Search Results

In February 2004 NASA released “The Vision for Space Exploration.” The important goals outlined in this document include extending human presence in the solar system culminating in the exploration of Mars. Unprocessed waste poses a biological hazard to crew health and morale. The waste processing methods currently under consideration include incineration, microbial oxidation, pyrolysis and compaction. Although each has advantages, no single method has yet been developed that is safe, recovers valuable resources including oxygen and water, and has low energy and space requirements. Thus, the objective of this project is to develop a low temperature oxidation process to convert waste cleanly and rapidly to carbon dioxide and water. In the Phase I project, TDA Research, Inc. demonstrated the potential of a low temperature oxidation process using ozone. In the current Phase II project, TDA and NASA Ames Research Center are developing a pilot scale low temperature ozone oxidation system.

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.

PGBA, a plant growth facility developed for commercial space biotechnology research, successfully grew a total of 50 plants (6 species) during 10 days aboard the Space Shuttle Endeavor (STS-77), and has reflown aboard the Space Shuttle Columbia (STS-83 for 4 days and STS-94 for 16 days) with 55 plants and 10 species. The PGBA life support system provides atmospheric, thermal, and humidity control as well as lighting and nutrient supply in a 33 liter microgravity plant growth chamber. The atmosphere treatment system removes ethylene and other hydrocarbons, actively controls CO2 replenishment, and provides passive O2 control. Temperature and humidity are actively controlled.

A steady-state system mass balance calculation was performed to investigate design issues regarding the storage and/or processing of solid waste. In the initial stages of BIO-Plex, only a certain percentage of the food requirement will be satisfied through crop growth. Since some food will be supplied to the system, an equivalent amount of waste will accumulate somewhere in the system. It is a system design choice as to where the mass should accumulate in the system. Here we consider two approaches. One is to let solid waste accumulate in order to reduce the amount of material processing that is needed. The second is to process all of the solid waste to reduce solid waste storage and then either resupply oxygen or add physical/chemical (P/C) processors to recover oxygen from the excess carbon dioxide and water that is produced by the solid waste processor.

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.

Designers of future space vehicles envision simplifying the Atmosphere Revitalization (AR) system by combining the functions of trace contaminant (TC) control and carbon dioxide removal into one swing-bed system. Flow rates and bed sizes of the TC and CO2 systems have historically been very different. There is uncertainty about the ability of trace contaminant sorbents to adsorb adequately in a high-flow or short bed length configurations, and to desorb adequately during short vacuum exposures. This paper describes preliminary results of a comparative experimental investigation into adsorbents for trace contaminant control. Ammonia sorbents and low temperature catalysts for CO oxidation are the foci. The data will be useful to designers of AR systems for Constellation. Plans for extended and repeated vacuum exposure of ammonia sorbents are also presented.

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.

Dynamic simulation of the lunar outpost habitat life support was undertaken to investigate the impact of life support failures and to investigate possible responses. Some preparatory static analysis for the Lunar Outpost life support model, an earlier version of the model, and an investigation into the impact of Extravehicular Activity (EVA) were reported previously. (Jones, 2008-01-2184, 2008-01-2017) The earlier model was modified to include possible resupply delays, power failures, recycling system failures, and atmosphere and other material storage failures. Most failures impact the lunar outpost water balance and can be mitigated by reducing water usage. Food solids and nitrogen can be obtained only by resupply from Earth. The most time urgent failure is a loss of carbon dioxide removal capability. Life support failures might be survivable if effective operational solutions are provided in the system design.

In February 2004 NASA released “The Vision for Space Exploration.” The goals outlined in this document include extending the human presence in the solar system, culminating in the exploration of Mars. A key requirement for this effort is to identify a safe and effective method to process waste. Methods currently under consideration include incineration, microbial oxidation, pyrolysis, drying, and compaction. Although each has advantages, no single method has yet been developed that is safe, recovers valuable resources including oxygen and water, and has low energy and space requirements. Thus, the objective of this work was to develop a low temperature oxidation process to convert waste cleanly and rapidly to carbon dioxide and water. TDA and NASA Ames Research Center have developed a pilot scale low temperature ozone oxidation system to convert organic waste to CO2 and H2O.

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 current CO2 removal technology of NASA is very energy intensive and contains many non-optimized subsystems. This paper discusses the concept of a next-generation, membrane-integrated, adsorption processor for CO2 removal and compression in closed-loop air revitalization systems. The membrane module removes water from the feed, passing it directly into the processor's exhaust stream; it replaces the desiccant beds in the current four-bed molecular sieve system, which must be thermally regenerated. Moreover, in the new processor, CO2 is removed and compressed in a single two-stage unit. This processor will use much less power than NASA's current CO2 removal technology and will be capable of maintaining a lower CO2 concentration in the cabin than that can be achieved by the existing CO2 removal systems.

Of the many competing technologies for resource recovery from solid wastes for long duration manned missions such as a lunar or Mars base, incineration technology is one of the most promising and certainly the most well developed in a terrestrial sense. Various factors are involved in the design of an optimum fluidized bed incinerator for inedible biomass. The factors include variability of moisture in the biomass, the ash content, and the amount of fuel nitrogen in the biomass. The crop mixture in the waste will vary; consequently the nature of the waste, the nitrogen content, and the biomass heating values will vary as well. Variation in feed will result in variation in the amount of contaminants such as nitrogen oxides that are produced in the combustion part of the incinerator. The incinerator must be robust enough to handle this variability. Research at NASA Ames Research Center using the fluidized bed incinerator has yielded valuable data on system parameters and variables.

We modeled BIO-Plex designs with separate or combined atmospheres and then simulated controlling the atmosphere composition. The BIO-Plex is the Bioregenerative Planetary Life Support Systems Test Complex, a large regenerative life support test facility under development at NASA Johnson Space Center. Although plants grow better at above-normal carbon dioxide levels, humans can tolerate even higher carbon dioxide levels. Incinerator exhaust has very high levels of carbon dioxide. An elaborate BIO-Plex design would maintain different atmospheres in the crew and plant chambers and isolate the incinerator exhaust in the airlock. This design option easily controls the crew and plant carbon dioxide levels but it uses many gas processors, buffers, and controllers. If all the crew’s food is grown inside BIO-Plex, all the carbon dioxide required by the plants can be supplied by crew respiration and the incineration of plant and food waste.

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.

New variable environment Modified Energy Cascade (MEC) crop models were developed for all the Advanced Life Support (ALS) candidate crops and implemented in SIMULINK. The MEC models are based on the Volk, Bugbee, and Wheeler Energy Cascade (EC) model and are derived from more recent Top-Level Energy Cascade (TLEC) models. The MEC models were developed to simulate crop plant responses to day-to-day changes in photosynthetic photon flux, photoperiod, carbon dioxide level, temperature, and relative humidity. The original EC model allowed only changes in light energy and used a less accurate linear approximation. For constant nominal environmental conditions, the simulation outputs of the new MEC models are very similar to those of earlier EC models that use parameters produced by the TLEC models. There are a few differences. The new MEC models allow setting the time for seed emergence, have more realistic exponential canopy growth, and have corrected harvest dates for potato and tomato.