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NASA NTRS2006

Using Dissimilarity Metrics to Identify Interesting Designs

A computer program helps to blend the power of automated-search software, which is able to generate large numbers of design solutions, with the insight of expert designers, who are able to identify preferred designs but do not have time to examine all the solutions. From among the many automated solutions to a given design problem, the program selects a smaller number of solutions that are worthy of scrutiny by the experts in the sense that they are sufficiently dissimilar from each other. The program makes the selection in an interactive process that involves a sequence of data-mining steps interspersed with visual displays of results of these steps to the experts. At crucial points between steps, the experts provide directives to guide the process. The program uses heuristic search techniques to identify nearly optimal design solutions and uses dissimilarity metrics defined by the experts to characterize the degree to which solutions are interestingly different. The search, data-mining, and visualization features of the program were derived from previously developed risk-management software used to support a risk-centric design methodology

Feather, Martin↗

NASA NTRS2010

Selection Effects in Identifying Magnetic Clouds and the Importance of the Closest Approach Parameter

This study is motivated by the unusually low number of magnetic clouds (MCs) that are strictly identified within interplanetary coronal mass ejections (ICMEs), as observed at 1 AU; this is usually estimated to be around 30% or lower. But a looser definition of MCs may significantly increase this percentage. Another motivation is the unexpected shape of the occurrence distribution of the observers' "closest approach distances" (measured from a MC's axis, and called CA) which drops off somewhat rapidly as |CA| (in % of MC radius) approaches 100%, based on earlier studies. We suggest, for various geometrical and physical reasons, that the |CA|-distribution should be somewhere between a uniform one and the one actually observed, and therefore the 30% estimate should be higher. So we ask, When there is a failure to identify a MC within an ICME, is it occasionally due to a large |CA| passage, making MC identification more difficult, i.e., is it due to an event selection effect? In attempting to answer this question we examine WIND data to obtain an accurate distribution of the number of MCs vs. |CA| distance, whether the event is ICME-related or not, where initially a large number of cases (N=98) are considered. This gives a frequence distribution that is far from uniform, confirming earlier studies. This along with the fact that there are many ICME identification-parameters that do not depend on |CA| suggest that, indeed an MC event selection effect may explain at least part of the low ratio of (No. MCs)/(No. ICMEs). We also show that there is an acceptable geometrical and physical consistency in the relationships for both average "normalized" magnetic field intensity change and field direction change vs. |CA| within a MC, suggesting that our estimates of |CA|, B(sub 0) (magnetic field intensity on the axis), and choice of a proper "cloud coordinate" system (all needed in the analysis) are acceptably accurate. Therefore the MC fitting model (Lepping et al., 1990) is adequate, on average, for our analysis. However, this selection effect is not likely to completely answer our original question, on the unexpected ratio of MCs to ICMEs, so we must look for other factors, such as peculiarities of CME birth conditions. As a by-product of this analysis, we determine that the first order structural effects within a MC due to its interaction with the solar wind, plus the MC's usual expansion at 1 AU (i.e., the non-force free components of the MC's field) are, on average, weakly dependent on radial distance from the MC's axis; that is, in the outer reaches of a typical MC the non-force free effects show up, but even there they are rather weak. Finally, we show that it is not likely that a MC's size distribution statistically controls the occurrence distribution of the estimated |CA|s.

Lepping, R. P.↗

NASA NTRS2005

Identifying Objects via Encased X-Ray-Fluorescent Materials - the Bar Code Inside

Systems for identifying objects by means of x-ray fluorescence (XRF) of encased labeling elements have been developed. The XRF spectra of objects so labeled would be analogous to the external bar code labels now used to track objects in everyday commerce. In conjunction with computer-based tracking systems, databases, and labeling conventions, the XRF labels could be used in essentially the same manner as that of bar codes to track inventories and to record and process commercial transactions. In addition, as summarized briefly below, embedded XRF labels could be used to verify the authenticity of products, thereby helping to deter counterfeiting and fraud. A system, as described above, is called an encased core product identification and authentication system (ECPIAS). The ECPIAS concept is a modified version of that of a related recently initiated commercial development of handheld XRF spectral scanners that would identify alloys or detect labeling elements deposited on the surfaces of objects. In contrast, an ECPIAS would utilize labeling elements encased within the objects of interest. The basic ECPIAS concept is best illustrated by means of an example of one of several potential applications: labeling of cultured pearls by labeling the seed particles implanted in oysters to grow the pearls. Each pearl farmer would be assigned a unique mixture of labeling elements that could be distinguished from the corresponding mixtures of other farmers. The mixture would be either incorporated into or applied to the surfaces of the seed prior to implantation in the oyster. If necessary, the labeled seed would be further coated to make it nontoxic to the oyster. After implantation, the growth of layers of mother of pearl on the seed would encase the XRF labels, making these labels integral, permanent parts of the pearls that could not be removed without destroying the pearls themselves. The XRF labels would be read by use of XRF scanners, the spectral data outputs of which would be converted to alphanumeric data in a digital equivalent data system (DEDS), which is the subject of the previous article. These alphanumeric data would be used to track the pearls through all stages of commerce, from the farmer to the retail customer.

Schramm, Harry F.↗

NASA NTRS2006

Small Body GN and C Research Report: G-SAMPLE - An In-Flight Dynamical Method for Identifying Sample Mass [External Release Version]

G-SAMPLE is an in-flight dynamical method for use by sample collection missions to identify the presence and quantity of collected sample material. The G-SAMPLE method implements a maximum-likelihood estimator to identify the collected sample mass, based on onboard force sensor measurements, thruster firings, and a dynamics model of the spacecraft. With G-SAMPLE, sample mass identification becomes a computation rather than an extra hardware requirement; the added cost of cameras or other sensors for sample mass detection is avoided. Realistic simulation examples are provided for a spacecraft configuration with a sample collection device mounted on the end of an extended boom. In one representative example, a 1000 gram sample mass is estimated to within 110 grams (95% confidence) under realistic assumptions of thruster profile error, spacecraft parameter uncertainty, and sensor noise. For convenience to future mission design, an overall sample-mass estimation error budget is developed to approximate the effect of model uncertainty, sensor noise, data rate, and thrust profile error on the expected estimate of collected sample mass.

in-flight sample-mass identification↗

NASA NTRS2011

Method for Identifying Probable Archaeological Sites from Remotely Sensed Data

Archaeological sites are being compromised or destroyed at a catastrophic rate in most regions of the world. The best solution to this problem is for archaeologists to find and study these sites before they are compromised or destroyed. One way to facilitate the necessary rapid, wide area surveys needed to find these archaeological sites is through the generation of maps of probable archaeological sites from remotely sensed data. We describe an approach for identifying probable locations of archaeological sites over a wide area based on detecting subtle anomalies in vegetative cover through a statistically based analysis of remotely sensed data from multiple sources. We further developed this approach under a recent NASA ROSES Space Archaeology Program project. Under this project we refined and elaborated this statistical analysis to compensate for potential slight miss-registrations between the remote sensing data sources and the archaeological site location data. We also explored data quantization approaches (required by the statistical analysis approach), and we identified a superior data quantization approached based on a unique image segmentation approach. In our presentation we will summarize our refined approach and demonstrate the effectiveness of the overall approach with test data from Santa Catalina Island off the southern California coast. Finally, we discuss our future plans for further improving our approach.

Tilton, James C.↗

NASA NTRS2012

Sensitivity of Ocean Reflectance Inversion Models for Identifying and Discriminating Between Phytoplankton Functional Groups

The daily, synoptic images provided by satellite ocean color instruments provide viable data streams for observing changes in the biogeochemistrY of marine ecosystems. Ocean reflectance inversion models (ORMs) provide a common mechanism for inverting the "color" of the water observed a satellite into marine inherent optical properties (lOPs) through a combination of empiricism and radiative transfer theory. lOPs, namely the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents, describe the contents of the upper ocean, information critical for furthering scientific understanding of biogeochemical oceanic processes. Many recent studies inferred marine particle sizes and discriminated between phytoplankton functional groups using remotely-sensed lOPs. While all demonstrated the viability of their approaches, few described the vertical distributions of the water column constituents under consideration and, thus, failed to report the biophysical conditions under which their model performed (e.g., the depth and thickness of the phytoplankton bloom(s)). We developed an ORM to remotely identifY Noctiluca miliaris and other phytoplankton functional types using satellite ocean color data records collected in the northern Arabian Sea. Here, we present results from analyses designed to evaluate the applicability and sensitivity of the ORM to varied biophysical conditions. Specifically, we: (1) synthesized a series of vertical profiles of spectral inherent optical properties that represent a wide variety of bio-optical conditions for the northern Arabian Sea under aN Miliaris bloom; (2) generated spectral remote-sensing reflectances from these profiles using Hydrolight; and, (3) applied the ORM to the synthesized reflectances to estimate the relative concentrations of diatoms and N Miliaris for each example. By comparing the estimates from the inversion model to those from synthesized vertical profiles, we were able to identifY those bio-optical conditions under which the inversion model performs both well and poorly.

Werdell, P. Jeremy↗

NASA NTRS2013

Ultrasonic Detectors Safely Identify Dangerous, Costly Leaks

In 1990, NASA grounded its space shuttle fleet. The reason: leaks detected in the hydrogen fuel systems of the Space Shuttles Atlantis and Columbia. Unless the sources of the leaks could be identified and fixed, the shuttles would not be safe to fly. To help locate the existing leaks and check for others, Kennedy Space Center engineers used portable ultrasonic detectors to scan the fuel systems. As a gas or liquid escapes from a leak, the resulting turbulence creates ultrasonic noise, explains Gary Mohr, president of Elmsford, New York-based UE Systems Inc., a long-time leader in ultrasonic detector technologies. "In lay terms, the leak is like a dog whistle, and the detector is like the dog ear." Because the ultrasound emissions from a leak are highly localized, they can be used not only to identify the presence of a leak but also to help pinpoint a leak s location. The NASA engineers employed UE s detectors to examine the shuttle fuel tanks and solid rocket boosters, but encountered difficulty with the devices limited range-certain areas of the shuttle proved difficult or unsafe to scan up close. To remedy the problem, the engineers created a long-range attachment for the detectors, similar to "a zoom lens on a camera," Mohr says. "If you are on the ground, and the leak is 50 feet away, the detector would now give you the same impression as if you were only 25 feet away." The enhancement also had the effect of reducing background noise, allowing for a clearer, more precise detection of a leak s location.

Source record↗

NASA NTRS2014

Using Satellite Imagery to Identify Tornado Damage Tracks and Recovery from the April 27, 2011 Severe Weather Outbreak

Emergency response to natural disasters requires coordination between multiple local, state, and federal agencies. Single, relatively weak tornado events may require comparatively simple response efforts; but larger "outbreak" events with multiple strong, long-track tornadoes can benefit from additional tools to help expedite these efforts. Meteorologists from NOAA's National Weather Service conduct field surveys to map tornado tracks, assess damage, and determine the tornado intensity following each event. Moderate and high resolution satellite imagery can support these surveys by providing a high-level view of the affected areas. Satellite imagery could then be used to target areas for immediate survey or to corroborate the results of the survey after it is completed. In this study, the feasibility of using satellite imagery to identify tornado damage tracks was determined by comparing the characteristics of tracks observed from low-earth orbit to tracks assessed during the official NWS storm survey process. Of the 68 NWS confirmed centerlines, 24 tracks (35.3%) could be distinguished from other surface features using satellite imagery. Within each EF category, 0% of EF-0, 3% of EF-1, 50% of EF-2, 77.7% of EF-3, 87.5% of EF-4 and 100% of EF-5 tornadoes were detected. It was shown that satellite data can be used to identify tornado damage tracks in MODIS and ASTER NDVI imagery, where damage to vegetation creates a sharp drop in values though the minimum EF-category which can be detected is dependent upon the type of sensor used and underlying vegetation. Near-real time data from moderate resolution sensors compare favorably to field surveys after the event and suggest that the data can provide some value in the assessment process.

Cole, Tony A.↗

NASA NTRS2014

Using Satellite Imagery to Identify Tornado Damage Tracks and Recovery from the April 27, 2011 Severe Weather Outbreak

Molthan, Andrew L.↗

NASA NTRS2012

Hierarchthis: An Interactive Interface for Identifying Mission-Relevant Components of the Advanced Multi-Mission Operations System

Even though NASA's space missions are many and varied, there are some tasks that are common to all of them. For example, all spacecraft need to communicate with other entities, and all spacecraft need to know where they are. These tasks use tools and services that can be inherited and reused between missions, reducing systems engineering effort and therefore reducing cost.The Advanced Multi-Mission Operations System, or AMMOS, is a collection of multimission tools and services, whose development and maintenance are funded by NASA. I created HierarchThis, a plugin designed to provide an interactive interface to help customers identify mission-relevant tools and services. HierarchThis automatically creates diagrams of the AMMOS database, and then allows users to show/hide specific details through a graphical interface. Once customers identify tools and services they want for a specific mission, HierarchThis can automatically generate a contract between the Multimission Ground Systems and Services Office, which manages AMMOS, and the customer. The document contains the selected AMMOS components, along with their capabilities and satisfied requirements. HierarchThis reduces the time needed for the process from service selections to having a mission-specific contract from the order of days to the order of minutes.

Advanced Multi-Mission Operations System (AMMOS)↗

NASA NTRS2016

Pilot Critical Incident Reports as a Means to Identify Human Factors of Remotely Piloted Aircraft

It has been estimated that aviation accidents are typically preceded by numerous minor incidents arising from the same causal factors that ultimately produced the accident. Accident databases provide in-depth information on a relatively small number of occurrences, however incident databases have the potential to provide insights into the human factors of Remotely Piloted Aircraft System (RPAS) operations based on a larger volume of less-detailed reports. Currently, there is a lack of incident data dealing with the human factors of unmanned aircraft systems. An exploratory study is being conducted to examine the feasibility of collecting voluntary critical incident reports from RPAS pilots. Twenty-three experienced RPAS pilots volunteered to participate in focus groups in which they described critical incidents from their own experience. Participants were asked to recall (1) incidents that revealed a system flaw, or (2) highlighted a case where the human operator contributed to system resilience or mission success. Participants were asked to only report incidents that could be included in a public document. During each focus group session, a note taker produced a de-identified written record of the incident narratives. At the end of the session, participants reviewed each written incident report, and made edits and corrections as necessary. The incidents were later analyzed to identify contributing factors, with a focus on design issues that either hindered or assisted the pilot during the events. A total of 90 incidents were reported. Human factor issues included the impact of reduced sensory cues, traffic separation in the absence of an out-the-window view, control latencies, vigilance during monotonous and ultra-long endurance flights, control station design considerations, transfer of control between control stations, the management of lost link procedures, and decision-making during emergencies. Pilots participated willingly and enthusiastically in the study, and generally had little difficulty recalling critical incidents. The results suggest that pilot interviews can be a productive method of gathering information on incidents that might not otherwise be reported. Some of the issues described in the reports have received significant attention in the literature, or are analogous to human factors of manned aircraft. In other cases, incident reports involved human factors that are poorly understood, and have not yet been the subject of extensive study. Although many of the reported incidents were related to pilot error, the participants also provided examples of the positive contribution that humans make to the operation of highly-automated systems.

unmanned aircraft systems↗

NASA NTRS2016

A Neural Network Approach for Identifying Particle Pitch Angle Distributions in Van Allen Probes Data

Analysis of particle pitch angle distributions (PADs) has been used as a means to comprehend a multitude of different physical mechanisms that lead to flux variations in the Van Allen belts and also to particle precipitation into the upper atmosphere. In this work we developed a neural network-based data clustering methodology that automatically identifies distinct PAD types in an unsupervised way using particle flux data. One can promptly identify and locate three well-known PAD types in both time and radial distance, namely, 90deg peaked, butterfly, and flattop distributions. In order to illustrate the applicability of our methodology, we used relativistic electron flux data from the whole month of November 2014, acquired from the Relativistic Electron-Proton Telescope instrument on board the Van Allen Probes, but it is emphasized that our approach can also be used with multiplatform spacecraft data. Our PAD classification results are in reasonably good agreement with those obtained by standard statistical fitting algorithms. The proposed methodology has a potential use for Van Allen belt's monitoring.

Souza, V. M.↗

NASA NTRS2017

Stratospheric Instrusion Catalog: A 10-Year Compilation of Events Identified by using TRACK with NASA's MERRA-2 Reanalysis

Stratospheric intrusions "the introduction of ozone-rich stratospheric air into the troposphere" have been linked with surface ozone air quality exceedances, especially at the high elevations in the western USA in springtime. However, the impact of stratospheric intrusions in the remaining seasons and over the rest of the USA is less clear. A new approach to the study of stratospheric intrusions uses NASA's Goddard Earth Observing System Model (GEOS) model and assimilation products with an objective feature tracking algorithm to investigate the atmospheric dynamics that generate stratospheric intrusions and the different mechanisms through which stratospheric intrusions may influence tropospheric chemistry and surface air quality seasonally over both the western and the eastern USA. A catalog of stratospheric intrusions identified in the MERRA-2 reanalysis was produced for the period 2004-2015 and validated against surface ozone observations (focusing on those which exceed the national air quality standard) and a recent data set of stratospheric intrusion-influenced air quality exceedance flags from the US Environmental Protection Agency (EPA). Considering not all ozone exceedances have been flagged by the EPA, a collection of stratospheric intrusions can support air quality agencies for more rapid identification of the impact of stratospheric air on surface ozone and demonstrates that future operational analyses may aid in forecasting such events. An analysis of the spatiotemporal variability of stratospheric intrusions over the continental US was performed, and while the spring over the western USA does exhibit the largest number of stratospheric intrusions affecting the lower troposphere, the number of intrusions in the remaining seasons and over the eastern USA is sizable. By focusing on the major modes of variability that influence weather in the USA, such as the Pacific North American (PNA) teleconnection index, predicative meteorological patterns associated with stratospheric intrusions and their regional effects on tropospheric ozone were identified. Improved understanding of the connections between large-scale climate variability and local-scale dynamically-driven air quality events may support improved seasonal prediction of such events.

PN↗

NASA NTRS2019

Using Chemcam Derived Geochemistry to Identify the Paleonet Sediment Transport Direction and Source Region Characteristics of the Stimson Formation in Gale Crater, Mars

The NASA Curiosity rover has encountered both ancient and modern dune deposits within Gale crater. The modern dunes are actively migrating across the surface within the Bagnold Dune field of which Curiosity conducted analysis campaigns at two different localities. Variations in mafic-felsic mineral abundances between these two sites have been related to the aeolian mineral sorting regime for basaltic environments identified on the Earth which become preferentially enriched in olivine relative to plagioclase feldspar with increasing distance from the source. This aeolian mineral sorting regime for basaltic minerals has also been inferred for Mars from orbital data. The aim of this study is to investigate whether this aeolian mafic-felsic mineral sorting trend has left a geochemical signature in the ancient dune deposits preserved within the Stimson formation. The Stimson formation unconformably overlies the Murray formation and consists of thickly laminated, cross-bedded sandstone. Stimson outcrops have a variable thickness up to 5 meters covering a total area of 17 square kilometers. A dry, aeolian origin was determined for this sandstone due to the high sphericity and roundness of the grains, uniform bimodal grain size distribution (250-710 microns), and 1-meter-thick cross-beds. Identifying the geochemical signature of mineral sorting can provide insights about the paleo-net sediment transport direction of the dunes and prevailing wind direction at the time of deposition.

Bedford, C. C.↗

NASA NTRS2017

Beyond Nanopore Sequencing in Space: Identifying the Unknown

Astronaut Kate Rubins sequenced DNA on the International Space Station (ISS) for the first time in August 2016 (Figure 1A). A 2D sequencing library containing an equal mixture of lambda bacteriophage, Escherichia coli, and Mus musculus was prepared on the ground with a SQK_MAP006 kit and sent to the ISS frozen and loaded into R7.3 flow cells. After a total of 9 on-orbit sequencing runs over 6 months, it was determined that there was no decrease in sequencing performance on-orbit compared to ground controls (1). A total of ~280,000 and ~130,000 reads generated on-orbit and on the ground, respectively, identified 90% of reads that were attributed to 30% lambda bacteriophage, 30% Escherichia coli, and 30% M. musculus (Figure 1B). Extensive bioinformatics analysis determined comparable 2D and 1D read accuracies between flight and ground runs (Figure 1C), and data collected from the ISS were able to construct directed assemblies of E.coli and lambda genomes at 100% and M. musculus mitochondrial genome at 96.7%. These findings validate sequencing as a viable option for potential on-orbit applications such as environmental microbial monitoring and disease diagnosis. Current microbial monitoring of the ISS applies culture-based techniques that provide colony forming unit (CFU) data for air, water, and surface samples. The identity of the cultured microorganisms in unknown until sample return and ground-based analysis, a process that can take up to 60 days. For sequencing to benefit ISS applications, spaceflight-compatible sample preparation techniques are required. Subsequent to the testing of the MinION on-orbit, a sample-to-sequence method was developed using miniPCR™ and basic pipetting, which was only recently proven to be effective in microgravity. The work presented here details the in- flight sample preparation process and the first application of DNA sequencing on the ISS to identify unknown ISS-derived microorganisms.

Stahl, Sarah E.↗

NASA NTRS2020

Philadelphia Health & Air Quality: Assessing Land Surface Temperature, Vegetation Cover, and Compounding Vulnerability Factors to Identify High Priority Areas for Cooling Initiatives in Philadelphia, Pennsylvania

Heat is the leading cause of weather-related deaths in the US, with heat-related hospitalizations increasing by 2-5% between 2001-2010. In Philadelphia alone, 137 heat-related deaths were recorded between 2010-2018, while a total of 18 daily temperature records have been set since 2010. Temperature is relatively higher in cities compared to rural areas, a phenomenon known as the urban heat island effect. This effect exaggerates daytime maximum temperatures and nighttime heat retention in urban areas, which increases heat exposure in urban environments and especially impacts vulnerable populations. Vulnerability to heat-related illnesses is determined by a combination of risk factors, such as demographics, socioeconomic status, and preexisting health conditions. This project supported the Philadelphia Department of Public Health and Office of Sustainability by identifying priority areas for cooling interventions, such as heat danger educational outreach and urban tree planting. The team developed heat vulnerability scores for each census tract within Philadelphia. Remotely sensed land surface temperature, normalized difference vegetation index, normalized difference built-up index, normalized difference water index, and albedo data were calculated from Aqua Moderate Resolution Imaging Spectroradiometer and Landsat 8 Operational Land Imager/Thermal Infrared Sensor instruments. These variables were weighted against socioeconomic variables and preexisting health conditions using a principal component analysis. A total of 74 census tracts clustered were identified as high-risk areas for heat-related illnesses. 15 of these census tracts also had very low tree density (lower 20th percentile) and should be targeted for tree planting initiatives. The findings of this project will help target interventions to mitigate heat-related health issues and improve the overall wellness of Philadelphia residents.

Health & Air Quality↗

NASA NTRS2020

Costa Rica & Panama Ecological Forecasting II: Identifying Current and Future Areas of Environmental Concern in La Amistad International Park to Inform Resource Management

Seven percent of all scientifically known life forms lie within the 202,230 square miles of Central America, making this area ecologically unique and increasing the need for environmental management. The Mesoamerican Biological Corridor forms a conservation partnership throughout Central America to establish a forested corridor of over 600 protected areas. Although conservation programs exist, deforestation still afflicts the area, putting strain on these diverse ecosystems. La Amistad International Park in southern Costa Rica and northern Panama in particular faces conflicting land use changes. Expanding agricultural development and urbanization, combined with concern over indigenous land rights, have raised questions about the implementation of sustainability goals and communication strategies within the region. To help address these issues, the NASA DEVELOP Costa Rica & Panama Ecological Forecasting II team continued a partnership with the Ministry of Environment and Energy in Costa Rica and the National Environmental Authority in Panama. The team created a Land Use Conflict Identification Strategy (LUCIS) model based on land cover maps for 2019 and 2029 that were created in term I using imagery from Landsat 8 Operational Land Imager (OLI). With partner input, the team applied weights to different objectives and combined suitability maps to identify areas of potential biodiversity conflict. Additionally, the team created a Short-term Forest Change (SFTC) Tool using Terra Moderate Resolution Imaging Spectroradiometer, Landsat 8 OLI, and Sentinel-2 Multispectral Instrument to help the partners identify areas of immediate, major forest changes. The LUCIS model indicated higher agricultural growth when compared to the ecological category.

Ecological Forecasting↗

NASA NTRS2020

Costa Rica & Panama Ecological Forecasting II: Identifying Current and Future Areas of Environmental Concern in La Amistad International Park to Inform Resource Management

Ecological Forecasting↗