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Results for “edge 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.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A temperature-induced hysteretic behavior of resistivity and magnetoresistance of electrodeposited bismuth microbridges for X-ray transition-edge sensor absorbers

This study investigates the temperature-induced hysteretic behavior of resistivity and magnetoresistance in electrodeposited bismuth films, with a focus on their application as absorbers in transition-edge sensors (TESs) for X-ray detection. Through a series of resistivity versus temperature measurements from room temperature to a few Kelvin, we explore the change in the conductive behavior of bismuth electrodeposited on various substrates. Our findings show for the first time both hysteretic and irreversible changes in resistivity as a function of temperature. Further, magnetoresistance measurements reveal notable variations in resistance behavior under different magnetic fields, highlighting the impact of magnetic fields on these films’ electronic transport properties, with an indication of potential weak anti-localization effects at the lowest temperatures. This study not only provides a deeper understanding of bismuth’s conductivity characteristics at low temperatures but also sheds light on the practical implications for developing more effective TESs for synchrotron X-ray facilities.

42 ENGINEERING↗
DOE OSTI2023

Improved microwave SQUID multiplexer readout using a kinetic-inductance traveling-wave parametric amplifier

We report on the use of a kinetic-inductance traveling-wave parametric amplifier (KITWPA) as the first amplifier in the readout chain of a microwave superconducting quantum interference device (SQUID) multiplexer (μmux). This μmux is designed to multiplex signals from arrays of low temperature detectors, such as superconducting transition-edge sensor microcalorimeters. When modulated with a periodic flux-ramp to linearize the SQUID response, the flux noise improves, on average, from 1.6 μ $\Phi$ 0 /$\sqrt{Hz}$ with the KITWPA off to 0.77 μ $\Phi$ 0 /$\sqrt{Hz}$ with the KITWPA on. When statically biasing the μmux to the maximally flux-sensitive point, the flux noise drops from 0.45 μ $\Phi$ 0 /$\sqrt{Hz}$ to 0.2 μ $\Phi$ 0 /$\sqrt{Hz}$⁠. We validate this new readout scheme by coupling a transition-edge sensor microcalorimeter to the μmux and detecting background radiation. In conclusion, the combination of μmux and KITWPA provides a variety of new capabilities including improved detector sensitivity and more efficient bandwidth utilization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Low energy backgrounds and excess noise in a two-channel low-threshold calorimeter

Here, we describe observations of low energy excess (LEE) events, background events observed in all light dark matter direct detection calorimeters, and noise in a transition edge sensor based two-channel silicon athermal phonon detector with 375 meV baseline energy resolution. We measure two distinct LEE populations: “shared” multichannel events with a pulse shape consistent with substrate athermal phonon events and sub-eV events that couple nearly exclusively to a single channel with a significantly faster pulse shape. These “singles” are consistent with events occurring within the aluminum athermal phonon collection fins. Similarly, our measured detector noise is higher than the theoretical expectation. Measured noise can be split into an uncorrelated component, consistent with shot noise from small energy depositions within the athermal phonon sensor itself, and a correlated component, consistent with shot noise from energy depositions within the silicon substrate's phonon system.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

First field test of a novel optical gas analyser in the exhaust of Wendelstein 7-X

A novel optical gas analyser, designed for isotope-resolved exhaust composition measurement, was field-tested at Wendelstein 7-X (W7-X) to validate its laboratory-proven concept under operational fusion experiment conditions. The system, Optix, comprises a cold cathode remote plasma generator and a high-resolution Fabry–Perot spectrometer and was deployed in the exhaust line of W7-X during the OP2.3 campaign. The injection of 3 He and 4 He for minority ion-cyclotron heating provided a test case for helium isotope discrimination. Despite limitations due to background gas and low partial pressures of the target species, isotope-resolved spectral signatures were successfully observed, demonstrating the fundamental viability of the Optix approach. Additionally, the spectrometer was evaluated for plasma emission measurements from both core and edge sightlines. While helium line emission was detectable, interpretation was hindered by complex background signals, highlighting the benefits of controlled remote plasma generators for spectroscopy. This first deployment provides critical insight into pressure requirements, spectral resolution, and operational constraints, informing future applications of optical exhaust diagnostics in fusion devices.

magnetic confinement fusion↗
DOE OSTI2024

MAPSTER: Automated Geospatial Data Sharing – Version 1.4.0

The US Department of Energy’s (DOE) Oak Ridge National Laboratory (ORNL) developed MAPSTER which is a geospatial data management tool that aggregates, organizes, and shares data from dispersed sources such as unmanned aerial systems (UAS). Built specifically for use in environments where communications may be limited, MAPSTER utilizes two key technologies to effectively manage data in the field and enable easy data sharing with authorized partners: Observer and Checkpoint. Observer is a lightweight software package on an edge device, such as a laptop, that automatically detects newly processed UAS data and sends to a central server called Checkpoint. Checkpoint is a centralized server at ORNL that receives and manages data from all Observer instances. Even in a very low bandwidth environment, Observer can still send information about the UAS data product almost instantly as it generates its own metadata package on the size of KB (kilobytes). MAPSTER is not only for UAS data but for any geospatial data collected at the austere edge and dispersed sources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Circular Trajectory Approach for Online Sinusoidal Signal Distortion Monitoring and Visualization

The increasing complexity and uncertainties of modern power systems are placing significant demands on signal monitoring techniques. This work proposes the Circular Trajectory Approach (CTA) for online sinusoidal signal distortion monitoring and visualization. CTA can detect distortions of a sinusoidal signal. Compared with existing waveform anomaly detection techniques, CTA is faster in detection and less computation intensive. It thus supports edge devices and online applications. CTA also offers a new means of sinusoidal signal distortion visualization. It can reveal the distorted sections in a sinusoidal cycle and clearly display the distortions. The proposed approach is tested on real data from an open source EPRI dataset.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Experimental studies of plasma-antenna coupling with the JET Alfvén Eigenmode Active Diagnostic

Here, this paper presents a dedicated study of plasma-antenna (PA) coupling with the Alfvén Eigenmode Active Diagnostic (AEAD) in JET. Stable AEs and their resonant frequencies f, damping rates γ < 0, and toroidal mode numbers n are measured for various PA separations and limiter versus X-point magnetic configurations. Two stable AEs are observed to be resonantly excited at distinct low and high frequencies in limiter plasmas. The values of f and n do not vary with PA separation. However, |γ| increases with PA separation for the low-f, but not high-f, mode, yet this may be due to slightly different edge conditions. The high-f AE is detected throughout the transition from limiter to X-point configuration, though its damping rate increases; the low-f mode, on the other hand, becomes unidentifiable. The linear, resistive MHD code CASTOR is used to simulate the frequency scan of an AEAD-like external antenna. For the limiter pulses, the high-f mode is determined to be an n = 0 GAE, while the low-f mode is likely an n = 2 TAE. During the transition from limiter to X-point configuration, CASTOR indicates that n = 1 and 2 EAEs are excited in the edge gap. These results extend previous experimental studies in JET and Alcator C-Mod; validate the computational work performed by Dvornova et al; and provide guidance for the optimization of PA coupling in upcoming JET energetic particle experiments, for which the AEAD will aim to identify the contribution of alpha particles to AE drive during the DT campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Experimental studies of plasma-antenna coupling with the JET Alfven Eigenmode Active Diagnostic

This paper presents a dedicated study of plasma-antenna (PA) coupling with the Alfven Eigenmode Active Diagnostic (AEAD) in JET. Stable AEs and their resonant frequencies f, damping rates gamma < 0, and toroidal mode numbers n are measured for various PA separations and limiter versus X-point magnetic configurations. Two stable AEs are observed to be resonantly excited at distinct low and high frequencies in limiter plasmas. The values of f and n do not vary with PA separation. However, |gamma| increases with PA separation for the low-f, but not high-f, mode, yet this may be due to slightly different edge conditions. The high-f AE is detected throughout the transition from limiter to X-point configuration, though its damping rate increases; the low-f mode, on the other hand, becomes unidentifiable. The linear resistive MHD code CASTOR is used to simulate the frequency scan of an AEAD-like external antenna. For the limiter pulses, the high-f mode is determined to be an n = 0 GAE, while the low-f mode is likely an n = 2 TAE. During the transition from limiter to X-point configuration, CASTOR indicates that n = 1 and 2 EAEs are excited in the edge gap. These results extend previous experimental studies in JET and Alcator C-Mod; validate the computational work performed by Dvornova et al 2020 Phys. Plasmas 27 012507; and provide guidance for the optimization of PA coupling in upcoming JET energetic particle experiments, for which the AEAD will aim to identify the contribution of alpha particles to AE drive during the DT campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A Dynamic Hierarchical Attention Framework for Multimodal Malware Detection

The increasing use of Android in the worldwide mobile ecosystem has come along with a significant increase in advanced malware, highlighting the critical necessity for efficient, scalable, and adaptable detection systems. Despite recent advancements in machine learning improving malware detection, the majority of current solutions are limited to one, two, or three data modalities, hence neglecting the comprehensive behavioral spectrum of contemporary multi-vector threats. This thesis presents the first comprehensive multimodal framework for Android malware detection, which combines textual, time-series (temporal), graph-based (structural), and visual information using an innovative hierarchical attention mechanism and Dynamic Fusion Controller (DFC). Our methodology consistently classifies and processes modalities as either sequential or structural, facilitating content-adaptive weighting and resilient cross-modal representation learning. We advance the implementation of cutting-edge time series techniques, such as MiniRocket, for malware detection, hence creating new opportunities for temporal analysis in cybersecurity. Comprehensive experimental assessment shows that our framework performs exceptionally well, with 99.46% classification accuracy and 97.15% detection accuracy, significantly outperforming existing approaches through effective multimodal integration and hierarchical attention mechanisms.

Nazmin, Tamanna↗
DOE OSTI2023

Accurate activity determination of a californium neutron source

Accurately counting analog events requires constructing an electronics chain that produces one count for each input pulse. Here, in this work, we review the use of Nuclear Instrumentation Module electronic units for counting neutron capture events in a 3He tube. We identify two unique types of false trigger events in a leading-edge discriminator and show how a dual timer module can be used to produce a veto window to exclude these events. We use the constructed electronics chain to build an apparatus to measure neutron pulses from a 252 Cf neutron source. We compare the measurements with a Monte Carlo N-Particle (MCNP) model to determine the activity of the neutron source. Furthermore, by making additional measurements with borated polyethylene attenuators between the source and detector, we are able to determine the boron concentration of the polyethylene. This technique provides accurate determination of the source activity to a precision of 2.8% at the k=1 level. The method used is simple, inexpensive, and requires no additional calibrated instruments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Nearly degenerate two-color impulsive coherent Raman hyperspectral imaging

Impulsive stimulated Raman scattering (ISRS) is a robust technique for studying low frequency (<300 cm –1 ) Raman vibrational modes, but ISRS has faced difficulty in translation to an imaging modality. A primary challenge is the separation of the pump and probe pulses. Here we introduce and demonstrate a simple strategy for ISRS spectroscopy and hyperspectral imaging that uses complementary steep edge spectral filters to separate the probe beam detection from the pump and enables simple ISRS microscopy with a single-color ultrafast laser source. ISRS spectra are obtained that span from the fingerprint region down to <50 cm –1 vibrational modes. Furthermore, hyperspectral imaging and polarization-dependent Raman spectra are also demonstrated.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Modeling the Vertical Response of an Aeroseismometer Balloon System

Aeroseismometery is a novel, cutting edge capability that involves balloon based systems for detecting and geolocating sources of infrasound. The incident infrasound from a range of sources such as volcanos, earthquakes, explosions, supersonic aircraft impinges upon the balloon system causing it to respond dynamically. The dynamic response is post-processed to locate the infrasound source. This report documents the derivation of an analytical model that predicts the balloon dynamics. Governing equations for the system are derived as well as a transfer function relating the infrasound signal to the net force on the balloon components. Experimental measurements of the infrasound signals are convolved with the transfer function and the governing equations numerically time integrated to obtain predictions of the displacement, velocity and acceleration of the balloon system. The predictions are compared to the experimental measurements with good agreement observed. The derivation focuses only on the vertical dynamics of the balloon system. Future work will develop governing equations for the swinging response of the balloon to the incident infrasound.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A network approach for multiscale catchment classification using traits

Abstract. The classification of river catchments into groups with similar biophysical characteristics is useful to understand and predict their hydrological behavior. The increasing availability of remote sensing and other large-scale geospatial datasets has enabled the use of advanced data-driven approaches to classify catchments using traits such as topography, geology, climate, land cover, land use, and human influence. Unsupervised clustering algorithms based on the Euclidean distance are commonly used for trait-based classification but are not suitable for highly dimensional data. In this study we present a new network-based method for multi-scale catchment classification, which can be applied to large datasets and used to determine the traits associated with different catchment groups. In this framework, two networks are analyzed in parallel: the first being where the nodes are traits and the second being where the nodes are catchments. In both cases, edges represent pairwise similarity, and a network cluster detection algorithm is used for the classification. The trait network is used to investigate redundancy in the trait data and to condense this information into a small number of interpretable categories. The catchments network is used to classify the catchments into clusters and to identify representative catchments for the different groups using the degree centrality metric. We apply this method to classify 9067 river catchments across the contiguous United States at both regional and continental scales using 274 non-categorical traits. At the continental scale, we identify 25 interpretable trait categories and 34 catchment clusters of sizes greater than 50. We find that catchments with similar trait categories are typically located in the same region, with different spatial patterns emerging among clusters dominated by natural and anthropogenic traits. We also find that the catchment clusters exhibit distinct hydrological behavior based on an analysis of streamflow indices. This network approach provides several advantages over traditional means of classification, including better separation of clusters, the use of alternate similarity metrics that are more suitable for highly dimensional data, and reducing redundancy in the trait information. The paired catchment–trait networks enable analysis of hydrological behavior using the dominant trait categories for each catchment cluster. The approach can be used at multiple spatial scales since the network topologies adjust automatically to reflect the trait patterns at the scale of investigation. Finally, the representative catchments identified as hub nodes in the network can be used to guide transferable observational and modeling strategies. The method is broadly applicable beyond hydrology for classification of other complex systems that utilize different types of trait datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

High-Pressure Investigation of 2,4,6-Trinitro-3-bromoanisole (TNBA): Structural Determination and Piezochromism

Understanding phase transitions in energetic materials is crucial for developing predictive models of detonation. 2,4,6-Trinitro-3-bromoanisole (TNBA), an energetic material, was studied in its single-crystal form up to pressures of 45 GPa in a diamond anvil cell. The material was characterized by using X-ray, Raman, and optical transmission measurements. From single-crystal X-ray diffraction, the ambient structure of TNBA was determined which crystallizes in the P2 1 /c space group having four molecular units per unit cell. The X-ray data up to 9.2 GPa were fitted to a third-order Birch–Murnaghan equation of state by using the parameters K o = 13.2(2.4) GPa and K p = 5.1(1.4). Between 6.8 and 7.3 GPa, a phase transition was inferred in TNBA from concurrent fading of X-ray diffraction, disappearance of Raman peaks, increase in sample fluorescence, and discontinuous color change. The new phase was consistent with an amorphous state of at least partially intact molecules judging from the presence of higher-order Raman modes and irreversibility of the Raman spectra upon release. Piezochromism was observed with the translucent yellow TNBA gradually darkening and becoming opaque black at ~25 GPa. This correlated to the absorption edge gradually shifting to the red in the visible spectrum. Signs of two possible additional structural transitions were detected in the 32.4–41.0 GPa range as suggested by a jump in the absorption edge, the irreversible changes in the absorption spectrum upon release to ambient pressure, and by the lack of Raman modes in recovered samples. Here, the crystal and electronic structures of TNBA were also investigated up to 10 GPa by using DFT calculations and crystal structure prediction (CSP) simulations. In agreement with the experimentally observed transition at 7 GPa, the simulations at 10 GPa found a bevy of polymorphs lower in enthalpy and higher in density than P2 1 /c. The lowest calculated enthalpy structure was determined to be P2 1 2 1 2 1 , being in a different space group than the ambient experimental result.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Integrating 5G Technology for Improved Process Monitoring and Network Slicing in ICS

Industrial Control Systems (ICS) are crucial for monitoring physical processes that support essential cyber-enabled services like power generation. The use of proprietary communication and lack of effective intrusion detection mechanisms pose constraints for efficient operation. Therefore, there is a need to modernize these systems with decentralized technologies like Edge Computing and 5G. However, integrating 5G and Edge Computing into large-scale ICS networks presents implementation and performance challenges. To address these challenges, this paper proposes an integrated ICS architecture that combines 5G and Edge Computing technologies with traditional ICS protocols. The objective is to minimize implementation and operational difficulties while improving the monitoring of physical processes and enabling robust intrusion detection. The proposed architecture outlines the necessary components, services, and communication protocols required for the integration of 5G and Edge Computing.

Aguayo, Jared M.↗
DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy's National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real-time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI's Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: Run in real-time on the edge (≥ 12 Hz), Classification: Achieve less than 5% false positive detection, Classification: Achieve ≥ 95% methane plume detection rate, Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time. In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗
DOE OSTI2024

Transmission interference fringe ( TIF ) technique for the dynamic visualization of evaporating droplet

Here, the transmission interference fringe (TIF) technique was developed to visualize the dynamics of evaporating droplets based on the Reflection Interference Fringe (RIF) technique for micro-sized droplets. The geometric formulation was conducted to determine the contact angle (CA) and height of macro-sized droplets without the need for the prism used in RIF. The TIF characteristics were analyzed through experiments and simulations to demonstrate a wider range of contact angles from 0 to 90°, in contrast to RIF's limited range of 0–30°. TIF was utilized to visualize the dynamic evaporation of droplets in the constant contact radius (CCR) mode, observing the droplet profile change from convex-only to convex-concave at the end of dry-out from the interference fringe formation. The TIF also observed the contact angle increase from the fringe radius increase. This observation is uniquely reported as the interference fringe (IF) technique can detect the formation of interference fringe between the reflection from the center convex profile and the reflection from the edge concave profile on the far-field screen. Unlike general microscopy techniques, TIF can detect far-field interference fringes as it focuses beyond the droplet-substrate interface. The formation of the convex-concave profile during CCR evaporation is believed to be influenced by the non-uniform evaporative flux along the droplet surface.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Optically induced quantum transitions in direct probed mesoscopic NbSe 2 for prototypical bolometers

Superconducting transition-edge sensors (TES) have emerged as fascinating devices to detect broadband electromagnetic radiation with low thermal noise. The advent of metallic transition metal dichalcogenides, such as NbSe 2 , has also created an impetus to understand their low-temperature properties, including superconductivity. Interestingly, NbSe 2 -based sensor within the TES framework remains unexplored. In this work, direct-probed superconducting NbSe 2 absorbers led to a proof-of-concept demonstration for the transduction of incoming light to heat, where a thermodynamic superconducting phase transition in NbSe 2 was evident to switch it to the normal-state, when biased below its superconducting transition temperature. A wavelength-dependent response of its optical absorption properties was observed, based on the incident optical excitation source used. Furthermore, extensive optical characterization studies were conducted using Raman spectroscopy, where the in-plane and out-of-plane thermal conductivity was empirically determined. Our results open new possibilities for the use of NbSe 2 in superconducting radiation detectors, including in a TES framework

47 OTHER INSTRUMENTATION↗