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At least 721 records · Page 40

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NASA NTRS2006

Shearography NDE of NASA COPV

1. 21 Composite Over-wrapped Pressure Vessels (COPV) consisting of Kevlar Space Shuttle Fleet Leaders and Graphite COPV were inspected at NASA WSTF, NM from Sept. 12 through Sept 16. 2. The inspection technique was Pressurization Shearography, tests designed to image composite material damage, degradation or design flaws leading to stress concentrations in the axial or hoop strain load path. 3. The defect types detected consisted of the following: a) Intentional impact damage with known energy. b) Un-intentional impact damage. c) Manufacturing defects. 4. COPV design features leading to strain concentrations detected include: a) Strain concentrations at bosses due to fiber closure pattern. b) Strain concentrations in body of COPV due to fiber wrap pattern. c) Strain concentrations at equator due to liner weld/fiber lay-up.

Newman, John W.↗

NASA NTRS2015

The CheMin XRD on the Mars Science Laboratory Rover Curiosity: Construction, Operation, and Quantitative Mineralogical Results from the Surface of Mars

The Mars Science Laboratory mission was launched from Cape Canaveral, Florida on Nov. 26, 2011 and landed in Gale crater, Mars on Aug. 6, 2012. MSL's mission is to identify and characterize ancient "habitable" environments on Mars. MSL's precision landing system placed the Curiosity rover within 2 km of the center of its 20 X 6 km landing ellipse, next to Gale's central mound, a 5,000 meter high pile of laminated sediment which may contain 1 billion years of Mars history. Curiosity carries with it a full suite of analytical instruments, including the CheMin X-ray diffractometer, the first XRD flown in space. CheMin is essentially a transmission X-ray pinhole camera. A fine-focus Co source and collimator transmits a 50μm beam through a powdered sample held between X-ray transparent plastic windows. The sample holder is shaken by a piezoelectric actuator such that the powder flows like a liquid, each grain passing in random orientation through the beam over time. Forward-diffracted and fluoresced X-ray photons from the sample are detected by an X-ray sensitive Charge Coupled Device (CCD) operated in single photon counting mode. When operated in this way, both the x,y position and the energy of each photon are detected. The resulting energy-selected Co Kalpha Debye-Scherrer pattern is used to determine the identities and amounts of minerals present via Rietveld refinement, and a histogram of all X-ray events constitutes an X-ray fluorescence analysis of the sample.The key role that definitive mineralogy plays in understanding the Martian surface is a consequence of the fact that minerals are thermodynamic phases, having known and specific ranges of temperature, pressure and composition within which they are stable. More than simple compositional analysis, definitive mineralogical analysis can provide information about pressure/temperature conditions of formation, past climate, water activity and the like. Definitive mineralogical analyses are necessary to establish the origin or provenance of a sample. The search for evidence of extant or extinct life on Mars will initially be a search for evidence of present or past conditions supportive of life (e.g., evidence of water), not for life itself.Results of the first 1,000 sols (Mars days) will be discussed, including the discovery of the first habitable environment on Mars.

CheMin↗

NASA NTRSDate not supplied

Mineralogical, Elemental and Tomographic Reconnaissance Investigation for CLPS (“METRIC”)

METRIC comprises a suite of two instruments in a Lunar lander that perform X-ray diffraction (XRD) for mineral structure, X-ray fluorescence (XRF) for elemental composition, and X-ray Micro Computed Tomography (XCT) for 3D internal micromorphology. The instruments are accompanied by optical-near IR cameras to provide local geologic context. The Honeybee Robotics PlanetVac pneumatic sampling and transfer system [1],positioned on a lander footpad, will deliver sieved regolith to the X-ray instruments for analysis. The instrument suite is intended for delivery to the lunar surface on a Commercial Lunar Payload Services (CLPS) lander. The METRICXRD/F instrument draws on heritage from the Mars Science Laboratory CheMin instrument [2] and improves upon the design in multiple ways [3]. Like CheMin, Rietveld refinement and full-pattern fitting of METRIC XRD data can identify minerals at a detection limit of ~1 wt.%, quantify their abundances when present at >3 wt.%, and determine mineral composition (e.g., Fo#in olivine) from lattice parameters for minerals present at >5 wt.%[4,5]. An optimized XRF geometry provides for improved detection and quantification of major, minor and trace elements. The METRIC XCT instrument is a miniaturized X-ray Computed Tomography scanner[6]. Lunar regolith is delivered to a 3 mm diameter, 10 mm long graphite tube inside the instrument. The tube is rotated through 360°in 0.9deg.incrementsand a divergent point source X-ray beam is directed through the material. A Charge Coupled Device (CCD)records attenuation images whose brightness and contrast area function of average atomic number and density. Quantitative data, including particle and void sizes, 3D particle shape parameters, modal volumes and pore geometry can be derived from the resulting 3D reconstructions(voxel resolution: 30 μm). Crystal morphologies derived from METRIC XCT data complement the bulk mineralogy determined by the METRIC XRD/F and provide a measure of grain size distribution for the different phases. Taken together, the METRIC instrument suite determines crystal structure, elemental composition and morphology, three principal characteristics of geological materials that are highly useful in determining the origin and subsequent processing of lunar regolith.

Moon↗

DOE OSTI2020

Ubiquitous Traffic Volume Estimation through Machine-Learning Procedure

Traffic volume data is one of the most important metrics for accurate assessment of the performance of a transportation system. Quality volume data is required to effectively assess extent of delay and congestion, detect real-time perturbations to the network, and understand traffic patterns during major weather events. Traffic volume on freeways are typically collected through continuous count stations installed by state DOTs, while there is lack of traffic volume observability on off-freeway roads. The National Renewable Energy Laboratory (NREL), in Collaboration with the I-95 Corridor Coalition and the University of Maryland, extended its research into estimating volumes anywhere anytime from industry probe based data for off-freeway roads. NREL combined vehicle probe count data with several other data sets (speed, whether, roadway geometry, time-of-day, day-of-week, etc.) to estimate hourly volumes as well as AADTs. The research validated and demonstrated the machine learning model, namely XGBoost, using data collected from Pennsylvania, North Carolina, and Tennessee.

47 OTHER INSTRUMENTATION↗

NASA NTRS1981

Dynamic Moire Methods for Detection of Loosened Space Shuttle Tiles

Moire fringe methods for detecting loose space shuttle tiles were investigated with a test panel consisting of a loose tile surrounded by four securely bonded tiles. The test panel was excited from 20 to 150 Hz with in-plane sinusoidal acceleration of 2 g (peak). If the shuttle orbiter can be subjected to periodic excitation of 1 to 2 g (peak) and rigid-body periodic displacements do not mask the change in the Moire pattern due to tile looseness, then the use of projected Moire fringes to detect out-of-plane rockin appears to be the most viable indicator of tile looseness since no modifications to the tiles are required.

Snow, W. L.↗

NASA NTRS1996

The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation composition was noted in the change detection image.

Hogan, Christine A.↗

DOE OSTI2021

Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

Abstract While various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Heliostat optical error inspection with polarimetric imaging drone

On a Concentrated Solar Power (CSP) field, optical errors have significant impacts on the collection efficiency of heliostats. Fast, cost-effective, labor-efficient, and non-intrusive autonomous field inspection remains a challenge. Approaches using imaging drone, i.e., Unmanned Aerial Vehicle (UAV) system integrated with high resolution visible imaging sensors, have been developed to address these challenges; however, these approaches are often limited by insufficient imaging contrast. Here, in this study, we report a polarimetry-based method with a polarization imaging system integrated on UAV to enhance imaging contrast for in-situ detection of heliostat mirrors without interrupting field operation. We developed an optical model for skylight polarization pattern to simulate the polarization images of heliostat mirrors and obtained optimized waypoints for polarimetric imaging drone flight path to capture images with enhanced contrast. The polarimetric imaging-based method improved the success rate of edge detections in scenarios which were challenging for mirror edge detection with conventional imaging sensors. We have performed field tests to achieve significantly enhanced heliostat edge detection success rate and investigate the feasibility of integrating polarimetric imaging method with existing imaging-based heliostat inspection methods, i.e., Polarimetric Imaging Heliostat Inspection Method (PIHIM). Our preliminary field test results suggest that the PIHIM hold the promise to enable sufficient imaging contrast for real-time autonomous imaging and detection of heliostat field, thus suitable for non-interruptive fast CSP field inspection during its operation.

CSP Field↗

DOE OSTI2017

Boost breaking in the EFT of inflation

If time-translations are spontaneously broken, so are boosts. This symmetry breaking pattern can be non-linearly realized by either just the Goldstone boson of time translations, or by four Goldstone bosons associated with time translations and boosts. Here in this paper we extend the Effective Field Theory of Multifield Inflation to consider the case in which the additional Goldstone bosons associated with boosts are light and coupled to the Goldstone boson of time translations. The symmetry breaking pattern forces a coupling to curvature so that the mass of the additional Goldstone bosons is predicted to be equal to √2H in the vast majority of the parameter space where they are light. This pattern therefore offers a natural way of generating self-interacting particles with Hubble mass during inflation. After constructing the general effective Lagrangian, we study how these particles mix and interact with the curvature fluctuations, generating potentially detectable non-Gaussian signals.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

ObstacleSense: Low-Power Neuromorphic Vision for Corridor Obstacle Awareness in Low-Level ADAS

The automotive industry’s pursuit of Level 5 autonomy is constrained by substantial perception-compute power requirements, often reaching 1, 000 + watts in full autonomy stacks. Reducing this energy burden requires rethinking perception not only at the high-end autonomy level, but also at the foundational Advanced Driver Assistance Systems (ADAS) level where low-power, safety-critical sensing can have broad impact. Neuromorphic vision provides a promising starting point: HD Dynamic Vision Sensors (DVS) can operate below 100 mW at the sensor level by reporting only asynchronous brightness changes. However, low-power sensing alone is insufficient if downstream perception reintroduces dense, energy-intensive computation. In particular, many event-driven object-detection pipelines still rely on CNN backbones, while purely spiking alternatives often trade away accuracy or ignore deployment constraints. We introduce ObstacleSense, a highly compact, CNN-free hybrid ANN–SNN framework for Level 0–1 forward-corridor obstacle awareness. Instead of performing full-scene object detection with a convolutional feature backbone, ObstacleSense targets the safety-critical question of whether the ego corridor is occupied and how far the nearest obstacle is. The architecture combines polarity-conditioned event encoding, lightweight temporal spiking dynamics, axial spatial mixing, and coarse-to-fine range estimation within a regular fixed-grid compute pattern. This design avoids the dense CNN backbone commonly used in event-based detection while maintaining a small state footprint suitable for eventual small-FPGA deployment. Before hardware mapping, we evaluate the software implementation using a model-side power proxy derived from MACs, weight and activation traffic, and spiking state updates under shared FP16 assumptions. On simulated CARLA event corpora, the deployment-oriented model achieves 0.9464 objectness F1, 0.9978 grid-level mAP, and 0.8987 m distance Mean Absolute Error at an estimated 1.92 mW proxy cost, while maintaining performance on unseen generalization test sequences.

Johnson-Scott, Zac [ORNL]↗

DOE OSTI2017

Twenty-First-Century Changes in U.S. Regional Heavy Precipitation Frequency Based on Resolved Atmospheric Patterns

Precipitation-gauge observations and atmospheric reanalysis are combined to develop an analogue method for detecting heavy precipitation events based on prevailing large-scale atmospheric conditions. Combinations of atmospheric variables for circulation (geopotential height and wind vector) and moisture (surface specific humidity, column and up to 500-hPa precipitable water) are examined to construct analogue schemes for the winter [December–February (DJF)] of the “Pacific Coast California” (PCCA) region and the summer [June–August (JJA)] of the Midwestern United States (MWST). The detection diagnostics of analogue schemes are calibrated with 1979–2005 and validated with 2006–14 NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA). All analogue schemes are found to significantly improve upon MERRA precipitation in characterizing the occurrence and interannual variations of observed heavy precipitation events in the MWST. When evaluated with the late twentieth-century climate model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5), all analogue schemes produce model medians of heavy precipitation frequency that are more consistent with observations and have smaller intermodel discrepancies than model-based precipitation. Under the representative concentration pathways (RCP) 4.5 and 8.5 scenarios, the CMIP5-based analogue schemes produce trends in heavy precipitation occurrence through the twenty-first century that are consistent with model-based precipitation, but with smaller intermodel disparity. The median trends in heavy precipitation frequency are positive for DJF over PCCA but are slightly negative for JJA over MWST. Overall, the analyses highlight the potential of the analogue as a powerful diagnostic tool for model deficiencies and its complementarity to an evaluation of heavy precipitation frequency based on model precipitation alone.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Performance Validation of Pulsed Thermal Imaging System for In-Service Applications

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which has the capability of melting metallic powder and net shaping the structures with relatively high precision. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermography Imaging (PTI) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTI method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTI method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTI system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTI capabilities in detecting microscopic defects in metallic specimens. SS316 and IN718 specimens were developed with a pattern of subsurface calibrated flat bottom hole (FBH) defects with diameters from 500µm to 200µm. FBH’s were created with EDM (electron discharge machining) drill. PTI imaging data was processed Spatial Temporal Denoised Thermal Source Separation (STDTSS) unsupervised machine learning (ML) algorithm. We show that defects as small as 200µm in SS316 and IN718 can be detected with STDTSS algorithm. To the best of our knowledge, these are the smallest detected defects which are reported in literature.

42 ENGINEERING↗

DOE OSTI2022

A Methodological Overview of Seismic Analysis for Nuclear Event Detection

Underground explosions generate potentially detectable signatures, including energy waves that travel through the Earth’s subsurface (i.e., seismic waves), low-frequency sound waves (i.e., infrasound and hydroacoustic waves), and radioactive gases and/or particles that might leak from the test cavity (if the event was nuclear). There can also be intelligence indicators of a test, such as observations of modified patterns of life and activity at a suspected test site. If all of these detectable signatures and intelligence indicators are present and self-consistent, then analysts have high confidence in classifying a signature generating event as an explosion. However, because only partial information about an event is likely to be available, determining whether an event was natural (e.g., an earthquake or landslide) or manmade (e.g., a chemical or nuclear explosion) is much more challenging. This primer describes how one category of event signatures—seismic signatures—can augment event analyses. While universities and government organizations have generated detailed technical descriptions of seismic analytic techniques, we seek to translate seismic event analysis for a broad, non-technical audience. When the geologic conditions near an event are well-characterized, seismic data can be used to calculate critical information, such as event location and depth, with relatively high accuracy. Moreover, specific features within seismic datasets can help determine whether an event was an explosion. However, a key challenge in seismic analysis is that geologic site conditions are often poorly characterized, complicating the ability to discern the true nature of the event. To overcome this challenge, geologists answer a series of questions (discussed in section 1) to guide seismic event analysis and determine the most probable nature of an event. As more information is gathered during each analytic step, confidence grows regarding the nature of the event. Section 2 addresses uncertainties in seismic analysis and the vital nature of high-fidelity geologic data for accurate seismic event analysis.

58 GEOSCIENCES↗

DOE OSTI2017

Diversity of Abundance Patterns of Light Neutron-capture Elements in Very-metal-poor Stars

We determine the abundances of neutron-capture elements from Sr to Eu for five very-metal-poor stars (−3 < [Fe/H] < −2) in the Milky Way halo to reveal the origin of light neutron-capture elements. Previous spectroscopic studies have shown evidence of at least two components in the r-process; one referred to as the “main r-process” and the other as the “weak r-process,” which is mainly responsible for producing heavy and light neutron-capture elements, respectively. Observational studies of metal-poor stars suggest that there is a universal pattern in the main r-process, similar to the abundance pattern of the r-process component of solar-system material. Still, it is uncertain whether the abundance pattern of the weak r-process shows universality or diversity, due to the sparseness of measured light neutron-capture elements. We have detected the key elements, Mo, Ru, and Pd, in five target stars to give an answer to this question. The abundance patterns of light neutron-capture elements from Sr to Pd suggest a diversity in the weak r-process. In particular, scatter in the abundance ratio between Ru and Pd is significant when the abundance patterns are normalized at Zr. Our results are compared with the elemental abundances predicted by nucleosynthesis models of supernovae with parameters such as electron fraction or proto-neutron-star mass, to investigate sources of such diversity in the abundance patterns of light neutron-capture elements. This paper presents that the variation in the abundances of observed stars can be explained with a small range of parameters, which can serve as constraints on future modeling of supernova models.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1974

Automated thematic mapping and change detection of ERTS-A images

The author has identified the following significant results. A diffraction pattern analysis of MSS images led to the development of spatial signatures for farm land, urban areas and mountains. Four spatial features are employed to describe the spatial characteristics of image cells in the digital data. Three spectral features are combined with the spatial features to form a seven dimensional vector describing each cell. Then, the classification of the feature vectors is accomplished by using the maximum likelihood criterion. It was determined that the recognition accuracy with the maximum likelihood criterion depends on the statistics of the feature vectors. It was also determined that for a given geographic area the statistics of the classes remain invariable for a period of a month, but vary substantially between seasons. Three ERTS-1 images from the Phoenix, Arizona area were processed, and recognition rates between 85% and 100% were obtained for the terrain classes of desert, farms, mountains, and urban areas. To eliminate the need for training data, a new clustering algorithm has been developed. Seven ERTS-1 images from four test sites have been processed through the clustering algorithm, and high recognition rates have been achieved for all terrain classes.

Gramenopoulos, N.↗

DOE OSTI2020

Spatiotemporal Pattern Recognition in the PMU Signals in the WECC system

Phasor measurement unit (PMU) data has been used by multiple power system applications, including state estimation, post event analysis, oscillation detection, model validation, and many others. Still, due to its big data nature and availability to general research institutions, comprehensive understanding of the spatiotemporal patterns and underlying mechanisms are incomplete. This study applies a set of signal processing and machine learning approaches aiming at deciphering the characteristic behaviors of multiple phasor measurement units (PMUs) attributes (e.g., voltage, frequency, rate of change of frequency, phase angle), including their auto-correlation, cross-dependence, similarities and discrepancies across units and temporal scales, and distributions of anomalies and their linkages to potential external factors such as weather events. Data analytics are applied to PMUs from the U.S. Western Electricity Coordinating Council (WECC) system. The PMU measurements, recorded events, outages, and weather extremes are all from real world datasets. The findings from the study and mechanistic understanding of the PMU dynamics help provide guidance on system control or preventing blackouts. The derived metrics can be directly used for adjusting or filtering simulated PMU data used for advanced algorithm development.

Hou, Zhangshuan↗

NASA NTRS2011

Wireless tamper detection sensor and sensing system

A wireless tamper detection sensor is defined by a perforated electrical conductor. The conductor is shaped to form a geometric pattern between first and second ends thereof such that the conductor defines an open-circuit that can store and transfer electrical and magnetic energy. The conductor resonates in the presence of a time-varying magnetic field to generate a harmonic response. The harmonic response changes when the conductor experiences a change in its geometric pattern due to severing of the conductor along at least a portion of the perforations. A magnetic field response recorder is used to wirelessly transmit the time-varying magnetic field and wirelessly detecting the conductor's harmonic response.

Woodard, Stanley E.↗

NASA NTRS2015

Experimentally Shocked and Altered Basalt: Laboratory Analogs for Calibration of Mars Remote Sensing and In Situ Data

Calcium phosphate (likely chloroapatite) is formed in the alteration experiments and is more abundant in the altered and shocked sample probably due to increased surface area exposed to alteration fluids resulting from shock damage in the form of both brittle and structural deformation to the starting material (Figs 1 & 3). Apatite forms in basic conditions so the closed system alteration experiment must be buffered by the basalt starting material to create a fluid chemistry environment evolving from neutral at the start to alkaline after 21 days at 160 degrees Centigrade. Plagioclase feldspar in the unshocked sample (Fig. 2) has undergone a solid-state transformation to maskelynite, a disordered phase that is not manifest in the X-ray diffraction pattern of the shocked sample (Fig.4). Olivine and ulvospinel that are present in the starting material can be detected by X-ray diffraction in the shocked and altered sample (Fig. 4). Tungsten from the sample holder used in the shock experiments dominates the X-ray diffraction pattern of the shocked and altered sample (Fig. 4). Samples were weighed after the alteration experiments to determine mass loss and predict the amount of material available for the planned analyses from the shock experiments. Within the constraints of these experiments, mass loss is negligible. The samples will next be characterized by Moessbauer and Vis-Near Infrared spectroscopy, the results of which will be compared to the Mars Exploration Rovers and Mars Reconnaissance Orbiter data sets respectively.

Bell, M. S.↗