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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.

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At least 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Autonomous management of a recursive area hierarchy for large scale wireless sensor networks using multiple parents

Large scale wireless sensor networks have been proposed for applications ranging from anomaly detection in an environment to vehicle tracking. Many of these applications require the networks to be distributed across a large geographic area while supporting three to five year network lifetimes. In order to support these requirements large scale wireless sensor networks of duty-cycled devices need a method of efficient and effective autonomous configuration/maintenance. This method should gracefully handle the synchronization tasks duty-cycled networks. Further, an effective configuration solution needs to recognize that in-network data aggregation and analysis presents significant benefits to wireless sensor network and should configure the network in a way such that said higher level functions benefit from the logically imposed structure. NOA, the proposed configuration and maintenance protocol, provides a multi-parent hierarchical logical structure for the network that reduces the synchronization workload. It also provides higher level functions with significant inherent benefits such as but not limited to: removing network divisions that are created by single-parent hierarchies, guarantees for when data will be compared in the hierarchy, and redundancies for communication as well as in-network data aggregation/analysis/storage.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Majorana neutrinos and dark matter from anomaly cancellation

We discuss a simple theory for neutrino masses where the total lepton number is a local gauge symmetry spontaneously broken below the multi-TeV scale. In this context, the neutrino masses are generated through the canonical seesaw mechanism and a Majorana dark matter candidate is predicted from anomaly cancellation. We discuss in great detail the dark matter annihilation channels and find out the upper bound on the symmetry-breaking scale using the cosmological bounds on the relic density. Since in this context the dark matter candidate has suppressed couplings to the Standard Model quarks, one can satisfy the direct detection bounds even if the dark matter mass is close to the electroweak scale. This theory predicts a light pseudo-Nambu-Goldstone boson (the Majoron) associated to the mechanism of neutrino mass. We discuss briefly the properties of the Majoron and the impact of the big bang nucleosynthesis bounds. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2018

Feasibility study for detection of fuel assemblies state inside sealed dry storage casks using external gamma flux measurements - 25445

The license for the storage of spent nuclear fuel assemblies in dry casks is limited to 40 years. In Germany, a site for a final repository of spent fuel is not yet available. Therefore, this license has to be renewed for prolonged storage period. Currently, there is no experience with dry cask storage worldwide that goes beyond a period of 40 years. Beside regulatory and security aspects, there are questions concerning the long-term integrity of the spent fuel assemblies as this is of relevance for final transportation and reloading to final waste repository casks. Once the cask is filled and sealed, the knowledge about the state of the fuel assemblies is limited. This study investigates the feasibility of using external gamma flux measurements to detect the state of the spent fuel assemblies inside the cask. Monte-Carlo simulations were performed to evaluate the gamma flux distribution outside the sidewall of a cask with all intact fuel assemblies and a cask with one damaged fuel assembly, mimicking a fuel assembly with expanded rods and fuel relocation. The evaluation was performed for different location of the damaged fuel assembly and different storage times. The results of the investigation showed that the intensity and the shape of the gamma flux outside the sidewall of the cask are sufficient to identify the damaged fuel assembly, in case it is located near the inner wall of the cask. The detection of the inner damaged fuel assemblies, however, is less feasible. Due to the self-shielding of the fuel assemblies, the gamma photons which come from the inner fuel assemblies stopped within the fuel basket and assemblies materials. The gamma photons which do survive the fuel assemblies self-shielding reach the inner cask wall with not enough energy to escape the shielding of the thick cast iron wall. In general, it can be concluded that the more the damaged fuel assembly is close to the cask inner walls and that the damage is in a large scale (i.e., significant fuel relocation), the more it can be detected by external gamma flux measurements. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Describing Point Defect Topology in 2D Energy Materials through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2d materials↗
DOE OSTI2025

Describing Point Defect Topology in 2D Energy Materials Through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. We employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2D materials↗
DOE OSTI2018

Maximizing ozone signals among chemical, meteorological, and climatological variability

The detection of meteorological, chemical, or other signals in modeled or observed air quality data – such as an estimate of a temporal trend in surface ozone data, or an estimate of the mean ozone of a particular region during a particular season – is a critical component of modern atmospheric chemistry. However, the magnitude of a surface air quality signal is generally small compared to the magnitude of the underlying chemical, meteorological, and climatological variabilities (and their interactions) that exist both in space and in time, and which include variability in emissions and surface processes. This can present difficulties for both policymakers and researchers as they attempt to identify the influence or signal of climate trends (e.g., any pauses in warming trends), the impact of enacted emission reductions policies (e.g., United States NO x State Implementation Plans), or an estimate of the mean state of highly variable data (e.g., summertime ozone over the northeastern United States). Here we examine the scale dependence of the variability of simulated and observed surface ozone data within the United States and the likelihood that a particular choice of temporal or spatial averaging scales produce a misleading estimate of a particular ozone signal. Our main objective is to develop strategies that reduce the likelihood of overconfidence in simulated ozone estimates. We find that while increasing the extent of both temporal and spatial averaging can enhance signal detection capabilities by reducing the noise from variability, a strategic combination of particular temporal and spatial averaging scales can maximize signal detection capabilities over much of the continental US. For signals that are large compared to the meteorological variability (e.g., strong emissions reductions), shorter averaging periods and smaller spatial averaging regions may be sufficient, but for many signals that are smaller than or comparable in magnitude to the underlying meteorological variability, we recommend temporal averaging of 10–15 years combined with some level of spatial averaging (up to several hundred kilometers). If this level of averaging is not practical (e.g., the signal being examined is at a local scale), we recommend some exploration of the spatial and temporal variability to provide context and confidence in the robustness of the result. These results are consistent between simulated and observed data, as well as within a single model with different sets of parameters. The strategies selected in this study are not limited to surface ozone data and could potentially maximize signal detection capabilities within a broad array of climate and chemical observations or model output.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Canister Helium Leak Detection Based on Temperature Information Using RAMM (Final CRADA Report)

The performance of RAMM-TM in detecting gas leakage from a canister with a small, simulated chloride-induced stress corrosion crack has been demonstrated in a series of experiments conducted at CRIEPI by using a 1/4.5- scale model cask. Leakage of both helium and air from a canister was detected within hours after the start of the leakage. The change in surface temperatures at the top and bottom of the canister (ΔTBT) during gas leakage (depressurization) triggered automatic alarms, providing a sound basis for early detection of gas leakage from the canister. This methodology would enable consequence management through the implementation of mitigatory actions to continue effective aging management, to reduce risks to public safety and health, and to protect the environment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1992

An energy analysis of crack-initiation and arrest in epoxy

The objective of this work is to study fracture processes such as crack initiation and arrest in epoxy. A compact tension specimen with displacement-controlled loading is employed to observe multiple crack initiations and arrests. The energy release rate at crack initiation is significantly higher than that at crack arrest, as has been observed elsewhere. In this study, the difference between these energy release rates is found to depend on specimen size (scale effect), and is quantitatively related to the fracture surface morphology. The scale effect, similar to that in strength theory, is conventionally attributed to the statistics of defects which control the fracture process. Triangular shaped ripples, deltoids, are formed on the fracture surface of the epoxy during the slow sub-critical crack growth, prior to the smooth mirrorlike surface characteristic of fast cracks. The deltoids are complimentary on the two crack faces which excludes any inelastic deformation from consideration. The deltoids are analogous to the ripples created on a river surface downstream from a small obstacle. However, in spite of the expectation based on this analogy and the observed scale effect, there are no 'defects' at the apex of the deltoids detectable down to the 0.1 micron level. This suggests that the formation of deltoids during the slow process of subcritical crack growth is an intrinsic feature of the fracture process itself, triggered by inhomogeneity of material on a submicron scale. This inhomogeneity may be related to a fluctuation in the cross-link density of the epoxy.

Chudnovsky, A.↗
DOE OSTI2023

Laser Characterization of Optically Smooth BREAD parts

The Broadband Reflector Experiment for Axion Detection is a dish antenna experiment probing the axion and dark photon parameter space in the [1 μeV, 1 eV] mass range, or [.02, 200] THz frequency range. In the pilot design for the InfraBREAD model, the dish antenna includes an optically smooth coaxial parabolic reflector to focus incoming photons in the near Infrared spectrum, created by the spontaneous photoconversion of axions and dark photons, onto a Superconducting Nanowire Single Photon Detector at the focus point of the reflector. As the pilot begins as a dark photon detector, sensitivity estimates hypothesize that it could cover unprobed parameter space in the search for the dark photon. Because of this, it is of critical importance that the reflector and SNSPD be placed at the correct points in the dish antenna, as previous work has shown that in addition to the focal spot of the photons being smeared to an area larger than the SNSPD, detection efficiency is s ensitive to shifts on the millimeter scale. In order to constrain this barrier to efficiency, the reflector had its focal spot, roughness, and length of surface waves measured by lasers in an optical bench setup. Results show the focal point diverging slightly from its theorized position in the antenna, while uncertainty in the height at which the detector should be placed was constrained to 10s of microns, the uncertainty in radial position could not be constrained to smaller than the detector given the methods used. Results for the roughness and surface wavelength show that the reflector was uniformly machined in a diamond-turning process used to fabricate optically smooth parts, as well as support a roughly 90% detection efficiency, reinforcing the sensitivity estimates presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Physics at the MeV-Scale in Liquid Argon Time Projection Chambers

The liquid argon time projection chamber (LArTPC) is the detection technology chosen for several Fermilab-based neutrino experiments. This technology will be used in studies of neutrino cross-sections and oscillations, neutrinos from supernovae as well as a variety of studies of beyond the Standard Model physics. This thesis explores the use of these detectors to study MeV-scale activity. MeV-scale electrons arising from Compton scatters of deexcitation photons and photons from inelastic neutron scattering in neutrino-nucleus interactions are reconstructed using novel methods presented here. This work represents the first demonstration of MeV-scale physics capabilities in a LArTPC neutrino experiment as well as the first observation of neutrino-produced photons from nuclear de-excitation and inelastic neutron scattering. A search for millicharged particles, postulated by theories of beyond the standard model physics, is also performed using data from a LArTPC and the low-ener gy reconstruction techniques developed. The results set world-leading bounds on the parameter space of millicharged particles. The work in this thesis demonstrates that studies of MeV-scale activity and new physics are possible with LArTPC technology and provides the foundation for future LArTPC studies of low energy neutrinos and new physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Alternate Null Hypothesis Correlation: A New Approach to Automatic Seismic Event Detection

This paper describes a new method of seismic signal detection that improves upon the conventional waveform correlation method. Recent studies suggested that a significant limiting factor in the application of waveform correlation to regional and global scale monitoring is the false alarm rate. The false alarms do not originate from detections on noise but rather from seismic arrivals with unrelated source locations. This article presents results from an approach to waveform correlation that exploits techniques from signal processing and machine learning to improve the accuracy of detecting seismic arrivals. We modify the detection model for waveform correlation such that transient signals from noncollocated seismicity are considered when designing the detectors. The new approach uses waveform templates from known catalog events to train a supervised machine learning algorithm that derives a new set of detectors to represent the unique characteristics of the template waveforms; these new detectors maximize the likelihood of detecting only the desired events, thereby minimizing false alarms. We train a waveform correlation template library for a single three-component seismic monitoring station. We then review results from applying the new detectors, known as alternate null hypothesis correlation (ANCorr) templates, to a test set of seismic waveforms. Finally, we compare ANCorr results with those from application of the conventional waveform correlation matched filter technique.

58 GEOSCIENCES↗
DOE OSTI2016

DOUBLE DYNAMO SIGNATURES IN A GLOBAL MHD SIMULATION AND MEAN-FIELD DYNAMOS

The 11 year solar activity cycle is the most prominent periodic manifestation of the magnetohydrodynamical (MHD) large-scale dynamo operating in the solar interior, yet longer and shorter (quasi-) periodicities are also present. The so-called “quasi-biennial” signal appearing in many proxies of solar activity has been gaining increasing attention since its detection in p -mode frequency shifts, which suggests a subphotospheric origin. A number of candidate mechanisms have been proposed, including beating between co-existing global dynamo modes, dual dynamos operating in spatially separated regions of the solar interior, and Rossby waves driving short-period oscillations in the large-scale solar magnetic field produced by the 11 year activity cycle. In this article, we analyze a global MHD simulation of solar convection producing regular large-scale magnetic cycles, and detect and characterize shorter periodicities developing therein. By constructing kinematic mean-field α {sup 2}Ω dynamo models incorporating the turbulent electromotive force (emf) extracted from that same simulation, we find that dual-dynamo behavior materializes in fairly wide regions of the model’s parameters space. This suggests that the origin of the similar behavior detected in the MHD simulation lies with the joint complexity of the turbulent emf and differential rotation profile, rather that with dynamical interactions such as those mediated by Rossby waves. Analysis of the simulation also reveals that the dual dynamo operating therein leaves a double-period signature in the temperature field, consistent with a dual-period helioseismic signature. Order-of-magnitude estimates for the magnitude of the expected frequency shifts are commensurate with helioseismic measurements. Taken together, our results support the hypothesis that the solar quasi-biennial oscillations are associated with a secondary dynamo process operating in the outer reaches of the solar convection zone.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Feature detection and matching on atmospheric nuclear detonation video

Automated feature matching of nuclear detonations (NUDETs) enables three‐dimensional point cloud reconstruction, and establishment a volume‐based model to reduce uncertainty in estimating the yield of NUDETs solely from video. Establishing a volume‐based model requires feature correspondences between wide viewpoints of 58°–110° that are larger than scale‐invariant feature transform‐based techniques can reliably match. The presented technique detects relative bright features in the NUDET known as ‘hotspots,’ and matches them across wide viewpoints using a spherical based object model. Results show that hotspots can be detected with a 71.95% hit rate and 86.03% precision. Hotspots are matched to films from different viewpoints with 76.6% correctness and a standard deviation of 16.4%. Hotspot descriptors are also matched in time sequence with 99.6% correctness and a standard deviation of 1.07%. The results demonstrate that a spherical model can serve as a viable descriptor model for matching across wide viewpoints when the object is known to be spherical. It also demonstrates an automated feature detection and matching combination that enables features to be matched from unsynchronised video across wide viewpoints of 58°–110° on spherical objects where state‐of‐the‐art techniques are insufficient.

Schmitt, Daniel T.↗
DOE OSTI2016

A characteristic transmission spectrum dominated by H{sub 2}O applies to the majority of HST/WFC3 exoplanet observations

Currently, 19 transiting exoplanets have published transmission spectra obtained with the Hubble/WFC3 G141 near-IR grism. Using this sample, we have undertaken a uniform analysis incorporating measurement-error debiasing of the spectral modulation due to H{sub 2}O, measured in terms of the estimated atmospheric scale height, H{sub s}. For those planets with a reported H{sub 2}O detection (10 out of 19), the spectral modulation due to H{sub 2}O ranges from 0.9 to 2.9 H{sub s} with a mean value of 1.8 ± 0.5 H{sub s}. This spectral modulation is significantly less than predicted for clear atmospheres. For the group of planets in which H{sub 2}O has been detected, we find the individual spectra can be coherently averaged to produce a characteristic spectrum in which the shape, together with the spectral modulation of the sample, are consistent with a range of H{sub 2}O mixing ratios and cloud-top pressures, with a minimum H{sub 2}O mixing ratio of 17{sub −6}{sup +12} ppm corresponding to the cloud-free case. Using this lower limit, we show that clouds or aerosols must block at least half of the atmospheric column that would otherwise be sampled by transmission spectroscopy in the case of a cloud-free atmosphere. We conclude that terminator-region clouds with sufficient opacity to be opaque in slant-viewing geometry are common in hot Jupiters.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2012

High-Contrast NIR Polarization Imaging of MWC480

One of the key predictions of modeling from the IR excess of Herbig Ae stars is that for protoplanetary disks, where significant grain growth and settling has occurred, the dust disk has flattened to the point that it can be partially or largely shadowed by the innermost material at or near the dust sublimation radius. When the self-shadowing has already started, the outer disk is expected to be detected in scattered light only in the exceptional cases that the scale height of the dust disk at the sublimation radius is smaller than usual. High-contrast imaging combined with the IR spectral energy distribution allow us to measure the degree of flattening of the disk, as well as to determine the properties of the outer disk. We present polarimetric differential imaging in H band obtained with Subaru/HiCIAO of one such system, MWC 480. The HiCIAO data were obtained at a historic minimum of the NIR excess. The disk is detected in scattered light from 0".2-1"0 (27.4-137 AU). Together with the marginal detection of the disk from 1998 February 24 by HST / NICMOS, our data constrain the opening half angle for the disk to lie between 1.3 <= Theta <=2.2 deg. When compared with similar measures in CO for the gas disk from the literature, the dust disk subtends only approx 30% of the gas disk scale height (H/R approx 0. 03). Such a dust disk is a factor of 5-7 flatter than transitional disks, which have structural signatures that giant planets have formed.

McElwain, M. W.↗
DOE OSTI2025

Boosting H I -Galaxy Cross-Clustering Signal through Higher-Order Cross-Correlations

After reionization, neutral hydrogen (${\rm H\, \small {I}}$) traces the large-scale structure (LSS) of the Universe, enabling ${\rm H\, \small {I}}$ intensity mapping (IM) to capture the LSS in 3D and constrain key cosmological parameters. We present a new framework utilizing higher-order cross-correlations to study ${\rm H\, \small {I}}$ clustering around galaxies, tested using real-space data from the IllustrisTNG300 simulation. This approach computes the joint distributions of k-nearest neighbor (kNN) optical galaxies and the ${\rm H\, \small {I}}$ brightness temperature field smoothed at relevant scales (the kNN-field framework), providing sensitivity to all higher-order cross-correlations, unlike two-point statistics. To simulate ${\rm H\, \small {I}}$ data from actual surveys, we add random thermal noise and apply a simple foreground cleaning model, filtering out Fourier modes of the brightness temperature field with k ∥ < k min,∥ . Under current levels of thermal noise and foreground cleaning, typical of a Canadian Hydrogen Intensity Mapping Experiment (CHIME)-like survey, the ${\rm H\, \small {I}}$-galaxy cross-correlation signal in our simulations, using the kNN-field framework, is detectable at >30σ across r = [3, 12] h –1 Mpc. In contrast, the detectability of the standard two-point correlation function (2PCF) over the same scales depends strongly on the foreground filter: a sharp k ∥ filter can spuriously boost detection to 8σ due to position-space ringing, whereas a less sharp filter yields no detection. Nonetheless, we conclude that kNN-field cross-correlations are robustly detectable across a broad range of foreground filtering and thermal noise conditions, suggesting their potential for enhanced constraining power over 2PCFs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Radiological characterization of high Cs-137 waste items at LANL combining Cs-137 NDA results and acceptable process knowledge - 15592

Radiological characterization is an important component to disposition and disposal of radioactive waste at the Los Alamos National Laboratory. Gamma and neutron based non-destructive assay systems are available at LANL's TA-54 Area G for radiological characterization and are generally very effective in quantifying the transuranic radionuclide concentration required for a TRU or low level waste disposition determination. This is routinely performed by scaling some nuclides to direct assay results using acceptable process knowledge scaling from a directly measured key TRU nuclide, e.g., for gamma systems using a standard isotopic distribution to determine the amount of Pu-240 associated with a measured value of Pu-239. However, for two groups of LANL waste items that have high levels of Cs-137, these non-destructive assay systems were unable to make a standard TRU/LLW determination. Therefore, it was necessary to apply an extension of the typical scaling technique that keyed in on the direct Cs-137 gamma assay result to effectively characterize these waste items for TRU processing or LLW disposition. Two basic types of waste packages contained the high Cs-137 waste requiring special scaling: drums and boxes. The drums included 55-gallon, 85-gallon and 110-gallon volume sizes and the boxes included a corrugated metal box, a Standard Waste Box, and several overpack boxes containing oversized waste. All of these items contained radioactive waste generated from operations at the Chemistry and Metallurgical Research facility at LANL that included hot cell, metallographic sectioning and maintenance activities. All of the drums as well as the CMB, SWB and one oversized item in a plywood box were located above-ground at LANL's TA-54 Area G, while five of the oversized items were hot cell liners in metal boxes stored below-ground in shafts. All of the items were measured in the 2013-2014 time period at TA-54 Area G with LANL NDA systems. Most of the items were counted with LLW certified far-field gamma spectroscopy systems employing portable far-field HPGe detectors and carts and some of the items were counted on WIPP certified gamma only or gamma with neutron NDA systems. In all cases Cs-137 was quantified directly with a gamma measurement but the key TRU nuclides were not detectable. Thus, for each waste item AK/PK was studied and scaling factors to Cs-137 were established and applied to provide a comprehensive radiological characterization. A total of 49 waste items were successfully characterized as LLW based on this technique. The above ground waste items were dispositioned and disposed of at an offsite LLW repository and the below ground boxes were left in place as LLW in the TA-54 Area G shafts. This NDA with scaling application has proved effective and defensible in these high Cs-137 cases at LANL and will continue to be used as applicable and appropriate for future waste characterization at LANL. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Prescriptive provenance for streaming analysis of workflows at scale

Abstract- We extend our approach capturing and relating the provenance and performance metrics of computational workflows as a diagnostic tool for runtime optimization and placement. One important challenge is the volume of extracted data, both for performance metrics and provenance, even when specifying filters and focusing on quantities of interest in a simulation. We reduce this data by performing anomaly detection on streaming data and store provenance for the detected anomalies, an approach we call prescriptive provenance. This paper discusses the Chimbuko architecture enabling the approach. We present the use of a protein structure propagation workflow based on NWChemEx. We are testing algorithms for anomaly detection and present preliminary results here obtained with Local Outlier Factor. While scaling remains a challenge, these results show that our robust Chimbuko architecture for streaming analysis with prescriptive provenance is a promising approach.

97 MATHEMATICS AND COMPUTING↗