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All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Kepler Planet Detection Mission: Introduction and First Results

The Kepler Mission is designed to determine the frequency of Earth-size and rocky planets in and near the habitable zone (HZ) of solar-like stars. The HZ is defined to be the region of space where a rocky planet could maintain liquid water on its surface. Kepler is the 10th competitively-selected Discovery Mission and was launched on March 6, 2009. Since completing its commissioning, Kepler has observed over 156,000 stars simultaneously and near continuously to search for planets that periodically pass in front of their host star (transit). The photometric precision is approximately 23 ppm for 50% of the 12th magnitude dwarf stars for an integration period of 6.5 hours. During the first 3 months of operation the photometer detected transit-like signatures from more than 200 stars. Careful examination shows that many of these events are false-positives such as small stars orbiting large stars or blends of target stars with eclipsing binary stars. Ground-based follow-up observations confirm the discovery of five new exoplanets with sizes between 0.37 andl.6 Jupiter radii (R(sub J)) and orbital periods ranging from 3.2 to 4.9 days. Ground-based observations with the Keck 1, Hobby-Ebberly, Hale, WIYN, MMT, Tillinghast, Shane, and Nordic Optical Telescopes are used to vet the planetary candidates and measure the masses of the putative planets. Observations of occultations and phase variations of hot, short-period planets such as HT-P-7b provide a probe of atmospheric properties. Asteroseismic analysis already shows the presence of p-mode oscillations in several stars. Such observations will be used to measure the mean stellar density and infer the stellar size and age. For stars too dim to permit asteroseismology, observations of the centroid motion of target stars will be used to measure the parallax and be combined with photometric measurements to estimate stellar sizes. Four open clusters are being observed to determine stellar rotation rates as a function of age and spectral type. Many different types of stellar variability are observed with unprecedented precision and over a wide range of time scales. Solar-like photometric variability of thousands of field stars is being studied to determine how photometric variability and the stellar rotation rates change with stellar age and metallicity. A wide variety of other astrophysical phenomena have also been observed. The data are being analyzed at the Ames Research Center and archived at the MAST at STScI. The Kepler Mission also supports a vigorous Guest Observer Program.

Borucki, William↗
DOE OSTI2020

Data Analytics Applied to Coal Fired Boilers for Detecting Leaks

Data analytics were used to detect boiler leaks from five different coal-fired boilers including both subcritical and supercritical systems. Discriminant functions were developed that detected leaks up to two weeks prior to forced plant shutdowns for repairs. The leaks were identified to occur at different sections of the boiler for each plant, including waterwalls, economizer and superheater using conventional process measurement data. Leaking conditions were detected with a high degree of confidence (≪ 1% misclassified observations) and were able to distinguish normal operations from those time periods with steam leaks even while operating the power plants in power cycling mode.Multivariable statistical analyses, including Principal Component (PCA), cluster, and Fischer Discriminant Analysis (FDA) were used to characterize the leak occurrence. Normal and operational states with steam leaks were provided in the original process datasets. These datasets were split into two different groups for training and validation purposes. The data were sorted chronologically, and every third observation was assigned to training the Discriminant Function Model (DFM) while the rest were reserved for validation. PCA was used to reduce dimensionality of the original datasets. Canonical and FDA analyses were used to investigate the relationship between process variables. The outcome of the analyses revealed that nearly 35,000 observations were classified correctly; less than 0.05% of total observations were misclassified to be leaking, i.e. both false positives and false negatives.

Indrawan, Natarianto↗
NASA NTRS2000

Real Time Intelligent Target Detection and Analysis with Machine Vision

We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

Howard, Ayanna↗
DOE OSTI2021

Validation of Scale-Derived Ages in Wild Juvenile and Adult Steelhead Using Parental-Based Tagging

Abstract Accurate age information is a critical component in fisheries monitoring, management, and research. The ability to assign accurate ages to fish by using nonlethal structures is vital in calculating cohort productivity for fish species with low abundances and variable life histories. A common nonlethal method to assign ages is by interpretation of patterns in scales. Validation of ages is not easily obtained for free-ranging fishes; however, the development of genetic “tags” has expanded age validation opportunities. In this study, we used parental-based genetic tagging to validate ages determined from scales collected from juvenile and adult steelhead Oncorhynchus mykiss in two streams within the Snake River basin. Juvenile scale ages were in agreement with 93% of the known ages. Adult scale ages were in agreement with 89% of the known ages. Although overall bias in juvenile ages was very low, we saw a slight positive bias in younger fish (young of the year and age 1) and a small negative bias in older juveniles (ages 2–4). A small negative bias in ages of adults was a consequence of errors in freshwater age. The errors observed did not significantly bias age compositions because the 90% confidence intervals about the age proportions based on scales contained the known proportions; therefore, scale analysis is an acceptable method for assigning ages to Snake River steelhead. We discuss the value of validated known-age scales as a reference collection, and as an illustrative use, we constructed a circulus count guide to aid technicians in identifying missing annuli and distinguishing true from false annuli. To demonstrate the use of the circulus guidelines, we reanalyzed samples with age discrepancies, applying the circulus count data and the known age to identify mistakes.

Reinhardt, Leslie↗
NASA NTRS2007

NASA Tech Briefs, December 2007

Topics include: Ka-Band TWT High-Efficiency Power Combiner for High-Rate Data Transmission; Reusable, Extensible High-Level Data-Distribution Concept; Processing Satellite Imagery To Detect Waste Tire Piles; Monitoring by Use of Clusters of Sensor-Data Vectors; Circuit and Method for Communication Over DC Power Line; Switched Band-Pass Filters for Adaptive Transceivers; Noncoherent DTTLs for Symbol Synchronization; High-Voltage Power Supply With Fast Rise and Fall Times; Waveguide Calibrator for Multi-Element Probe Calibration; Four-Way Ka-Band Power Combiner; Loss-of-Control-Inhibitor Systems for Aircraft; Improved Underwater Excitation-Emission Matrix Fluorometer; Metrology Camera System Using Two-Color Interferometry; Design and Fabrication of High-Efficiency CMOS/CCD Imagers; Foam Core Shielding for Spacecraft CHEM-Based Self-Deploying Planetary Storage Tanks Sequestration of Single-Walled Carbon Nanotubes in a Polymer PPC750 Performance Monitor Application-Program-Installer Builder Using Visual Odometry to Estimate Position and Attitude Design and Data Management System Simple, Script-Based Science Processing Archive Automated Rocket Propulsion Test Management Online Remote Sensing Interface Fusing Image Data for Calculating Position of an Object Implementation of a Point Algorithm for Real-Time Convex Optimization Handling Input and Output for COAMPS Modeling and Grid Generation of Iced Airfoils Automated Identification of Nucleotide Sequences Balloon Design Software Rocket Science 101 Interactive Educational Program Creep Forming of Carbon-Reinforced Ceramic-Matrix Composites Dog-Bone Horns for Piezoelectric Ultrasonic/Sonic Actuators Benchtop Detection of Proteins Recombinant Collagenlike Proteins Remote Sensing of Parasitic Nematodes in Plants Direct Coupling From WGM Resonator Disks to Photodetectors Using Digital Radiography To Image Liquid Nitrogen in Voids Multiple-Parameter, Low-False-Alarm Fire-Detection Systems Mosaic-Detector-Based Fluorescence Spectral Imager Plasmoid Thruster for High Specific-Impulse Propulsion Analysis Method for Quantifying Vehicle Design Goals Improved Tracking of Targets by Cameras on a Mars Rover Sample Caching Subsystem Multistage Passive Cooler for Spaceborne Instruments GVIPS Models and Software Stowable Energy-Absorbing Rocker-Bogie Suspensions

Source record↗
DOE OSTI2023

Realistic application of short-lived fission product delayed neutron, gamma-ray analysis for simultaneous nondestructive trace quantification of U, Pu mixtures on cellulose swipes

Detection and characterization of fissile traces are of interest to the international nuclear nonproliferation community, including the International Atomic Energy Agency. Pre-inspection check samples are analyzed by neutron activation analysis at the High Flux Isotope Reactor operated by the Oak Ridge National Laboratory under the umbrella of the IAEA Network of Analytical Laboratories. The simultaneous quantification of U and Pu mixtures was accomplished using the combined delayed neutron (DN) delayed gamma-ray (DG) method to analyze cellulose swipes with actinide loading <1ng in a blind field trial. The total fissile quantity was measured by the DN counts and the relative proportions of U, Pu were determined by calibration of the 104 Tc / 141 Ba fission product count ratio using known mixtures. The DNDG method demonstrated high accuracy in flagging the presence of 239 Pu in uranium down to <100 pg mass loading. In conclusion, peak significance tests helped to control false positive Pu flagging and simultaneous quantification of U and Pu loading was accomplished on samples that passed the significance tests.

36 MATERIALS SCIENCE↗
NASA NTRS1973

Census cities experiment in urban change detection

The author has identified the following significant results. Work continues on mapping of 1970 urban land use from 1970 census contemporaneous aircraft photography. In addition, change detection analysis from 1972 aircraft photography is underway for several urban test sites. Land use maps, mosaics, and census overlays for the two largest urban test sites are nearing publication readiness. Preliminary examinations of ERTS-1 imagery of San Francisco Bay have been conducted which show that tracts of land of more than 10 acres in size which are undergoing development in an urban setting can be identified. In addition, each spectral band is being evaluated as to its utility for urban analyses. It has been found that MSS infrared band 7 helps to differentiate intra-urban land use details not found in other MSS bands or in the RBV coverage of the same scene. Good quality false CIR composites have been generated from 9 x 9 inch positive MSS bands using the Diazo process.

Wray, J. R.↗
NASA NTRSDate not supplied

Performance Evaluation of a Shaped Sonic Boom Detector and Classifier

NASA will soon fly the X‑59 aircraft over selected communities to evaluate community responses to shaped sonic booms. Community tests will include dozens of deployed acoustic sensors capable of measuring and detecting shaped sonic boom waveforms in situ for rapid onboard analysis. To this end, we present a sonic boom detector and classifier. The sonic boom detector identifies a shaped sonic boom within a measured acoustical waveform by calculating the cross-correlation with a template shaped sonic boom waveform. The sonic boom classifier determines whether the identified event is indeed a shaped sonic boom based on the correlation coefficient and the calculated noise exposure level. We evaluate these algorithms using simulations of on- and off-design X-59 sonic boom waveforms injected into previously measured 30 s ambient noise recordings. Results of this case study indicate that the detector identifies a sonic boom with an accuracy of ±100 ms in 99.98% of the cases. Furthermore, for a given 30 s measurement, the classifier shows true-positive rates of approximately 0.9999 when the false-positive rate is 10e-3. The case study demonstrates that the recommended onboard sonic boom detector and classifier should be highly capable of identifying shaped sonic booms.

sonic boom↗
DOE OSTI2022

AviSense: A Real-time System for Detection, Classification, and Analysis of Aviation Signals

Wireless systems are an integral part of aviation. Apart from their apparent use in air-to-ground communication, wireless systems play a crucial role in avionic functions including navigation and landing. An interference-free wireless environment is therefore critical for the uninterrupted operation and safety of an aircraft. Hence, there is an urgency for airport facilities to acquire the capability to continuously monitor aviation frequency bands for real-time detection of interference and anomalies. To meet this critical need, we design and build AviSense, an SDR-based real-time, versatile system for monitoring aviation bands. AviSense detects and characterizes signal activities to enable practical and effective anomaly detection. We identify and tackle the challenges posed by a diverse set of critical aviation bands and technologies. We evaluate our methodology with real-world aviation signal measurements and two custom datasets of anomalous signals. We find that our signal classification capability achieves a true positive rate of ~99%, with few exceptions, and a false positive rate of less than 4%. We also demonstrate that AviSense can effectively distinguish between different types of anomalies. We build and evaluate a prototype implementation of AviSense that supports distributed monitoring.

42 ENGINEERING↗
DOE OSTI2021

Analysis of Automated Fault Detection and Diagnosis Records as an Indicator of HVAC Fault Prevalence: Methodology and Preliminary Results

Faults in commercial buildings can cause energy waste and other performance problems such as reduced occupant comfort, reduced equipment longevity, and increased noise. However, it is currently unknown how commonly faults occur in different equipment types. A method has been developed to estimate the prevalence of faults in air handling units, air terminal units, and rooftop units. This method includes two types of data. The first is data from several automated fault detection and diagnostics (AFDD) software technologies. This type of data provides a large sample that represents a wide range of building types, geographical locations, and equipment types. It includes fault diagnoses from thousands of buildings around the United States, as well as anonymized metadata describing the building and equipment characteristics. The number of fault records is in the order of 107. However, despite the size and richness of the data sample, this data contains some degree of inaccuracy, i.e., false positive and false negative findings. Therefore, the study includes a second type of data, coming from manual inspection of buildings that have had the same AFDD methods applied to them (from the commercial AFDD offerings). Since the field tests are conducted in buildings with AFDD-generated fault prevalence data, they can be combined with the larger sample size to provide insight into the potential biases or lower sensitivity of the AFDD data. Once a library of fault prevalence data is built, it will be studied to provide further insight into the drivers of fault prevalence, for example, whether prevalence is correlated with building type, geographical location (which is tied to climate and to utility rates), building size, etc. This paper describes the methods developed for this study and illustrates them with preliminary data. It discusses some of the challenges of harmonizing disparate outputs from multiple AFDD vendors, application of a unifying fault taxonomy, and fault prevalence metrics.

Ebrahimi Fakhar, Amir↗
DOE OSTI2023

Clear-sky detection for PV degradation analysis using multiple regression

A method is presented to detect clear-sky periods for plane-of-array irradiance time-averaged data that is based on the algorithm originally described by Reno and Hansen. Here we show this new method improves the state-of-the-art by providing accurate detection at longer data averaging intervals. Moreover, our new method detects clear periods in plane-of-array data, which is novel. The new method is developed by applying a Design of Experiment approach to optimize the parameters used in the Reno method, and Monte Carlo simulations are used to understand the robustness of the found parameters. Clear-sky detection accuracy is compared among four methods: the Reno method, the default clear-sky filter in RdTools, the Ellis method, and the method outlined in this work, using a hand-labeled two-year data set of 1-min plane-of-array irradiance for a fixed tilt system. The RdTools clear-sky filter is marred by excessive false positives. The other methods all perform well at 1-min data intervals; the method developed here provides more accurate detection at longer data averaging intervals. We show that the parameters are directly linked to the data frequency in the hope that these input variables may not have to be optimized for every data frequency and location. However, only a single fixed system in one location was carefully examined. Finally, we illustrate how accurate determination of clear-sky conditions helps to eliminate data noise and bias in the assessment of long-term performance of PV plants.

14 SOLAR ENERGY↗
NASA NTRS2012

Initial Evaluation of a Conflict Detection Tool in the Terminal Area

Despite the recent economic recession and its adverse impact on air travel, the Federal Aviation Administration (FAA) continues to forecast an increase in air traffic demand that may see traffic double or triple by the year 2025. Increases in air traffic will burden the air traffic management system, and higher levels of safety and efficiency will be required. The air traffic controllers primary task is to ensure separation between aircraft in their airspace and keep the skies safe. As air traffic is forecasted to increase in volume and complexity [1], there is an increased likelihood of conflicts between aircraft, which adds risk and inefficiency to air traffic management and increases controller workload. To attenuate these factors, recent ATM research has shown that air and ground-based automation tools could reduce controller workload, especially if the automation is focused on conflict detection and resolution. Conflict Alert is a short time horizon conflict detection tool deployed in the Terminal Radar Approach Control (TRACON), which has limited utility due to the high number of false alerts generated and its use of dead reckoning to predict loss of separation between aircraft. Terminal Tactical Separation Assurance Flight Environment (T-TSAFE) is a short time horizon conflict detection tool that uses both flight intent and dead reckoning to detect conflicts. Results of a fast time simulation experiment indicated that TTSAFE provided a more effective alert lead-time and generated less false alerts than Conflict Alert [2]. TSAFE was previously tested in a Human-In-The-Loop (HITL) simulation study that focused on the en route phase of flight [3]. The current study tested the T-TSAFE tool in an HITL simulation study, focusing on the terminal environment with current day operations. The study identified procedures, roles, responsibilities, information requirements and usability, with the help of TRACON controllers who participated in the experiment. Metrics such as lead alert time, alert response time, workload, situation awareness and other measures were statistically analyzed. These metrics were examined from an overall perspective and comparisons between conditions (altitude resolutions via keyboard entry vs. ADS-B entry) and controller positions (two final approach sectors and two feeder sectors) were also examined. Results of these analyses and controller feedback provided evidence of T-TSAFE s potential promise as a useful air traffic controller tool. Heuristic analysis also provided information on ways in which the T-TSAFE tool can be improved. Details of analyses results will be presented in the full paper.

Verma Savita Arora↗
NASA NTRS2000

Synthetic spectra of simulated terrestrial atmospheres containing possible biomarker gases

NASA's proposed Terrestrial Planet Finder, a space-based interferometer, will eventually allow spectroscopic analyses of the atmospheres of extrasolar planets. Such analyses would provide information about the existence of life on these planets. One strategy in the search for life is to look for evidence of O3 (and hence O2) in a planet's atmosphere; another is to look for gases that might be present in an atmosphere analogous to that of the inhabited early Earth. In order to investigate these possibilities, we have calculated synthetic spectra for several hypothetical terrestrial-type atmospheres. The model atmospheres represent four different scenarios. The first two, representing inhabited terrestrial planets, are an Earth-like atmosphere containing variable amounts of oxygen and an early Earth-type atmosphere containing methane. In addition, two cases representing Mars-like and early Venus-like atmospheres were evaluated, to provide possible "false positive" spectra. The calculated spectra suggest that ozone could be detected by an instrument like Terrestrial Planet Finder if the O2 concentration in the planet's atmosphere is > or = 200 ppm, or 10(-3) times the present atmospheric level. Methane should be observable on an early-Earth type planet if it is present in concentrations of 100 ppm or more. Methane has both biogenic and abiogenic sources, but concentrations exceeding 1000 ppm, or 0.1% by volume, would be difficult to produce from abiogenic sources alone. High methane concentrations in a planet's atmosphere are therefore another potential indicator for extraterrestrial life.

NASA Discipline Exobiology↗
DOE OSTI2022

Graph Neural Networks for low-energy event classification & reconstruction in IceCube

IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The classification and reconstruction of events from the in-ice detectors play a central role in the analysis of data from IceCube. Reconstructing and classifying events is a challenge due to the irregular detector geometry, inhomogeneous scattering and absorption of light in the ice and, below 100 GeV, the relatively low number of signal photons produced per event. To address this challenge, it is possible to represent IceCube events as point cloud graphs and use a Graph Neural Network (GNN) as the classification and reconstruction method. The GNN is capable of distinguishing neutrino events from cosmic-ray backgrounds, classifying different neutrino event types, and reconstructing the deposited energy, direction and interaction vertex. Based on simulation, we provide a comparison in the 1 GeV–100 GeV energy range to the current state-of-the-art maximum likelihood techniques used in current IceCube analyses, including the effects of known systematic uncertainties. For neutrino event classification, the GNN increases the signal efficiency by 18% at a fixed background rate, compared to current IceCube methods. Alternatively, the GNN offers a reduction of the background (i.e. false positive) rate by over a factor 8 (to below half a percent) at a fixed signal efficiency. For the reconstruction of energy, direction, and interaction vertex, the resolution improves by an average of 13%–20% compared to current maximum likelihood techniques in the energy range of 1 GeV–30 GeV. The GNN, when run on a GPU, is capable of processing IceCube events at a rate nearly double of the median IceCube trigger rate of 2.7 kHz, which opens the possibility of using low energy neutrinos in online searches for transient events.

47 OTHER INSTRUMENTATION↗
NASA NTRS2003

A New Objective Technique for Verifying Mesoscale Numerical Weather Prediction Models

This report presents a new objective technique to verify predictions of the sea-breeze phenomenon over east-central Florida by the Regional Atmospheric Modeling System (RAMS) mesoscale numerical weather prediction (NWP) model. The Contour Error Map (CEM) technique identifies sea-breeze transition times in objectively-analyzed grids of observed and forecast wind, verifies the forecast sea-breeze transition times against the observed times, and computes the mean post-sea breeze wind direction and speed to compare the observed and forecast winds behind the sea-breeze front. The CEM technique is superior to traditional objective verification techniques and previously-used subjective verification methodologies because: It is automated, requiring little manual intervention, It accounts for both spatial and temporal scales and variations, It accurately identifies and verifies the sea-breeze transition times, and It provides verification contour maps and simple statistical parameters for easy interpretation. The CEM uses a parallel lowpass boxcar filter and a high-order bandpass filter to identify the sea-breeze transition times in the observed and model grid points. Once the transition times are identified, CEM fits a Gaussian histogram function to the actual histogram of transition time differences between the model and observations. The fitted parameters of the Gaussian function subsequently explain the timing bias and variance of the timing differences across the valid comparison domain. Once the transition times are all identified at each grid point, the CEM computes the mean wind direction and speed during the remainder of the day for all times and grid points after the sea-breeze transition time. The CEM technique performed quite well when compared to independent meteorological assessments of the sea-breeze transition times and results from a previously published subjective evaluation. The algorithm correctly identified a forecast or observed sea-breeze occurrence or absence 93% of the time during the two- month evaluation period from July and August 2000. Nearly all failures in CEM were the result of complex precipitation features (observed or forecast) that contaminated the wind field, resulting in a false identification of a sea-breeze transition. A qualitative comparison between the CEM timing errors and the subjectively determined observed and forecast transition times indicate that the algorithm performed very well overall. Most discrepancies between the CEM results and the subjective analysis were again caused by observed or forecast areas of precipitation that led to complex wind patterns. The CEM also failed on a day when the observed sea- breeze transition affected only a very small portion of the verification domain. Based on the results of CEM, the RAMS tended to predict the onset and movement of the sea-breeze transition too early and/or quickly. The domain-wide timing biases provided by CEM indicated an early bias on 30 out of 37 days when both an observed and forecast sea breeze occurred over the same portions of the analysis domain. These results are consistent with previous subjective verifications of the RAMS sea breeze predictions. A comparison of the mean post-sea breeze winds indicate that RAMS has a positive wind-speed bias for .all days, which is also consistent with the early bias in the sea-breeze transition time since the higher wind speeds resulted in a faster inland penetration of the sea breeze compared to reality.

Case, Jonathan L.↗
DOE OSTI2023

A study of examiner accuracy in cartridge case comparisons. Part 2: Examiner use of the AFTE range of conclusions

Here, this report describes an analysis of how examiners used the Association of Firearm and Toolmark Examiners (AFTE) Range of Conclusions in a controlled study undertaken to estimate examiner error rates in comparing cartridge cases. Results of the error rate analysis are reported in [1]; this paper focuses on a broader analysis of how the entire collection of classification categories, especially those in the Inconclusive range, were used by the participating examiners. Volunteer active examiners with AFTE membership or working in laboratories that participate in Association of Crime Laboratory Directors (ASCLD) were provided with 15 sets of three known and one questioned cartridge cases fired from a collection of 25 new Ruger SR9 handguns. Remington 9-mm Luger (manufacturer designation L9MM3) ammunition was used and comparison sets were made up of cartridge cases fired within 100 cartridges of each other for each gun. Examiners were provided with a background survey, an answer sheet allowing for the AFTE Range of Conclusions, and return shipping materials. The participating examiners were provided with both same-source and different-source comparison sets allowing the study to assess both error rates. Responses were received from 218 participating examiners. The overall rate of false-negatives was estimated as 0.367 % from comparisons known to be from the same firearm but reported as eliminations. The overall rate of false-positives was estimated as 1.01 % from comparisons known to be from different firearms but reported as identifications. In the case of true different-source examinations, it is clear that the three Inconclusive categories and the Elimination category are not used consistently by all examiners. We identify five different apparent patterns of use of the AFTE Range of Conclusions scale, and discuss possible reasons for and implications of these differences.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1992

Automated anomaly detection for Orbiter High Temperature Reusable Surface Insulation

The description, analysis, and experimental results of a method for identifying possible defects on High Temperature Reusable Surface Insulation (HRSI) of the Orbiter Thermal Protection System (TPS) is presented. Currently, a visual postflight inspection of Orbiter TPS is conducted to detect and classify defects as part of the Orbiter maintenance flow. The objective of the method is to automate the detection of defects by identifying anomalies between preflight and postflight images of TPS components. The initial version is intended to detect and label gross (greater than 0.1 inches in the smallest dimension) anomalies on HRSI components for subsequent classification by a human inspector. The approach is a modified Golden Template technique where the preflight image of a tile serves as the template against which the postflight image of the tile is compared. Candidate anomalies are selected as a result of the comparison and processed to identify true anomalies. The processing methods are developed and discussed, and the results of testing on actual and simulated tile images are presented. Solutions to the problems of brightness and spatial normalization, timely execution, and minimization of false positives are also discussed.

Cooper, Eric G.↗
NASA NTRS2010

Support for Systematic Code Reviews with the SCRUB Tool

SCRUB is a code review tool that supports both large, team-based software development efforts (e.g., for mission software) as well as individual tasks. The tool was developed at JPL to support a new, streamlined code review process that combines human-generated review reports with program-generated review reports from a customizable range of state-of-the-art source code analyzers. The leading commercial tools include Codesonar, Coverity, and Klocwork, each of which can achieve a reasonably low rate of false-positives in the warnings that they generate. The time required to analyze code with these tools can vary greatly. In each case, however, the tools produce results that would be difficult to realize with human code inspections alone. There is little overlap in the results produced by the different analyzers, and each analyzer used generally increases the effectiveness of the overall effort. The SCRUB tool allows all reports to be accessed through a single, uniform interface (see figure) that facilitates brows ing code and reports. Improvements over existing software include significant simplification, and leveraging of a range of commercial, static source code analyzers in a single, uniform framework. The tool runs as a small stand-alone application, avoiding the security problems related to tools based on Web browsers. A developer or reviewer, for instance, must have already obtained access rights to a code base before that code can be browsed and reviewed with the SCRUB tool. The tool cannot open any files or folders to which the user does not already have access. This means that the tool does not need to enforce or administer any additional security policies. The analysis results presented through the SCRUB tool s user interface are always computed off-line, given that, especially for larger projects, this computation can take longer than appropriate for interactive tool use. The recommended code review process that is supported by the SCRUB tool consists of three phases: Code Review, Developer Response, and Closeout Resolution. In the Code Review phase, all tool-based analysis reports are generated, and specific comments from expert code reviewers are entered into the SCRUB tool. In the second phase, Developer Response, the developer is asked to respond to each comment and tool-report that was produced, either agreeing or disagreeing to provide a fix that addresses the issue that was raised. In the third phase, Closeout Resolution, all disagreements are discussed in a meeting of all parties involved, and a resolution is made for all disagreements. The first two phases generally take one week each, and the third phase is concluded in a single closeout meeting.

Holzmann, Gerald J.↗