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This paper features a set of advanced technologies for autonomy and intelligence in advanced inspection systems of facility operations. These technologies offer a significant contribution to set a path to establish a system and an operating environment with autonomy and intelligence for inspection, monitoring and safety via gas and ambient sensors, video mining and speech recognition commands on unmanned ground vehicles and other platforms to support operational activities in the Cryogenics Test bed and other facilities and vehicles. These advanced technologies are in current development and progress and their functions and operations require guidance and formulation in conjunction with the development team(s) toward the system architecture.

The term Integrated Vehicle Health Management (IVHM) describes a set of capabilities that enable sustainable and safe operation of components and subsystems within aerospace platforms. However, very little guidance exists for the systems engineering aspects of design with IVHM in mind. It is probably because of this that designers have to use knowledge picked up exclusively by experience rather than by established process. This motivated a group of leading IVHM practitioners within the aerospace industry under the aegis of SAE's HM-1 technical committee to author a document that hopes to give working engineers and program managers clear guidance on all the elements of IVHM that they need to consider before designing a system. This proposed recommended practice (ARP6883 [1]) will describe all the steps of requirements generation and management as it applies to IVHM systems, and demonstrate these with a “real-world” example related to designing a landing gear system.

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.

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.

Biomolecules exhibit specific binding and high affinity for their ligands. These properties can be exploited to produce sensitive, specific, real-time sensors for analytes that cannot be readily monitored by other methods. Several technologies for environmental monitoring using proteins are currently being developed. We discuss specific challenges to practical application of a family of protein-based sensors derived from bacterial periplasmic binding proteins. We also present recent work to address these challenges.

This paper describes a multi-disciplinary damage detection methodology that can aid in detecting and diagnosing a damage in a given structural system, not limited to the example of a rotating gear presented here. Damage detection is performed on the gear stress data corresponding to the steady state conditions. The normal and damage data are generated by a finite-difference solution of elastodynamic equations of velocity and stress in generalized coordinates1. The elastodynamic solution provides a knowledge of the stress distribution over the gear such as locations of stress extrema, which in turn can lead to an optimal placement of appropriate sensors over the gear to detect a potential damage. The damage detection is performed by a multi-function optimization that incorporates Tikhonov kernel regularization reinforced by an added Laplacian regularization term as used in semi-supervised machine learning. Damage is mimicked by reducing the rigidity of one of the gear teeth.

This paper discussed how data mining techniques could give advantage to the robot in navigation, in terms of speed. The input of our navigation system is the sensory information collected by the robot's equipped landmark sensor and infra-red sensor, the process of the system is the proposed data mining technique, and the output of the system is the execution of the moving direction in a 2D Martian environment. The results demonstrate efficient goal-oriented navigation using data mining techniques.

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.

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).

Remote Tower Sensor Systems are proof-of-concept prototypes being developed by NASA/Ames Research Center (NASA/ARC) with collaboration with the FAA and NOAA. RTSS began with the deployment of an Airport Approach Zone Camera System that includes real-time weather observations at San Francisco International Airport. The goal of this research is to develop, deploy, and demonstrate remotely operated cameras and sensors at several major airport hubs and un-towered airports. RTSS can provide real-time weather observations of airport approach zone. RTSS will integrate and test airport sensor packages that will allow remote access to real-time airport conditions and aircraft status.

Samples of Mars surface material will return to Earth in 2014. Prior to curation and distribution to the scientific community the returned samples will be isolated in a special facility until their biological safety has been assessed following protocols established by NASA’s Planetary Protection Office. The primary requirements for the pre-release handling of the Martian samples include protecting the samples from the Earth and protecting the Earth from the sample. A testbed will be established to support the design of such a facility and to test the planetary protection protocols. One design option that is being compared to the conventional Biological Safety Level 4 facility is a double walled differential pressure chamber with airlocks and automated equipment for analyzing samples and transferring them from one instrument to another.

The concept of free flight introduces many challenges for both air and ground aviation operations. Of considerable concern has been the issue of moving from centralized control and responsibility to decentralized control and distributed responsibility for aircraft separation. Data from capacity studies suggest that we will reach our capacity limits with ATC centralized control within the next 2 decades, if not sooner. Based on these predictions, research on distributed air-ground concepts was under taken by NASA Advanced Air Transportation Technologies Program to identify and develop air-ground concepts in support of free-flight operations. This paper will present the results of a full mission air-ground simulation conducted in the NASA Crew Vehicle Systems Research Facility. The purpose of the study was to evaluate the effect of advanced displays with “intent” (4-D flight plans) information on flight crew and ATC performance during limited free-flight operations.

Accurate root zone moisture control in microgravity plant growth systems is problematic. With gravity, excess water drains along a vertical gradient, and water recovery is easily accomplished. In microgravity, the distribution of water is less predictable and can easily lead to flooding, as well as anoxia. Microgravity water delivery systems range from solidified agar, water-saturated foams, soils and hydroponics soil surrogates including matrix-free porous tube delivery systems. Surface tension and wetting along the root substrate provides the means for adequate and uniform water distribution. Reliable active soil moisture sensors for an automated microgravity water delivery system currently do not exist. Surrogate parameters such as water delivery pressure have been less successful.

Ames Research Center’s Life Sciences Division has developed and flown an extensive array of spaceflight experiment unique equipment (EUE) during the last decade of the twentieth century. Over this ten year span, the EUE developed at ARC supported a vital gravitational biology flight research program executed on several different platforms, including the Space Shuttle, Spacelab, and Space Station Mir. This paper highlights some of the key EUE elements developed at ARC and flown during the period 1990-1999. Resulting lessons learned will be presented that can be applied to the development of similar equipment for the International Space Station.

A three country effort (U.S., Russia, and Bulgaria) has upgraded the plant growth facilities on the Mir Space Station and used the new facility to grow wheat for 90 days. The Svet plant-growth facility was reactivated and used in an initial experiment as part of the Shuttle/Mir program, August to November, 1995. The Svet system, used first to grow cabbage and radish during a 1990 experiment, was augmented by the addition of a U.S. developed Gas Exchange Measurement System (GEMS) that measures a range of environmental parameters plus transpiration, photosynthesis, and possibly respiration. Environmental parameters include cabin, chamber, root-zones, and leaf temperatures. Light levels, relative humidity, oxygen, and atmospheric pressure are also measured. High-accuracy water-vapor and carbon-dioxide concentrations and differences are measured using specially developed IRGA systems.

During 1995, we tested instruments and attempted a seed-to-seed experiment with Super-Dwarf wheat in the Russian Space Station Mir. Utah instrumentation included four IR gas analyzers (CO2 and H2O vapor, calculate photosynthesis, respiration, and transpiration) and sensors for air and leaf (IR) temperatures, O2, pressure, and substrate moisture (16 probes). Shortly after planting on August 14, three of six fluorescent lamp sets failed; another failed later. Plastic bags, necessary to measure gas exchange, were removed. Hence, gases were measured only in the cabin atmosphere. Other failures led to manual watering, control of lights, and data transmission. The 57 plants were sampled five times plus final harvest at 90 d. Samples and some equipment (including hard drives) were returned to earth on STS-74 (Nov. 20). Plants were disoriented and completely vegetative. Maintaining substrate moisture was challenging, but the moisture probes functioned well.

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.

We examine the requirements for on-board aircraft sensor systems that would allow pilots to “see through” poor weather, especially fog, and land and rollout aircraft under conditions that currently cause flight cancellations and airport closures. Three visual aspects of landing and rollout are distinguished: guidance, hazard detection and hazard recognition. The visual features which support the tasks are discussed. Three broad categories of sensor technology are examined: passive millimeter wave (PMMW), imaging radar, and passive infrared (IR). PMMW and imaging radar exhibit good weather penetration, but poor spatial and temporal resolution. Imaging radar exhibits good weather penetration, but typically relies on a flat-earth assumption which can lead to interpretive errors. PMMW systems have a narrow field of view. IR has poorer weather penetration but good spatial resolution.