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At least 235 records · Page 13

An expert system shell for inferring vegetation characteristics

The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. VEG is described in detail in several references. The first generation version of VEG was extended. In the first year of this contract, an interface to a file of unknown cover type data was constructed. An interface that allowed the results of VEG to be written to a file was also implemented. A learning system that learned class descriptions from a data base of historical cover type data and then used the learned class descriptions to classify an unknown sample was built. This system had an interface that integrated it into the rest of VEG. The VEG subgoal PROPORTION.GROUND.COVER was completed and a number of additional techniques that inferred the proportion ground cover of a sample were implemented. This work was previously described. The work carried out in the second year of the contract is described. The historical cover type database was removed from VEG and stored as a series of flat files that are external to VEG. An interface to the files was provided. The framework and interface for two new VEG subgoals that estimate the atmospheric effect on reflectance data were built. A new interface that allows the scientist to add techniques to VEG without assistance from the developer was designed and implemented. A prototype Help System that allows the user to get more information about each screen in the VEG interface was also added to VEG.

Harrison, P. Ann↗

Software for Displaying Data from Planetary Rovers

Science Activity Planner (SAP) DownlinkBrowser is a computer program that assists in the visualization of processed telemetric data [principally images, image cubes (that is, multispectral images), and spectra] that have been transmitted to Earth from exploratory robotic vehicles (rovers) on remote planets. It is undergoing adaptation to (1) the Field Integrated Design and Operations (FIDO) rover (a prototype Mars-exploration rover operated on Earth as a test bed) and (2) the Mars Exploration Rover (MER) mission. This program has evolved from its predecessor - the Web Interface for Telescience (WITS) software - and surpasses WITS in the processing, organization, and plotting of data. SAP DownlinkBrowser creates Extensible Markup Language (XML) files that organize data files, on the basis of content, into a sortable, searchable product database, without the overhead of a relational database. The data-display components of SAP DownlinkBrowser (descriptively named ImageView, 3DView, OrbitalView, PanoramaView, ImageCubeView, and SpectrumView) are designed to run in a memory footprint of at least 256MB on computers that utilize the Windows, Linux, and Solaris operating systems.

Powell, Mark↗

Applying artificial intelligence to astronomical databases - A survey of applicable technology

AI technologies which are relevant to astronomical data bases are reviewed, including intelligent interfaces, internal representations, and data analysis. The natural language query system developed for the Hubble Space Telescope and the technique of goal directed queries are considered. Two technologies which might lead to the development of pictorial interfaces are presented: one based on Bayesian probabilities, the other on associative memories. The development of a data analysis system which can discover classes of data within a data base without any information other than the data itself is examined. A prototype data analysis assistant to automatically develop and implement plans for data reduction is described.

Rosenthal, Donald A.↗

SU-E-T-03: 3 Year Clinical Experience with the IBA Proton Eyeline

Purpose: Over the past 3 years, more than 50 patients with ocular disease have been treated with a prototype commercial eyeline developed by Ion Beam Applications (IBA). It is particularly crucial for the dosimetry of the machine to be accurate, precise, and reproducible because of the small treatment volumes and several surrounding critical structures. A quality assurance (QA) program has been developed in order to regularly check and record the machine’s dosimetry over time. In this study we have summarized and evaluated three years of patient and system QA data for the eyeline prototype. Methods: In order to accurately deliver the prescribed dose to the patient’s treatment site, an output model was created based on several machine parameters. This output model, along with the requested system parameters, are regularly checked and recorded by a QA program. 10 standard proton fields have been created which have regular QA performed monthly with a water tank and parallel-plate chamber, and recorded in a database. QA has additionally been performed for each patient-specific treatment field. This is to verify and evaluate the patient output model as well as the system parameters for range&modulation combinations different than the standard QA fields. Results: 140 beam measurements have been analyzed for range, modulation, and output. The range is typically within tolerance, although there are about 6 cases where the system did not perform as expected. The modulation appears to be very stable, always being within tolerance. Output for the standard QA fields are typically within 2.5% from the baseline value. The patient output measurements agree within 2.5% from the model. Conclusion: Overall the eyeline performs well within the tolerances set, and the patient output measurements agree within 2% of the model.

60 APPLIED LIFE SCIENCES↗

Applying AI tools to operational space environmental analysis

The U.S. Air Force and National Oceanic Atmospheric Agency (NOAA) space environmental operations centers are facing increasingly complex challenges meeting the needs of their growing user community. These centers provide current space environmental information and short term forecasts of geomagnetic activity. Recent advances in modeling and data access have provided sophisticated tools for making accurate and timely forecasts, but have introduced new problems associated with handling and analyzing large quantities of complex data. AI (Artificial Intelligence) techniques have been considered as potential solutions to some of these problems. Fielding AI systems has proven more difficult than expected, in part because of operational constraints. Using systems which have been demonstrated successfully in the operational environment will provide a basis for a useful data fusion and analysis capability. Our approach uses a general purpose AI system already in operational use within the military intelligence community, called the Temporal Analysis System (TAS). TAS is an operational suite of tools supporting data processing, data visualization, historical analysis, situation assessment and predictive analysis. TAS includes expert system tools to analyze incoming events for indications of particular situations and predicts future activity. The expert system operates on a knowledge base of temporal patterns encoded using a knowledge representation called Temporal Transition Models (TTM's) and an event database maintained by the other TAS tools. The system also includes a robust knowledge acquisition and maintenance tool for creating TTM's using a graphical specification language. The ability to manipulate TTM's in a graphical format gives non-computer specialists an intuitive way of accessing and editing the knowledge base. To support space environmental analyses, we used TAS's ability to define domain specific event analysis abstractions. The prototype system defines events covering reports of natural phenomena such as solar flares, bursts, geomagnetic storms, and five others pertinent to space environmental analysis. With our preliminary event definitions we experimented with TAS's support for temporal pattern analysis using X-ray flare and geomagnetic storm forecasts as case studies. We are currently working on a framework for integrating advanced graphics and space environmental models into this analytical environment.

Krajnak, Mike↗

Space Weather Forecasting Capabilities at the Community Coordinated Modeling Center (CCMC)

The Community Coordinated Modeling Center (CCMC) provides a variety of services to the space science community. The mission for the CCMC's Space Weather Forecasting team is to address the space weather needs of NASA's robotic mission by conducting customized space weather services to NASA end-users. The team leverages CCMC tools/resources, carries out prototyping activities for the next generation space weather tools and follows communications/interactions with the users. We provide space weather forecasts, notifications, analysis and also education. This presentation will describe the team's concepts of operations, notification processes, anomaly analysis, and the tools used for space weather forecasting. The tools include a system that are completely open and available to the public's use like the Integrated Space Weather Analysis (iSWA) tool and the Database of Notifications, Knowledge and Information (DONKI). We will also discuss the education and training activities and how events like solar eclipses are important for the improvement and validation of different space weather models.

Collado-Vega, Yaireska↗

Smart Crop Farming Systems for Artemis Exploration Missions

Space crop production systems that mitigate risks of crew poor performance or illness due to inadequate food and nutrition are needed during manned Artemis exploration missions beyond LEO. Prototype farms must be designed for deployment on ISS and tested in manned platforms: Gateway, lunar habitats, and Mars trans-hab spacecraft in preparation for human missions to Mars. Food production must be optimal and safe for human consumption. Thus, plant growth facilities (i.e. Veggie and APH) can be enhanced with imaging systems (including hyperspectral, multispectral, lidar, and fluorescence imaging systems) for nondestructive monitoring of plant health, stress and assessing food safety. Databases of crop responses to stress obtained during ground studies can be used to develop novel artificial intelligence (AI) algorithms for optimizing crop production (i.e. environmental settings during growth) and for detecting crop indices that ensure food safety. Future farming systems should be sustainable and smart. Novel adaptive AI algorithms requiring limited data sets for calibration are needed for reducing crew intervention during plant cultivation except for maintenance and harvesting events. Eventually, AI driven control systems that include autonomous planting, growing, and harvesting as well as periodic sanitization need evaluation for supplementing crew diets with fresh produce during future Mars exploration missions.

O Monje↗

Evaluation of tritium release properties of advanced tritium breeders

Demonstration power plant (DEMO) fusion reactors require advanced tritium breeders with high thermal stability. Lithium titanate (Li{sub 2}TiO{sub 3}) advanced tritium breeders with excess Li (Li{sub 2+x}TiO{sub 3+y}) are stable in a reducing atmosphere at high temperatures. Although the tritium release properties of tritium breeders are documented in databases for DEMO blanket design, no in situ examination under fusion neutron (DT neutron) irradiation has been performed. In this study, a preliminary examination of the tritium release properties of advanced tritium breeders was performed, and DT neutron irradiation experiments were performed at the fusion neutronics source (FNS) facility in JAEA. Considering the tritium release characteristics, the optimum grain size after sintering is <5 μm. From the results of the optimization of granulation conditions, prototype Li{sub 2+x}TiO{sub 3+y} pebbles with optimum grain size (<5 μm) were successfully fabricated. The Li{sub 2+x}TiO{sub 3+y} pebbles exhibited good tritium release properties similar to the Li{sub 2}TiO{sub 3} pebbles. In particular, the released amount of HT gas for easier tritium handling was higher than that of HTO water. (authors)

07 ISOTOPE AND RADIATION SOURCES↗

Computer Codes V and V Tests with a Large-Scale Sodium Thermal-Hydraulic Test Facility (STELLA)

The Korea Atomic Energy Research Institute (KAERI) is carrying out the design of a 'Prototype Generation IV Sodium-cooled Fast Reactor (PGSFR)' in cooperation with Argonne National Laboratory (ANL) in the US. In regard to computer codes V and V, a large-scale sodium thermal-hydraulic test program is currently being progressed in parallel with the PGSFR design, which is called STELLA (Sodium Test Loop for Safety Simulation and Assessment). The final objective of this program is to collect a separate and integral effect test database to validate the safety analysis codes and other thermal hydraulic design codes. In the first phase of the STELLA program, the sodium component test loop (hereafter called STELLA-1) was constructed at the KAERI site, and it has been used for performance tests of key sodium heat exchangers in PGSFR. Since this sodium test loop is basically for separate effects tests to verify the performance of key sodium components, the test database obtained from STELLA-1 has been used for the V and V of safety codes as well as heat exchanger design codes. The second phase of the program aiming at an integral effect test is called STELLA-2, which will be used for synthetic review of the key safety issues of PGSFR. The basic and detailed design phases of the STELLA-2 test facility are underway in accordance with the specific design requirements reflecting the whole design features of PGSFR. The facility installation is scheduled to be completed by 2018. Then the main experiments including the start-up tests will begin and the first integral effect test database will be constructed by the end of 2019. Based on the STELLA-2 platform, a simulation of the PGSFR transient will be made to evaluate the plant dynamic behaviors and demonstrate the decay heat removal performance. Multi-dimensional effects coming from a large sodium pool system will be identified as well. The test database obtained from the STELLA-2 experiment will be used for the validation of the safety analysis codes and other thermal hydraulics codes, and this project finally contributes to the specific design phase of PGSFR. This paper presents both the results of heat transfer tests for the key sodium heat exchangers using STELLA-1 and the first results of heat exchanger design codes V and V. The recent progress of the engineering design for the STELLA-2 test section is introduced and its specific design parameters are also presented in this paper with detailed evaluation results of their scaling distortions. A large-scale sodium thermal-hydraulic test program (STELLA) was introduced with the specific activities for separate and integral effects tests. The test database obtained from STELLA-1 was successfully used to validate both the heat exchanger design and safety analysis codes. Specific design features of the integral effects test facility (STELLA- 2) with a scaling ratio of 1/5 in length and 1/125 in volume were also presented. Validation of the STELLA-2 facility design is underway using system codes and CFD tools. Dedicated water-mockup experiments to verify the scaling design of key subsystems are currently being conducted as well. (authors)

42 ENGINEERING↗

Hyper-X Engine Design and Ground Test Program

The Hyper-X Program, NASA's focused hypersonic technology program jointly run by NASA Langley and Dryden, is designed to move hypersonic, air-breathing vehicle technology from the laboratory environment to the flight environment, the last stage preceding prototype development. The Hyper-X research vehicle will provide the first ever opportunity to obtain data on an airframe integrated supersonic combustion ramjet propulsion system in flight, providing the first flight validation of wind tunnel, numerical and analytical methods used for design of these vehicles. A substantial portion of the integrated vehicle/engine flowpath development, engine systems verification and validation and flight test risk reduction efforts are experimentally based, including vehicle aeropropulsive force and moment database generation for flight control law development, and integrated vehicle/engine performance validation. The Mach 7 engine flowpath development tests have been completed, and effort is now shifting to engine controls, systems and performance verification and validation tests, as well as, additional flight test risk reduction tests. The engine wind tunnel tests required for these efforts range from tests of partial width engines in both small and large scramjet test facilities, to tests of the full flight engine on a vehicle simulator and tests of a complete flight vehicle in the Langley 8-Ft. High Temperature Tunnel. These tests will begin in the summer of 1998 and continue through 1999. The first flight test is planned for early 2000.

Voland, R. T.↗

Data acquisition and slow control interface for the Mu2e experiment

The Mu2e experiment at the Fermilab Muon Campus will search for the coherent neutrinoless conversion of a muon into an electron in the field of an aluminum nucleus with a sensitivity improvement by a factor of 10000 over existing limits. The Mu2e Trigger and Data Acquisition System (TDAQ) uses otsdaq as the online Data Acquisition System (DAQ) solution. Developed at Fermilab, otsdaq integrates both the artdaq DAQ and the art analysis frameworks for event transfer, filtering, and processing. otsdaq is an online DAQ software suite with a focus on flexibility and scalability and provides a multi-user, web-based, interface accessible through a web browser. The data stream from the detector subsystems is read by a software filter algorithm that selects events which are combined with the data flux coming from a cosmic ray veto system. The Detector Control System (DCS) has been developed using the Experimental Physics and Industrial Control System (EPICS) open source platform for monitoring, controlling, alarming, and archiving. The DCS system has been integrated into otsdaq. A prototype of the TDAQ and the DCS systems has been built at Fermilab's Feynman Computing Center. In this study, we report on the progress of the integration of this prototype in the online otsdaq software.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Intelligent tutoring using HyperCLIPS

HyperCard is a popular hypertext-like system used for building user interfaces to databases and other applications, and CLIPS is a highly portable government-owned expert system shell. We developed HyperCLIPS in order to fill a gap in the U.S. Army's computer-based instruction tool set; it was conceived as a development environment for building adaptive practical exercises for subject-matter problem-solving, though it is not limited to this approach to tutoring. Once HyperCLIPS was developed, we set out to implement a practical exercise prototype using HyperCLIPS in order to demonstrate the following concepts: learning can be facilitated by doing; student performance evaluation can be done in real-time; and the problems in a practical exercise can be adapted to the individual student's knowledge.

Hill, Randall W., Jr.↗

TPS In-Flight Health Monitoring Project Progress Report

Progress in the development of new thermal protection systems (TPS) is reported. New approaches use embedded lightweight, sensitive, fiber optic strain and temperature sensors within the TPS. Goals of the program are to develop and demonstrate a prototype TPS health monitoring system, develop a thermal-based damage detection algorithm, characterize limits of sensor/system performance, and develop ea methodology transferable to new designs of TPS health monitoring systems. Tasks completed during the project helped establish confidence in understanding of both test setup and the model and validated system/sensor performance in a simple TPS structure. Other progress included complete initial system testing, commencement of the algorithm development effort, generation of a damaged thermal response characteristics database, initial development of a test plan for integration testing of proven FBG sensors in simple TPS structure, and development of partnerships to apply the technology.

Kostyk, Chris↗

Passive IFF: Autonomous Nonintrusive Rapid Identification of Friendly Assets

A proposed optoelectronic instrument would identify targets rapidly, without need to radiate an interrogating signal, apply identifying marks to the targets, or equip the targets with transponders. The instrument was conceived as an identification, friend or foe (IFF) system in a battlefield setting, where it would be part of a targeting system for weapons, by providing rapid identification for aimed weapons to help in deciding whether and when to trigger them. The instrument could also be adapted to law-enforcement and industrial applications in which it is necessary to rapidly identify objects in view. The instrument would comprise mainly an optical correlator and a neural processor (see figure). The inherent parallel-processing speed and capability of the optical correlator would be exploited to obtain rapid identification of a set of probable targets within a scene of interest and to define regions within the scene for the neural processor to analyze. The neural processor would then concentrate on each region selected by the optical correlator in an effort to identify the target. Depending on whether or not a target was recognized by comparison of its image data with data in an internal database on which the neural processor was trained, the processor would generate an identifying signal (typically, friend or foe ). The time taken for this identification process would be less than the time needed by a human or robotic gunner to acquire a view of, and aim at, a target. An optical correlator that has been under development for several years and that has been demonstrated to be capable of tracking a cruise missile might be considered a prototype of the optical correlator in the proposed IFF instrument. This optical correlator features a 512-by-512-pixel input image frame and operates at an input frame rate of 60 Hz. It includes a spatial light modulator (SLM) for video-to-optical image conversion, a pair of precise lenses to effect Fourier transforms, a filter SLM for digital-to-optical correlation-filter data conversion, and a charge-coupled device (CCD) for detection of correlation peaks. In operation, the input scene grabbed by a video sensor is streamed into the input SLM. Precomputed correlation-filter data files representative of known targets are then downloaded and sequenced into the filter SLM at a rate of 1,000 Hz. When there occurs a match between the input target data and one of the known-target data files, the CCD detects a correlation peak at the location of the target. Distortion- invariant correlation filters from a bank of such filters are then sequenced through the optical correlator for each input frame. The net result is the rapid preliminary recognition of one or a few targets.

Moynihan, Philip↗

High fidelity multiphysics tightly coupled model for a lead cooled fast reactor concept and application to statistical calculation of hot channel factors

A tightly coupled multiphysics code system is established using the MOOSE framework for hot channel factor (HCF) evaluation on a Lead Fast Reactor (LFR) concept. The coupled system is driven by the Griffin multiphysics coupling capability under which the MOOSE Heat Transfer module and NekRS computational fluid dynamics solver are coupled for conjugate heat transfer using the Cardinal application. The coupled capability is demonstrated on an LFR assembly model based on materials and geometry of a prototypical lead-cooled fast reactor design by Westinghouse Electric Company, LLC. Moreover, the work integrates the Multiphysics Object Oriented Simulation Environment (MOOSE) Stochastic Tools Module (STM) to perform calculations for statistical analysis of HCF. Furthermore, the coupling strategy and workflow demonstrated in this paper is not only useful for predicting accurate hot channel factors for different kinds of advanced reactors but also for other engineering applications such as control rod worth assessment, generation of high-fidelity database for Artificial intelligence (AI)/machine learning (ML) training, design optimization and multi-resolution modeling.

Cardinal↗

Computer aided systems human engineering: A hypermedia tool

The Computer Aided Systems Human Engineering (CASHE) system, Version 1.0, is a multimedia ergonomics database on CD-ROM for the Apple Macintosh II computer, being developed for use by human system designers, educators, and researchers. It will initially be available on CD-ROM and will allow users to access ergonomics data and models stored electronically as text, graphics, and audio. The CASHE CD-ROM, Version 1.0 will contain the Boff and Lincoln (1988) Engineering Data Compendium, MIL-STD-1472D and a unique, interactive simulation capability, the Perception and Performance Prototyper. Its features also include a specialized data retrieval, scaling, and analysis capability and the state of the art in information retrieval, browsing, and navigation.

Boff, Kenneth R.↗

A Heuristic Approach to Correlating ERAM Flight Data from Twenty Centers

Among its many other functions, the Federal Aviation Administration’s En Route Automation Modernization (ERAM) provides external systems with real-time air traffic data for flights in enroute airspace in the National Airspace System. It replaced the En Route Host computer and backup system used at 20 FAA Air Route Traffic Control Centers (Centers) nationwide. Among the new features of ERAM, its output data stream of flight plan and track data includes a unique identifier for a flight originating in any one of the 20 ERAM Centers. The unique identifier, called the Global Unique Flight Identifier (GUFI), is persistent across all the Centers that track the flight. However, certain factors make it difficult to correlate data using the GUFI. First, the value of the GUFI is only unique within a time window of seven days. Second, the GUFI is attached only to flight-plan related data messages. Finally, track positions reported by ERAM do not reference the GUFI. In order to correlate historical as well as real time flight-plan and position related ERAM data, an efficient, heuristic approach was developed, and a prototype was developed. The approach showed that the processing speed, through parallel processing, is sufficient to correlate ERAM data in real-time. As described in this paper, when there are multiple track positions reported from multiple Centers within a few seconds, each position is assigned with a weighted score to indicate the quality of the position relative to its last know position. The weighted score can be used to eliminate potentially duplicate track positions. The approach is database-agnostic, and can be implemented in a Big Data system such as an Apache Hadoop system, as well as in traditional database systems.

Correlating ERAM Flight Data↗

An expert system for satellite and instrument data anomaly and fault isolation

A prototype Generic Payload Operations Control System (GPOCC) is being developed at the NASA Jet Propulsion Laboratory to provide a low-cost command and control processing center for science instruments and small payloads. The GPOCC supports the difficult transition from integration and test to flight operations. The prototype will incorporate four expert systems to perform telemetry, command, and mission planning functions as well as telecommunications scheduling. The first of these expert systems to be developed will perform telemetry data analysis and fault isolation, as well as propose corrective action. This Data Analysis Module (DAM) will monitor telemetry data and perform continual data monitoring and trend analysis based on a knowledge base and historic data archived on an optical disk storage device. The system maintains a continuous knowledge database of past system performance characteristics. The goal of the Data Analysis Module is to achieve consistent, dependable and validatable performance, to demonstrate thorough, reliable and fast reasoning, and to reduce the concentration demanded of flight analysis personnel.

Busse, Carl↗