Results for “Automatic Data Processing” — Page 68

DOE OSTI2016

ORIGAMI Automator Primer. Automated ORIGEN Source Terms and Spent Fuel Storage Pool Analysis

Source terms and spent nuclear fuel (SNF) storage pool decay heat load analyses for operating nuclear power plants require a large number of Oak Ridge Isotope Generation and Depletion (ORIGEN) calculations. SNF source term calculations also require a significant amount of bookkeeping to track quantities such as core and assembly operating histories, spent fuel pool (SFP) residence times, heavy metal masses, and enrichments. The ORIGEN Assembly Isotopics (ORIGAMI) module in the SCALE code system provides a simple scheme for entering these data. However, given the large scope of the analysis, extensive scripting is necessary to convert formats and process data to create thousands of ORIGAMI input files (one per assembly) and to process the results into formats readily usable by follow-on analysis tools. This primer describes a project within the SCALE Fulcrum graphical user interface (GUI) called ORIGAMI Automator that was developed to automate the scripting and bookkeeping in large-scale source term analyses. The ORIGAMI Automator enables the analyst to (1) easily create, view, and edit the reactor site and assembly information, (2) automatically create and run ORIGAMI inputs, and (3) analyze the results from ORIGAMI. ORIGAMI Automator uses the standard ORIGEN binary concentrations files produced by ORIGAMI, with concentrations available at all time points in each assembly’s life. The GUI plots results such as mass, concentration, activity, and decay heat using a powerful new ORIGEN Post-Processing Utility for SCALE (OPUS) GUI component. This document includes a description and user guide for the GUI, a step-by-step tutorial for a simplified scenario, and appendices that document the file structures used.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1986

Mission adaptive wing soars at NASA Facility

Research pilots have flown the Mission Adaptive Wing (MAW) aircraft, a highly modified F-111 jet fighter, from subsonic speeds up to Mach 1.4 in initial flight tests. The inital test flights are clearing the envelope with the wings flexed at various curvatures. This process allows further research data to be safely gathered so that designers of future variable camber wing aircraft have the best information possible. The altitude envelope was cleared from 27,500 down to 7,500 feet where denser air can cause more stress on the aircraft. Testing with the aircraft was conducted with wing sweep angles of 26 and 58 degrees. At the conclusion of the performance tests in the manual configuration, the system will be reconfigured for automatic mode tests. The limited automatic modes include maneuver camber control where the wings are deflected automatically to the best lift versus drag combination for a particular speed; cruise camber control which can help protect the aircraft from high G stresses; and maneuver enhancement/gust alleviation which is designed to improve the aircraft's up and down movement response to pilot commands and reduce the aircraft response to turbulence.

Rahn, D.↗

NASA NTRS1994

Automation technology using Geographic Information System (GIS)

Airport Surface Movement Area is but one of the actions taken to increase the capacity and safety of existing airport facilities. The System Integration Branch (SIB) has designed an integrated system consisting of an electronic moving display in the cockpit, and includes display of taxi routes which will warn controllers and pilots of the position of other traffic and warning information automatically. Although, this system has in test simulation proven to be accurate and helpful; the initial process of obtaining an airport layout of the taxi-routes and designing each of them is a very tedious and time-consuming process. Other methods of preparing the display maps are being researched. One such method is the use of the Geographical Information System (GIS). GIS is an integrated system of computer hardware and software linking topographical, demographic and other resource data that is being referenced. The software can support many areas of work with virtually unlimited information compatibility due to the system's open architecture. GIS will allow us to work faster with increased efficiency and accuracy while providing decision making capabilities. GIS is currently being used at the Langley Research Center with other applications and has been validated as an accurate system for that task. GIS usage for our task will involve digitizing aerial photographs of the topology for each taxi-runway and identifying each position according to its specific spatial coordinates. The information currently being used can be integrated with the GIS system, due to its ability to provide a wide variety of user interfaces. Much more research and data analysis will be needed before this technique will be used, however we are hopeful this will lead to better usage of man-power and technological capabilities for the future.

Brooks, Cynthia L.↗

NASA NTRS1997

Detection and Monitoring of Stratigraphic Markers and Temperature Trends at the Greenland Ice Sheet Project 2 Using Passive-Microwave Remote-Sensing Data

Satellite passive-microwave sensors provide a sensitive means of studying ice-sheet surface processes that assists ice-core interpretation and can extend local observations across regional scales. Analysis of special sensor microwave/imager (SSM/I) brightness temperature (TB) data supports ice-core research in two specific ways. First, the summer hoar complex layers used to date the Holocene portion of the Greenland Ice Sheet Project 2 ice core can be defined temporally and spatially by SSM/I 37-GHz vertically (V) and horizontally (H) polarized B ratio (V/H) trends. Second, comparison of automatic weather station temperatures to SSM/I 37-GHz V TB data shows that they are an effective proxy temperature record in this region. Also, the TB data can be correlated with proxy temperature trends from stable-isotope-ratio (delta O-18 and delta-D) profiles from snow pits and this allows the assignment of dates to specific snow depths.

Shuman, C. A.↗

NASA NTRS2000

Comparison of Three Wind Measuring Systems for Flight Test

A preliminary field test of the accuracy of wind velocity measurements obtained using global positioning system-tracked rawinsonde balloons has been performed. Wind comparisons have been conducted using global positioning system (GPS) and radio automatic theodolite sounder (RATS) rawinsondes and a high-precision range instrumentation radar-tracked reflector. Wind velocity differences between the GPS rawinsondes and the radar were significantly less than between the RATS rawinsondes and the radar. These limited test results indicate a root-mean-square wind velocity difference from 4.98 kn (2.56 m/sec) for the radar and RATS to 1.09 kn (0.56 m/sec) for the radar and GPS. Differences are influenced by user reporting requirements, data processing techniques, and the inherent tracking accuracies of the system. This brief field test indicates that the GPS sounding system tracking data are more precise than the RATS system. When high-resolution wind data are needed, use of GPS rawinsonde systems can reduce the burden on range radar operations.

Teets, Edward H., Jr.↗

NASA NTRS2000

Comparison of Three Wind Measuring Systems for Flight Test

A preliminary field test of the accuracy of wind velocity measurements obtained using global positioning system-tracked rawinsonde balloons has been performed. Wind comparisons have been conducted using global positioning system (GPS) and radio automatic theodolite sounder (RATS) rawinsondes and a high-precision range instrumentation radar-tracked reflector. Wind velocity differences between the GPS rawinsondes and the radar were significantly less than between the RATS rawinsondes and the radar. These limited test results indicate a root-mean-square wind velocity difference from 4.98 kn (2.56 m/sec) for the radar and RATS to 1.09 kn (0.56 m/sec) for the radar and GPS. Differences are influenced by user reporting requirements, data processing techniques, and the inherent tracking accuracies of the system. This brief field test indicates that the GPS sounding system tracking data are more precise than the RATS system. When high-resolution wind data are needed, use of GPS rawinsonde systems can reduce the burden on range radar operations.

Teets, Edward H., Jr.↗

DOE OSTI2015

TU-G-303-02: Robust Radiomics Methods for PET and CT Imaging

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding requirements for reliable radiomic models, including robustness of metrics, adequate predictive accuracy, and generalizability. Understanding the methodology behind radiomic-genomic (’radiogenomics’) correlations. Research supported by NIH (US), CIHR (Canada), and NSERC (Canada)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-G-303-03: Machine Learning to Improve Human Learning From Longitudinal Image Sets

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding requirements for reliable radiomic models, including robustness of metrics, adequate predictive accuracy, and generalizability. Understanding the methodology behind radiomic-genomic (’radiogenomics’) correlations. Research supported by NIH (US), CIHR (Canada), and NSERC (Canada)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-G-303-04: Radiomics and the Coming Pan-Omics Revolution

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding requirements for reliable radiomic models, including robustness of metrics, adequate predictive accuracy, and generalizability. Understanding the methodology behind radiomic-genomic (’radiogenomics’) correlations. Research supported by NIH (US), CIHR (Canada), and NSERC (Canada)

60 APPLIED LIFE SCIENCES↗

NASA NTRS2022

Characterization of Response Times based on Voice Communication and Traffic Surveillance Data

A barrier to the integration of remotely piloted aircraft operations in the U.S. National Airspace System is the latency of voice communications between the air traffic controller and the remote pilot, and the latency of communication between the aircraft and the remote pilot. The latency can be substantial especially when satellite-based beyond-radio-line-of-sight communication and relay through the aircraft are employed. This study uses voice recordings of controller-pilot communications and aircraft track data to establish a baseline of pilot readback latencies and maneuver detection delays in the current piloted operations. A machine learning pipeline was developed to parse the contents of the air traffic control clearances including the callsigns using natural language processing. After manually validating the results obtained using the pipeline, the average pilot readback latency was found to be about 0.6 seconds. The average latency between the end of maneuver (inferred from track data), initiated by the pilot in response to the clearance, and the end of clearance was found to be about 176 seconds for altitude change commands, 69 seconds for heading change commands, and 182 seconds for speed change commands. The average latency between the beginning of maneuver and the end of clearance was found to be about 17 seconds for altitude change commands, 17seconds for heading change commands, and 25 seconds for speed change commands.

controller-pilot communication, communication late↗

NASA NTRS2022

Characterization of Response Times Based on Voice Communication and Traffic Surveillance Data

A barrier to the integration of remotely piloted aircraft operations in the U.S. National Airspace System is the latency of voice communications between the air traffic controller and the remote pilot, and the latency of communication between the aircraft and the remote pilot. The latency can be substantial especially when satellite-based beyond-radio-line-of-sight communication and relay through the aircraft are employed. This study uses voice recordings of controller-pilot communications and aircraft track data to establish a baseline of pilot readback latencies and maneuver detection delays in the current piloted operations. A machine learning pipeline was developed to parse the contents of the air traffic control clearances including the callsigns using natural language processing. After manually validating the results obtained using the pipeline, the average pilot readback latency was found to be about 0.6 seconds. The average latency between the end of maneuver (inferred from track data), initiated by the pilot in response to the clearance, and the end of clearance was found to be about 176 seconds for altitude change commands, 69 seconds for heading change commands, and 182 seconds for speed change commands. The average latency between the beginning of maneuver and the end of clearance was found to be about 17 seconds for altitude change commands, 17seconds for heading change commands, and 25 seconds for speed change commands.

controller-pilot communication↗

DOE OSTI2015

TU-G-303-01: Radiomics: Quantitative Imaging in the Service of Improved Treatment Decision Making

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding requirements for reliable radiomic models, including robustness of metrics, adequate predictive accuracy, and generalizability. Understanding the methodology behind radiomic-genomic (’radiogenomics’) correlations. Research supported by NIH (US), CIHR (Canada), and NSERC (Canada)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

An algorithm for charge-integration, pulse-shape discrimination and estimation of neutron/photon misclassification in organic scintillators

Organic scintillators are frequently used for measurements that require sensitivity to both photons and fast neutrons because of their pulse shape discrimination capabilities. In these measurement scenarios, particle identification is commonly handled using the charge-integration pulse shape discrimination method. This method works particularly well for high-energy depositions, but is prone to misclassification for relatively low-energy depositions. A novel algorithm has been developed for automatically performing charge-integration pulse shape discrimination in a consistent and repeatable manner. The algorithm is able to estimate the photon and neutron misclassification corresponding to the calculated discrimination parameters, and is capable of doing so using only the information measured by a single organic scintillator. This paper describes the algorithm and assesses its performance by comparing algorithm-estimated misclassification to values computed via a more traditional time-of-flight estimation. A single data set was processed using four different low-energy thresholds: 40, 60, 90, and 120 keVee. Overall, the results compared well between the two methods; in most cases, the algorithm-estimated values fell within the uncertainties of the TOF-estimated values.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1977

Generalized vegetation map of north Merrit Island based on a simplified multispectral analysis

A simplified system for classification of multispectral data was used for making a generalized map of ground features of North Merritt Island. Subclassification of vegetation within broad categories yielded promising results which led to a completely automatic method and to the production of satisfactory detailed maps. Changes in an area north of Happy Hammocks are evidently related to water relations of the soil and are not associated with the last winter freeze-damage which affected mainly the mangrove species, likely to reestablish themselves by natural processes. A supplementary investigation involving reflectance studies in the laboratory has shown that the reflectance by detached citrus leaves, of wavelengths lying between 400 microns and 700 microns, showed some variation over a period of seven days during which the leaves were kept in a laboratory atmosphere.

Poonai, P.↗

NASA NTRS1990

An engineering approach to automatic programming

An exploratory study of the automatic generation and optimization of symbolic programs using DECOM - a prototypical requirement specification model implemented in pure LISP was undertaken. It was concluded, on the basis of this study, that symbolic processing languages such as LISP can support a style of programming based upon formal transformation and dependent upon the expression of constraints in an object-oriented environment. Such languages can represent all aspects of the software generation process (including heuristic algorithms for effecting parallel search) as dynamic processes since data and program are represented in a uniform format.

Rubin, Stuart H.↗

NASA NTRS2012

Mass Analyzers Facilitate Research on Addiction

The famous go/no go command for Space Shuttle launches comes from a place called the Firing Room. Located at Kennedy Space Center in the Launch Control Center (LCC), there are actually four Firing Rooms that take up most of the third floor of the LCC. These rooms comprise the nerve center for Space Shuttle launch and processing. Test engineers in the Firing Rooms operate the Launch Processing System (LPS), which is a highly automated, computer-controlled system for assembly, checkout, and launch of the Space Shuttle. LPS monitors thousands of measurements on the Space Shuttle and its ground support equipment, compares them to predefined tolerance levels, and then displays values that are out of tolerance. Firing Room operators view the data and send commands about everything from propellant levels inside the external tank to temperatures inside the crew compartment. In many cases, LPS will automatically react to abnormal conditions and perform related functions without test engineer intervention; however, firing room engineers continue to look at each and every happening to ensure a safe launch. Some of the systems monitored during launch operations include electrical, cooling, communications, and computers. One of the thousands of measurements derived from these systems is the amount of hydrogen and oxygen inside the shuttle during launch.

Source record↗

NASA NTRS1999

Quantification of Processing Effects on Filament Wound Pressure Vessels

A computational simulation procedure is described which is designed specifically for the modeling and analysis of filament wound pressure vessels. Cylindrical vessels with spherical or elliptical end caps can be generated automatically. End caps other than spherical or elliptical may be modeled by varying circular sections along the x-axis according to the C C! end cap shape. The finite element model generated is composed of plate type quadrilateral shell elements on the entire vessel surface. This computational procedure can also be sued to generate grid, connectivity and material cards (bulk data) for component parts of a larger model. These bulk data are assigned to a user designated file for finite element structural/stress analysis of composite pressure vessels. The procedure accommodates filament would pressure vessels of all types of shells-of-revolution. It has provisions to readily evaluate initial stresses due to pretension in the winding filaments and residual stresses due to cure temperature.

Aiello, Robert A.↗

DOE OSTI2014

Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

An autonomous metabolomic workflow combining mass spectrometry analysis with tandem mass spectrometry data acquisition was designed to allow for simultaneous data processing and metabolite characterization. Although previously tandem mass spectrometry data have been generated on the fly, the experiments described herein combine this technology with the bioinformatic resources of XCMS and METLIN. We can analyze large profiling datasets and simultaneously obtain structural identifications, as a result of this unique integration. Furthermore, validation of the workflow on bacterial samples allowed the profiling on the order of a thousand metabolite features with simultaneous tandem mass spectra data acquisition. The tandem mass spectrometry data acquisition enabled automatic search and matching against the METLIN tandem mass spectrometry database, shortening the current workflow from days to hours. Overall, the autonomous approach to untargeted metabolomics provides an efficient means of metabolomic profiling, and will ultimately allow the more rapid integration of comparative analyses, metabolite identification, and data analysis at a systems biology level.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗