Search NASA⌕ Search

SEARCH · Search NASA

Results for “pattern detection”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Extreme Lake-Effect Snow from a GPM Microwave Imager Perspective: Observational Analysis and Precipitation Retrieval Evaluation

This study focuses on the ability of the Global Precipitation Measurement (GPM) passive microwave sensors to detect and provide quantitative precipitation estimates (QPE) for extreme lake-effect snowfall events over the United States lower Great Lakes region. GPM Microwave Imager (GMI) high frequency channels can clearly detect intense shallow convective snowfall events. However, GMI Goddard PROfiling (GPROF) QPE retrievals produce inconsistent results when compared against the Multi-Radar/Multi-Sensor (MRMS) ground-based radar reference dataset. While GPROF retrievals adequately capture intense snowfall rates and spatial patterns of one event, GPROF systematically underestimates intense snowfall rates in another event. Furthermore, GPROF produces abundant light snowfall rates that do not conform with MRMS observations. Ad-hoc precipitation rate thresholds are suggested to partially mitigate GPROF’s overproduction of light snowfall rates. The sensitivity and retrieval efficiency of GPROF to key parameters (2-meter temperature, total precipitable water, and background surface type) used to constrain the GPROF a-priori retrieval database are investigated. Results demonstrate that typical lake-effect snow environmental and surface conditions, especially coastal surfaces, are underpopulated in the database and adversely affect GPROF retrievals. For the two presented case studies, using snow cover a-priori database in the locations of originally deemed as coastline improves retrieval. This study suggests that it is particularly important to have more accurate GPROF surface classifications and better representativeness of the a-priori databases to improve intense lake-effect snow detection and retrieval performance.

Lisa Milani↗
DOE OSTI2022

Post-hazard condition assessment of nuclear piping-equipment systems: Novel approach to feature extraction and deep learning

Over the past decade, the use of artificial intelligence techniques in the field of health-monitoring has gained significant interest, especially for structures such as building and bridges. However, applications to industrial systems such as equipment-piping systems in nuclear plants have not been explored. Here, in this paper, it is shown that the existing techniques developed for buildings and bridges cannot be extended directly to equipment-piping systems as the response of such systems is governed by multiple localized modes unlike that in buildings and bridges. This paper proposes a new approach that consists of three key aspects: (i) a novel vector of degradation-sensitive features extracted from measured data, (ii) using a deep Artificial Neural Network (ANN) for diagnosis of degradation location and degradation severity, and (iii) consideration of uncertainty in degradation severity when training the ANN. Degradation in piping-equipment systems can occur due to flow-accelerated erosion and corrosion. These locations can potentially exhibit damage such as localized yielding or initiation of cracking due to an external event such as an earthquake. Moreover, such locations can at times go undetected by current inspection techniques. Therefore, a robust framework is needed for detection of degradation after a seismic event. This manuscript proposes a proof-of-concept framework, which utilizes data collected from sensors to generate a deep ANN database for predicting degraded locations and severity in a piping-equipment system. Degradation severity is classified as minor, moderate, and severe. In the suggested methodology, a novel vector of degradation-sensitive features is extracted from the sensor data to train the ANN. A simple piping-equipment system is selected to demonstrate feature extraction as a means to simplify pattern recognition, explore the design and parameters of an ANN, and develop a sensor placement strategy. The effectiveness of the proposed framework is demonstrated on a realistic primary safety system of a two-loop nuclear reactor. It is shown that the proposed post-hazard condition assessment framework is able to detect degraded locations along with the severity levels, including minor degradation, with considerably higher accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1989

Contrasting landform perception with varied radar illumination geometries and at simulated resolutions of Venera and Magellan

The high sensitivity of imaging radars to slope at moderate to low incidence angles enhances the perception of linear topography on images. It reveals broad spatial patterns that are essential to landform mapping and interpretation. As radar responses are strongly directional, the ability to discriminate linear features on images varies with their orientation. Landforms that appear prominent on images where they are transverse to the illumination may be obscure to indistinguishable on images where they are parallel to it. Landform detection is also influenced by the spatial resolution in radar images. Seasat radar images of the Gran Desierto Dunes complex, Sonora, Mexico; the Appalachian Valley and Ridge Province; and accreted terranes in eastern interior Alaska were processed to simulate both Venera 15 and 16 images (1000 to 3000 km resolution) and image data expected from the Magellan mission (120 to 300 m resolution. The Gran Desierto Dunes are not discernable in the Venera simulation, whereas the higher resolution Magellan simulation shows dominant dune patterns produced from differential erosion of the rocks. The Magellan simulation also shows that fluvial processes have dominated erosion and exposure of the folds.

Ford, J. P.↗
DOE OSTI2016

SU-G-BRB-07: Developing a QA Procedure for Gated VMAT SABR Treatments Using 10 MV Beam in Flattening-Filter Free Mode

Purpose: To develop a QA procedure for gated VMAT stereotactic ablative radiotherapy (SABR) treatments. Methods: An interface was constructed to attach the translational stage of a Quasar respiratory motion phantom to a pinpoint ion chamber insert and move the ion chamber inside an ArcCheck diode array. The Quasar phantom controller used a patient specific breathing pattern to translate the ion chamber in a superior-inferior direction inside the ArcCheck. An amplitude-based RPM tracking system was specified to turn the beam on during the exhale phase of the breathing pattern. SABR plans were developed using Eclipse for liver PTVs ranging in size from 3-12 cm in diameter using a 2-arc VMAT technique. Dose was measured in the middle of the penumbra region, where the high dose gradient allowed for sensitive detection of any inaccuracies in gated dose delivery. The overall fidelity of the dose distribution was confirmed using ArcCheck. The sensitivity of the gating QA procedure was investigated with respect to the following four parameters: PTV size, duration of exhale, baseline drift, and gating window size. Results: The difference between the measured dose to a point in the penumbra and the Eclipse calculated dose was under 2% for small residual motions. The QA procedure was independent of PTV size and duration of exhale. Baseline drift and gating window size, however, significantly affected the penumbral dose measurement, with differences of up to 30% compared to Eclipse. Conclusion: This study described a highly sensitive QA procedure for gated VMAT SABR treatments. The QA outcome was dependent on the gating window size and baseline drift. Analysis of additional patient breathing patterns will be required to determine a clinically relevant gating window size and an appropriate tolerance level for this procedure.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Primary and post-chemoradiotherapy staging using MRI in rectal cancer: the role of diffusion imaging in the assessment of perirectal infiltration

Purpose: To analyze changes in MRI diagnostic accuracy in main rectal tumor (T) evaluation resulting from the use of diffusion-weighted imaging (DWI), according to the degree of experience of the radiologist. Methods: This is a cross-sectional study of a database including one hundred 1.5 T MRI records (2011–2016) from patients with biopsy-proven rectal cancer, including primary staging and post-chemoradiotherapy follow-up. All cases were individually blindedly reviewed by ten radiologists: three experienced in rectal cancer, three specialized in other areas, and four residents. Each case was assessed twice to detect perirectal infiltration: first, evaluating just high-resolution T2-weighted sequences (HRT2w); second, evaluation of DWI plus HRT2w sequences. Results were pooled by experience, calculating accuracy (area under ROC curve), sensitivity and specificity, predictive values, likelihood ratios, and overstaging/understaging. Histology of surgical specimens provided the reference standard. Results: DWI significantly improved specificity by experienced radiologists in primary staging (63.2% to 75.9%) and, to a lesser extent, positive likelihood ratio (2.06 to 2.87); minimal changes were observed post-chemoradiotherapy, with a slight decrease of accuracy (0.657 to 0.626). Inexperienced radiologists showed a similar pattern, but with slight enhancement post-chemoradiotherapy (accuracy 0.604 to 0.621). Residents experienced small changes, with increased sensitivity/decreased specificity in both primary (69% to 72%/67.2% to 64.7%) and post-chemoradiotherapy (68.1% to 73.6%/47.3% to 44.6%) staging. Conclusions: Adding DWI to HRT2w significantly improved specificity for the detection of perirectal infiltration at primary staging by experienced radiologists and also by inexperienced ones, although to a lesser extent. In the post-neoadjuvant treatment subgroup, only minimal changes were observed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Deep-Learning-Enabled Crack Detection and Analysis in Commercial Lithium-Ion Battery Cathodes

We report in Li-ion batteries, the mechanical degradation initiated by micro cracks is one of the bottlenecks for enhancing the performance. Quantifying the crack formation and evolution in complex composite electrodes can provide important insights into electrochemical behaviors under prolonged and/or aggressive cycling. However, observation and interpretation of the complicated crack patterns in battery electrodes through imaging experiments are often time-consuming, labor intensive, and subjective. Herein, a deep learning-based approach is developed to extract the crack patterns from nanoscale hard X-ray holo-tomography data of a commercial 18650-type battery cathode. Efficient and effective quantification of the damage heterogeneity with automation and statistical significance is demonstrated. The crack characteristics are further associated with the active particles’ packing densities and a potentially viable architectural design is discussed for suppressing the structural degradation in an industry-relevant battery configuration.

25 ENERGY STORAGE↗
NASA NTRS1973

Automated thematic mapping and change detection of ERTS-1 images, part A

The author has identified the following significant results. Automatic and accurate image processing techniques are essential to full utilization of ERTS-1 photography. In pursuit of this, terrain types in the ERTS-1 photography will be classified by spatial signatures. Diffraction patterns from selected ERTS-1 images have been developed optically and are being analyzed to identify unique signatures for various terrain types. Spatial signatures have been definitely identified for cultivated land and certain urban areas. A Fourier plane mask has been developed that greatly facilitates the analysis of the diffraction patterns.

Gramenopoulos, N.↗
NASA NTRS1987

Automated detection of severe thunderstorms using geosynchronous infrared data

A procedure to identify thunderstorms from short-interval (5 min) GOES infrared (IR) data and to estimate their intensity (updraft strength) in an automated fashion is described. Thunderstorms are identified in the IR field by a simple pattern-recognition approach. For mature thunderstorms, two key parameters are used to estimate intensity: the amount of penetration above the neutral point and the occurrence (or not) of a cold-warm couplet in the IR TB field. Based on cloud model results, the amount of penetration is related to the maximum updraft speed, which is converted to an index. Application of the algorithm to a case study is presented.

Adler, Robert F.↗
NASA NTRS1992

Polarization signatures for abandoned agricultural fields in the Manix Basin area of the Mojave Desert - Can polarimetric SAR detect desertification?

Radar backscatter from abandoned circular alfalfa fields in the Manix Basin area of the Mojave desert shows systematic changes with length of abandonment. The obliteration of circular planting rows by surface processes could account for the disappearance of bright spokes, which seem to be reflection patterns from remnants of the planting rows, with increasing length of abandonment. An observed shift in the location of the maximum L-band copolarization return away from VV, as well as an increase in surface roughness, both occurring with increasing age of abandonment, seems to be attributable to the formation of wind ripples on the relatively vegetationless fields.

Ray, Terrill W.↗
DOE OSTI2018

Utilizing Geo-located Sensors and Social Media for Studying Population Dynamics and Land Classification

The ability to understand where, when, and why humans move across space and time has always been essential to research areas such as urban planning, transportation, population dynamics, and emergency preparedness and response. The increasing sources of activity data is generating novel opportunities to understand human dynamics that previously was not possible; Geo-located user generated content from mobile devices and sensors allow a level of spatial and temporal granularity that could possibly answer the reasons for human movement at a high-resolution. This work discusses a broad array of research agenda in human dynamics and land use by proposing an explicit model that assists in delineating and articulating the opportunities, challenges, and limitations of using new forms of unauthoritated data, such as social media in main-stream GIS research. We study mobile phone call volume and GPS locations to characterize human activity patterns and provide inference on land use. Later, we demonstrate the ability of geo-located social media posts to provide insight on population density estimates for special events and Points of Interest detection. The chapter underpins the need to utilize new forms of data collection mechanism as well as their use to augment our understanding of human dynamics research and future application of geographical information systems.

Thakur, Gautam Malviya↗
DOE OSTI2022

Earlier emergence of a temperature response to mitigation by filtering annual variability

The rate of global surface warming is crucial for tracking progress towards global climate targets, but is strongly influenced by interannual-to-decadal variability, which precludes rapid detection of the temperature response to emission mitigation. Here we use a physics based Green’s function approach to filter out modulations to global mean surface temperature from sea-surface temperature (SST) patterns, and show that it results in an earlier emergence of a response to strong emissions mitigation. For observed temperatures, we find a filtered 2011–2020 surface warming rate of 0.24 °C per decade, consistent with long-term trends. Unfiltered observations show 0.35 °C per decade, partly due to the El Nino of 2015–2016. Pattern filtered warming rates can become a strong tool for the climate community to inform policy makers and stakeholder communities about the ongoing and expected climate responses to emission reductions, provided an effort is made to improve and validate standardized Green’s functions.

58 GEOSCIENCES↗
DOE OSTI2015

Evolution of laser induced electromagnetic postsolitons in multi-species plasma

The evolution of an s-polarized relativistic electromagnetic soliton created in multi-species plasma by an intense short laser pulse is investigated using two-dimensional particle-in-cell simulations. The multi-component plasma consists of electrons and high-Z ions with a small addition of protons. By comparison, the evolution of postsoliton is very different from that in hydrogen plasma. A halo-like structure is found in spatial patterns of both electromagnetic fields and electron densities. The process of energy depletion is much slower due to the smaller charge-to-mass ratio of ions, which implies a better way of detecting postsolitons in simulations and experiments. In addition, it is found that the Coulomb explosion of high-Z ions in the postsoliton stage facilitates low-Z ion acceleration, and the maximum energy of low-Z ions increases with the component ratio of high-Z to low-Z ions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Simultaneous ambient pressure x-ray photoelectron spectroscopy and grazing incidence x-ray scattering in gas environments

We have developed an experimental system to simultaneously measure surface structure, morphology, composition, chemical state, and chemical activity for samples in gas phase environments. This is accomplished by simultaneously measuring x-ray photoelectron spectroscopy (XPS) and grazing incidence x-ray scattering in gas pressures as high as the multi-Torr regime while also recording mass spectrometry. Scattering patterns reflect near-surface sample structures from the nano-scale to the meso-scale, and the grazing incidence geometry provides tunable depth sensitivity of structural measurements. Scattered x rays are detected across a broad range of angles using a newly designed pivoting-UHV-manipulator for detector positioning. At the same time, XPS and mass spectrometry can be measured, all from the same sample spot and under ambient conditions. To demonstrate the capabilities of this system, we measured the chemical state, composition, and structure of Ag-behenate on a Si(001) wafer in vacuum and in O 2 atmosphere at various temperatures. These simultaneous structural, chemical, and gas phase product probes enable detailed insights into the interplay between the structure and chemical state for samples in gas phase environments. The compact size of our pivoting-UHV-manipulator makes it possible to retrofit this technique into existing spectroscopic instruments installed at synchrotron beamlines. Because many synchrotron facilities are planning or undergoing upgrades to diffraction limited storage rings with transversely coherent beams, a newly emerging set of coherent x-ray scattering experiments can greatly benefit from the concepts we present here.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

A clinically observed discrepancy between image-based and log-based MLC positions

Purpose: To present a clinical case in which real-time intratreatment imaging identified an multileaf collimator (MLC) leaf to be consistently deviating from its programmed and logged position by >1 mm. Methods: An EPID-based exit-fluence dosimetry system designed to prevent gross delivery errors was used to capture cine during treatment images. The author serendipitously visually identified a suspected MLC leaf displacement that was not otherwise detected. The leaf position as recorded on the EPID images was measured and log-files were analyzed for the treatment in question, the prior day’s treatment, and for daily MLC test patterns acquired on those treatment days. Additional standard test patterns were used to quantify the leaf position. Results: Whereas the log-file reported no difference between planned and recorded positions, image-based measurements showed the leaf to be 1.3 ± 0.1 mm medial from the planned position. This offset was confirmed with the test pattern irradiations. Conclusions: It has been clinically observed that log-file derived leaf positions can differ from their actual position by >1 mm, and therefore cannot be considered to be the actual leaf positions. This cautions the use of log-based methods for MLC or patient quality assurance without independent confirmation of log integrity. Frequent verification of MLC positions through independent means is a necessary precondition to trust log-file records. Intratreatment EPID imaging provides a method to capture departures from MLC planned positions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

RNAi-Mediated Manipulation of Cuticle Coloration Genes in Lygus hesperus Knight (Hemiptera: Miridae)

Cuticle coloration in insects is a consequence of the accumulation of pigments in a species-specific pattern. Numerous genes are involved in regulating the underlying processes of melanization and sclerotization, and their manipulation can be used to create externally visible markers of successful gene editing. To clarify the roles for many of these genes and examine their suitability as phenotypic markers in Lygus hesperus Knight (western tarnished plant bug), transcriptomic data were screened for sequences exhibiting homology with the Drosophila melanogaster proteins. Complete open reading frames encoding putative homologs for six genes (aaNAT, black, ebony, pale, tan, and yellow) were identified, with two variants for black. Sequence and phylogenetic analyses supported preliminary annotations as cuticle pigmentation genes. In accord with observable difference in color patterning, expression varied for each gene by developmental stage, adult age, body part, and sex. Knockdown by injection of dsRNA for each gene produced varied effects in adults, ranging from the non-detectable (black 1, yellow), to moderate decreases (pale, tan) and increases (black 2, ebony) in darkness, to extreme melanization (aaNAT). Based solely on its expression profile and highly visible phenotype, aaNAT appears to be the best marker for tracking transgenic L. hesperus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Chemical composition of ultrafine aerosol particles in central Amazonia during the wet season

Central Amazonia serves as an ideal location to study atmospheric particle formation, since it often represents nearly natural, pre-industrial conditions but can also experience periods of anthropogenic influence due to the presence of emissions from large metropolitan areas like Manaus, Brazil. Ultrafine (sub-100 nm diameter) particles are often observed in this region, although new particle formation events seldom occur near the ground despite being readily observed in other forested regions with similar emissions of volatile organic compounds (VOCs). This study focuses on identifying the chemical composition of ultrafine particles as a means of determining the chemical species and mechanisms that may be responsible for new particle formation and growth in the region. These measurements were performed during the wet season as part of the Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) field campaign at a site located 70 km southwest of Manaus. A thermal desorption chemicalionization mass spectrometer (TDCIMS) characterized the most abundant compounds detected in ultrafine particles. Two time periods representing distinct influences on aerosol composition, which we label as “anthropogenic” and “background” periods, were studied as part of a larger 10 d period of analysis. Higher particle number concentrations were measured during the anthropogenic period, and modeled back-trajectory frequencies indicate transport of emissions from the Manaus metropolitan area. During the background period there were much lower number concentrations, and back-trajectory frequencies showed that air masses arrived at the site predominantly from the forested regions to the north and northeast. TDCIMS-measured constituents also show distinct differences between the two observational periods. Although bisulfate was detected in particles throughout the 10 d period, the anthropogenic period had higher levels of particulate bisulfate overall. Ammonium and trimethyl ammonium were positively correlated with bisulfate. The background period had distinct diurnal patterns of particulate cyanate and acetate, while oxalate remained relatively constant during the 10 d period. 3-Methylfuran, a thermal decomposition product of a particulate-phase isoprene epoxy diol(IEPOX), was the dominant species measured in the positive-ion mode. Principal component analysis (PCA) was performed on the TDCIMS-measured ion abundance and aerosol mass spectrometer (AMS) mass concentration data. Two different hierarchical clusters representing unique influences arise: one comprising ultrafine particulate acetate, hydrogen oxalate, cyanate, trimethyl ammonium and 3-methylfuran and another made up of ultra fine particulate bisulfate, chloride, ammonium and potassium. A third cluster separated AMS-measured species from the two TDCIMS-derived clusters, indicating different sources or processes in ultrafine aerosol particle formation compared to larger submicron-sized particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1977

Measurements of the frequency spectrum of transition radiation

We report a measurement of the frequency spectrum of X-ray transition radiation. X rays were generated by electrons of 5 and 9 GeV in radiators of multiple polypropylene foils, and detected in the range 4 to 30 keV with a calibrated single-crystal Bragg spectrometer. The experimental results closely reproduce the features of the theoretically predicted spectrum. In particular, the pronounced interference pattern of multifoil radiators and the expected hardening of the radiation with increasing foil thickness are clearly observed. The overall intensity of the radiation is somewhat lower than predicted by calculations.

Cherry, M. L.↗