduction in Equivalent System Mass (ESM) and system complexity.

One of the major problems associated with solid waste processing technologies is effluent contaminants that are released in gaseous forms from the processes. This is a concern in both biological as well as physicochemical solid waste processing. Carbon dioxide (CO2), the major gas released, does not present a serious problem and there are currently in place a number of flight-qualified technologies for CO2 removal. However, a number of other gases, in particular NOx, SO2, NH3, and various hydrocarbons (e.g. CH4) do present health hazards to the crew members in space habitats. In the present configuration of solid waste processing in the International Space Station (ISS), some of these gases are removed by the Trace Contaminant Control System (TCCS), demands a major resupply. Reduction of the resupply can be effective by using catalyst impregnated carbon nanotubes. For example, NO decomposition to N2 and O2 is thermodynamically favored.

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.