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Remotely operating complex robotic mechanisms in unstructured natural environments is difficult at best. When the communications time delay is large, as for a Mars exploration rover operated from Earth, the difficulties become enormous. Conventional approaches, such as rate control of the rover actuators, are too inefficient and risky. The Intelligent Mechanisms Laboratory at the NASA Ames Research Center has developed over the past four years an architecture for operating science exploration robots in the presence of large communications time delays. The operator interface of this system is called the Virtual Environment Vehicle Interface (VEVI), and draws heavily on Virtual Environment (or Virtual Reality) technology. This paper describes the current operational version of VEVI, which we refer to as version 2.0. In this paper we will describe the VEVI design philosophy and implementation, and will describe some past examples of its use in field science exploration missions.

The development of virtual environment technology at NASA Ames Research Center and other research institutions has created opportunities for enhancing human performance. The application of this technology to training astronaut flight crews planning to go onboard the International Space Station has already begun at the NASA Johnson Space Center. A unique application of virtual environments to crew training is envisioned at NASA Ames Research Center which combines state of the art technology with haptic feedback to create a method for training crewmembers on critical life sciences operations which require fine motor skills. This paper describes such a concept, known as the Virtual Glovebox, as well as surveys other applications of virtual environments to astronaut crew training.

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.

The blade crossing event of a coaxial counter-rotating rotor is a potential source of noise and impulsive blade loads. Blade crossings occur many times during each rotor revolution. In previous research by the authors, this phenomenon was analyzed by simulating two airfoils passing each other at specified speeds and vertical separation distances, using the compressible Navier-Stokes solver OVERFLOW. The simulations explored mutual aerodynamic interactions associated with thickness, circulation, and compressibility effects. Results revealed the complex nature of the aerodynamic impulses generated by upper/lower airfoil interactions. In this paper, the coaxial rotor system is simulated using two trains of airfoils, vertically offset, and traveling in opposite directions. The simulation represents multiple blade crossings in a rotor revolution by specifying horizontal distances between each airfoil in the train based on the circumferential distance between blade tips.

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.

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.

Various methods have been used to simulate reduced gravity environments for space systems research and development. Neutral buoyancy has been the most universally used simulation of zero-g. This paper describes the facilities, personnel and experimental work that are associated with the Neutral Buoyancy Test Facility (NBTF) at NASA Ames Research Center (ARC). This facility provides a unique underwater environment for the researcher to simulate reduced gravity activities and evaluate the performance of space-related equipment. The NBTF's small size gives it several advantages over larger water facilities. First, a smaller crew ensures a lower overhead. Second, the facility is used for research purposes only, eliminating any scheduling conflicts with astronaut training. Lastly, the small volume of water allows the researcher to more easily vary the water temperature. This feature is ideal for investigations of astronaut thermal comfort and regulation.

This paper introduces a data driven model for predicting airport arrival capacity with 2-8 hour look-ahead forecast data. The model is suitable for air traffic flow management by explicitly investigating the impact of convective weather on airport arrival meter fix throughput. Estimation of the arrival airport capacity under arrival meter fix flow constraints due to severe weather is an important part of Air Traffic Management (ATM). Airport arrival capacity can be reduced if one or more airport arrival meter fixes are partially or completely blocked by convective weather. When the predicted airport arrival demands exceed the predicted available airport’s arrival capacity for a sustained period, Ground Delay Program (GDP) operations will be triggered by ATM system.

The On-line Project Information System (OPIS) is the Exploration Life Support (ELS) mechanism for task data sharing and annual reporting. Fiscal year 2008 (FY08) was the first year in which ELS Principal Investigators (PI's) were required to complete an OPIS annual report. The reporting process consists of downloading a template that is customized to the task deliverable type(s), completing the report, and uploading the document to OPIS for review and approval. In addition to providing a general status and overview of OPIS features, this paper describes the user critiques and resulting system modifications of the first year of OPIS reporting efforts. Specifically, this paper discusses process communication and logistics issues, user interface ambiguity, report completion challenges, and the resultant or pending system improvements designed to circumvent such issues for the fiscal year 2009 reporting effort.

The On-line Project Information System (OPIS) is a LAMP-based (Linux, Apache, MySQL, PHP) system being developed at NASA Ames Research Center to improve Agency information transfer and data availability, largely for improvement of system analysis and engineering. The tool will enable users to investigate NASA technology development efforts, connect with experts, and access technology development data. OPIS is currently being developed for NASA's Exploration Life Support (ELS) Project. Within OPIS, NASA ELS Managers assign projects to Principal Investigators (PI), track responsible individuals and institutions, and designate reporting assignments. Each PI populates a “Project Page” with a project overview, team member information, files, citations, and images. PI's may also delegate on-line report viewing and editing privileges to specific team members. Users can browse or search for project and member information.

Within NASA's Aviation Safety Program, the Aviation System Monitoring and Modeling (ASMM) Project addresses the need to provide decision makers with the tools to identify and evaluate predisposing conditions that could lead to accidents. This Project is developing a set of automated tools to facilitate efficient, comprehensive, and accurate analyses of data collected in large, heterogeneous databases throughout the National Aviation System. This report is a brief overview of the ASMM Project as an introduction to the rest of the presentations in this session on one of its key elements---the Performance Data Analysis and Reporting System (PDARS).

A review of the research accomplished in 2009 in the System-Level Design, Analysis and Simulation Tools (SLDAST) of the NASA's Airspace Systems Program is presented. This research thrust focuses on the integrated system-level assessment of component level innovations, concepts and technologies of the Next Generation Air Traffic System (NextGen) under research in the ASP program to enable the development of revolutionary improvements and modernization of the National Airspace System. The review includes the accomplishments on baseline research and the advancements on design studies and system-level assessment, including the cluster analysis as an annualization standard of the air traffic in the U.S. National Airspace, and the ACES-Air MIDAS integration for human-in-the-loop analyzes within the NAS air traffic simulation.

When the demand for either a region of airspace or an airport approaches or exceeds the available capacity, miles-in-trail (MIT) restrictions are the most frequently issued traffic management initiatives (TMIs) that are used to mitigate these imbalances. Miles-in-trail operations require aircraft in a traffic stream to meet a specific inter-aircraft separation in exchange for maintaining a safe and orderly flow within the stream. This stream of aircraft can be departing an airport, over a common fix, through a sector, on a specific route or arriving at an airport. This study begins by providing a high-level overview of the distribution and causes of arrival MIT restrictions for the top ten airports in the United States. This is followed by an in-depth analysis of the frequency, duration and cause of MIT restrictions impacting the Hartsfield-Jackson Atlanta International Airport (ATL) from 2009 through 2011.

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.

The elemental composition of food consumed by astronauts is well defined. The major elements carbon, hydrogen, oxygen, nitrogen and sulfur are taken up in large amounts and these are often associated with the organic fraction (carbohydrates, proteins, fats etc) of human tissue. On the other hand, a number of the elements are located in the extracellular fluids and can be accounted for in the liquid and solid waste fraction of humans. These elements fall into three major categories - cationic macroelements (e.g. Ca, K, Na, Mg and Si), anionic macroelements (e.g. P, S and Cl and17 essential microelements, (e.g. Fe, Mn, Cr, Co, Cu, Zn, Se and Sr). When provided in the recommended concentrations to an adult healthy human, these elements should not normally accumulate in humans and will eventually be excreted in the different human wastes.

A suite of cockpit navigation displays for low-visibility airport surface operations has been designed by researchers at NASA Ames Research Center following a human-centered process. This paper reports on the final research effort in this process that examined the procedural integration of these technologies into the flight deck. Using NASA Ames' high-fidelity Advanced Concepts Flight Simulator, eighteen airline crews completed fourteen low-visibility (RVR 1000′) land-and-taxi scenarios that included both nominal (i.e., hold short of intersections, route amendments) and off-nominal taxi scenarios designed to assess how pilots integrate these technologies into their procedures and operations. Recommendations for integrating datalink and cockpit displays into current and future surface operations are provided.

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.

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.

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.

A multi-discipline, multi-year collaborative spaceflight research program (NASA/Mir Science Program) has been established between the United States and Russia utilizing the capabilities of the Russian Mir Space Station and the NASA space shuttle fleet. As a key research discipline to be carried out onboard Mir, fundamental biology research encompasses three basic objectives: first, to investigate long-term effects of microgravity upon plant and avian physiology and developmental biology; second, to investigate the long-term effects of microgravity upon circadian rhythm patterns of biological systems; and third, to characterize the long-term radiation environment (internal and external) of the Russian Mir space station. The first joint U.S./Russian fundamental biology research on-board Mir is scheduled to begin in March, 1995 with the Mir mission 18 and conclude with the docking of the U.S. shuttle to Mir in June, 1995 during the STS-71, Spacelab/Mir Mission-1 (SLM-1).