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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Elucidating the Discharge Behavior of Aqueous Zinc Sulfur Batteries in the Presence of Molybdenum(IV) Chalcogenide Catalyst: The Criticality of Interfacial Electrochemistry

The aqueous zinc-sulfur battery holds promise for significant capacity and energy density with low cost and safe operation based on environmentally benign materials. However, it suffers from the sluggish kinetics of the conversion reaction. Here, we highlight the efficacy of molybdenum(IV) sulfide (MoS 2 ) to reduce the overpotential of S-ZnS conversion in aqueous electrolytes and study the discharge products formed at the solid-solid and solid-liquid interfaces using experimental and theoretical approaches. Specifically, the MoS 2 -catalyzed electrochemical conversion reaction is characterized via ex situ X-ray diffraction (XRD), transmission electron microscopy (TEM) with energy dispersive spectroscopy (EDS), Raman spectroscopy, synchrotron-based Mo K-edge X-ray absorption spectroscopy (XAS), and in situ synchrotron-based X-ray computed tomography (XCT). Additionally, operando synchrotron-based S K-edge XAS and X-ray fluorescence (XRF) maps are collected to determine the spatial evolution of sulfur-based species at the electrode-electrolyte interface. Further, coupling the operando S K-edge XAS data with the simulated spectra and fitting the data suggested a possible ZnS 2 intermediate phase.

25 ENERGY STORAGE↗
DOE OSTI2022

The edges of galaxies: Tracing the limits of star formation

The outskirts of galaxies have been studied from multiple perspectives for the past few decades. However, it is still unknown if all galaxies have clear-cut edges similar to everyday objects. We address this question by developing physically motivated criteria to define the edges of galaxies. Based on the gas density threshold required for star formation, we define the edge of a galaxy as the outermost radial location associated with a significant drop in either past or ongoing in situ star formation. We explore ~1000 low-inclination galaxies with a wide range in morphology (dwarfs to ellipticals) and stellar mass (10 7 M ⊙ < M * < 10 12 M ⊙ ). The location of the edges of these galaxies (R edge ) were visually identified as the outermost cutoff or truncation in their radial profiles using deep multi-band optical imaging from the IAC Stripe82 Legacy Project. We find this characteristic feature at the following mean stellar mass density, which varies with galaxy morphology: 2.9 ± 0.10 M ⊙ pc -2 for ellipticals, 1.1 ± 0.04 M ⊙ pc -2 for spirals, and 0.6 ± 0.03 M ⊙ pc -2 for present-day star-forming dwarfs. Additionally, we find that R edge depends on its age (colour) where bluer galaxies have larger R edge at a fixed stellar mass. The resulting stellar mass–size plane using R edge as a physically motivated galaxy size measure has a very narrow intrinsic scatter (≲0.06 dex). These results highlight the importance of new deep imaging surveys to explore the growth of galaxies and trace the limits of star formation in their outskirts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Demonstration Trials of AI/ML Edge+Cloud Suite (CRADA Final Report)

PACE AI and LBNL partnered under this CRADA to test and evaluate the PACE5 edge node prototype, an AI/ML edge and cloud-based suite, at FLEXLAB.The objective of the test was to evaluate the PACE5 edge node prototype's ability to perform demand shed and take to dynamic price signals, and to demonstrate advanced fault detection and microgrid monitoring capabilities.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2011

Development of a Real-Time Pulse Processing Algorithm for TES-Based X-Ray Microcalorimeters

We report here a real-time pulse processing algorithm for superconducting transition-edge sensor (TES) based x-ray microcalorimeters. TES-based. microca1orimeters offer ultra-high energy resolutions, but the small volume of each pixel requires that large arrays of identical microcalorimeter pixe1s be built to achieve sufficient detection efficiency. That in turn requires as much pulse processing as possible must be performed at the front end of readout electronics to avoid transferring large amounts of data to a host computer for post-processing. Therefore, a real-time pulse processing algorithm that not only can be implemented in the readout electronics but also achieve satisfactory energy resolutions is desired. We have developed an algorithm that can be easily implemented. in hardware. We then tested the algorithm offline using several data sets acquired with an 8 x 8 Goddard TES x-ray calorimeter array and 2x16 NIST time-division SQUID multiplexer. We obtained an average energy resolution of close to 3.0 eV at 6 keV for the multiplexed pixels while preserving over 99% of the events in the data sets.

Tan, Hui↗
NASA NTRS1978

Adjustable securing base

An adjustable securing base had a surface radius of curvature which was adjusted to support an adjacent part on the base surface. The securing base comprised of a flexible thin plate with an adjustment mechanism connected on opposite edges of the base for adjusting the plate curvature. An opening in the plate was coupled to a vacuum device for securing the part adjacent to the plate surface.

Zebus, P. P.↗
DOE OSTI2016

Surface nanopattern formation due to current-induced homoepitaxial nanowire edge instability

Physical nanopatterning based on a precise control of macroscopic forcing is an essential tool of nanoscale science and technology. Using an externally applied electric field as the macroscopic force, we report here a computational study on the formation of surface nanopatterns consisting of single-layer homoepitaxial islands as a result of a morphological instability that can occur under edge electromigration conditions on the straight edge of a single-layer nanowire grown epitaxially on a crystalline substrate. Direct dynamical simulations based on a model that has been validated experimentally for the Ag/Ag system show that the current-induced nanowire edge instability causes the breakup of the nanowire and leads to the formation of uniformly distributed islands, arranged in linear or V-shaped arrays, which are uniformly sized with nanoscale dimensions. The simulation results are supported by linear stability theory and demonstrate that the geometrical features of the island patterns and the island sizes can be controlled precisely by controlling the electric field direction with respect to the nanowire axis and the electric field strength. Our findings have important implications for developing physical nanopatterning approaches toward enabling future nanofabrication technologies.

36 MATERIALS SCIENCE↗
NASA NTRS2000

Augmentation of Stagnation Region Heat Transfer Due to Turbulence From a DLN Can Combustor

Heat transfer measurements have been made in the stagnation region of a flat plate with a circular leading edge. Electrically heated aluminum strips placed symmetrically about the leading edge stagnation region were used to measure spanwise averaged heat transfer coefficients. The maximum Reynolds number obtained, based on leading edge diameter, was about 100,000. The model was immersed in the flow field downstream of an approximately half scale model of a can-type combustor from a low NO(x), ground based power-generating turbine. The tests were conducted with room temperature air; no fuel was added. Room air flowed into the combustor through six vane type fuel/air swirlers. The combustor can contained no dilution holes. The fuel/air swirlers all swirled the incoming airflow in a counter clockwise direction (facing downstream). A 5-hole probe flow field survey in the plane of the model stagnation point showed the flow was one big vortex with flow angles up to 36' at the outer edges of the rectangular test section. Hot wire measurements showed test section flow had very high levels of turbulence, around 28.5 percent, and had a relatively large axial-length scale-to-leading edge diameter ratio of 0.5. X-wire measurements showed the turbulence to be nearly isotropic. Stagnation heat transfer augmentation over laminar levels was around 77 percent and was about 14 percent higher than predicted by a previously developed correlation for isotropic grid generated turbulence.

VanFossen, G. James↗
NASA NTRS2008

Recent Developments in Transition-Edge Strip Detectors for Solar X-Rays

LMSAL and NIST are developing position-sensitive x-ray strip detectors based on Transition Edge Sensor (TES) microcalorimeters optimized for solar physics. By combining high spectral (E/ delta E approximately equals 1600) and temporal (single photon delta t approximately equals 10 micro s) resolutions with imaging capabilities, these devices will be able to study high-temperature (>l0 MK) x-ray lines as never before. Diagnostics from these lines should provide significant new insight into the physics of both microflares and the early stages of flares. Previously, the large size of traditional TESs, along with the heat loads associated with wiring large arrays, presented obstacles to using these cryogenic detectors for solar missions. Implementing strip detector technology at small scales, however, addresses both issues: here, a line of substantially smaller effective pixels requires only two TESs, decreasing both the total array size and the wiring requirements for the same spatial resolution. Early results show energy resolutions of delta E(sub fwhm) approximately equals 30 eV and spatial resolutions of approximately 10-15 micron, suggesting the strip-detector concept is viable.

Rausch, Adam J.↗
DOE OSTI2014

AHF: Array-Based Half-Facet Data Structure for Mixed-Dimensional and Non-Manifold Meshes

We present an Array-based Half-Facet mesh data structure, or AHF, for efficient mesh query and modification operations. The AHF extends the compact array-based half-edge and half-face data structures (T.J. Alumbaugh and X. Jiao, Compact array-based mesh data structures, IMR, 2005) to support mixed-dimensional and non-manifold meshes. The design goals of our data structure include generality to support such meshes, efficiency of neighborhood queries and mesh modification, compactness of memory footprint, and facilitation of interoperability of mesh-based application codes. To accomplish these goals, our data structure uses sibling half-facets as a core abstraction, coupled with other explicit and implicit representations of entities. A unique feature of our data structure is a comprehensive implementation in MATLAB, which allows rapid prototyping, debugging, testing, and deployment of meshing algorithms and other mesh-based numerical methods. We have also developed C++ implementation built on top of MOAB (T.J. Tautges, R. Meyers, and K. Merkley, MOAB: A Mesh-Oriented Database, Sandia National Laboratories, 2004). We present some comparisons of the memory requirements and computational costs, and also demonstrate its effectiveness with a few sample applications.

Dyedov, Volodymyr↗
DOE OSTI2015

System and method for automated object detection in an image

A contour/shape detection model may use relatively simple and efficient kernels to detect target edges in an object within an image or video. A co-occurrence probability may be calculated for two or more edge features in an image or video using an object definition. Edge features may be differentiated between in response to measured contextual support, and prominent edge features may be extracted based on the measured contextual support. The object may then be identified based on the extracted prominent edge features.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2001

Augmentation of Stagnation Region Heat Transfer Due to Turbulence from a DLN Can Combustor

Heat transfer measurements have been made in the stagnation region of a flat plate with a circular leading edge. Electrically heated aluminum strips placed symmetrically about the leading edge stagnation region were used to measure spanwise-averaged heat transfer coefficients. The maximum Reynolds number obtained, based on leading edge diameter, was about 100,000. The model was immersed in the flow field downstream of an approximately half-scale model of a can-type combustor from a low NO(x), ground-based power-generating turbine. The tests were conducted with room temperature air; no fuel was added. Room air flowed into the combustor through six vane-type fuel/air swirlers. The combustor can contained no dilution holes. The fuel/air swirlers all swirled the incoming airflow in a counterclockwise direction (facing downstream). A five-hole probe flow field survey in the plane of the model stagnation point showed the flow was one big vortex with flow angles up to 36 deg at the outer edges of the rectangular test section. Hot-wire measurements showed test section flow had very high levels of turbulence, around 28.5%, and had a relatively large axial-length scale-to-leading edge diameter ratio of 0.5. X-wire measurements showed the turbulence to be nearly isotropic. Stagnation heat transfer augmentation over laminar levels was around 77% and was about 14% higher than predicted by a previously developed correlation for isotropic grid-generated turbulence.

VanFossen, G. James↗
DOE OSTI2024

Divertor-safe nonlinear burn control based on a SOLPS parameterized core-edge model for ITER

Abstract For ITER operations, the range of desirable burning-plasma regimes with high fusion power output will be restricted by various operational constraints. These constraints include the saturation of ITER’s various heating and fueling actuators such as the neutral beam injectors, the ion and electron cyclotron heating systems, the gas puffing system, and the deuterium–tritium pellet injectors. In addition to these actuator constraints, the H-mode power threshold, divertor detachment, and the heat load on the divertor targets may apply limitations to ITER’s operational space. In this work, Plasma Operation Contour (POPCON) plots that map the aforementioned constraints to the temperature-density space are used to investigate which constraints are most limiting towards accessing regimes with high fusion power output. The presented POPCON plots are based on a control-oriented core-edge model that couples the nonlinear density and energy response models for the core-plasma region with SOLPS4.3 parameterizations for conditions in the edge-plasma regions (scrape-off-layer and divertor). Using this control-oriented core-edge model, a nonlinear burn controller, which aims to regulate the plasma temperature and density in the core-plasma region, is constructed in this work. This controller is augmented with an online optimization scheme that governs the control references such that the plasma can be guided towards regimes with high fusion powers while protecting the divertor targets from dangerously high heat loads. A closed-loop simulation study illustrates the capability of this burn control scheme.

Physics↗
NASA NTRS1987

Thermal stresses and buckling of elastic plates with reinforced edges

An approximation method based on the method of Kantorovich is used to calculate the critical thickness necessary to prevent thermal buckling of a rectangular cantilever plate with edge stiffeners. The case where no external loads are applied is considered, and the only stresses are those due to the prescribed thermal profile. Stiffeners are found to play an important role in the thermal buckling by affecting the overall distribution of the in-plane stresses within the plate. Results show that edge stiffeners can cause less or more buckling, and that in most situations the edge stiffeners hinder buckling because a thicker plate is required than if the stiffeners were not present.

Ahmed, M.↗
DOE OSTI2016

A curved edge diffraction-utilized displacement sensor for spindle metrology

This paper presents a new dimensional metrological sensing principle for a curved surface based on curved edge diffraction. Spindle error measurement technology utilizes a cylindrical or spherical target artifact attached to the spindle with non-contact sensors, typically a capacitive sensor (CS) or an eddy current sensor, pointed at the artifact. However, these sensors are designed for flat surface measurement. Therefore, measuring a target with a curved surface causes error. This is due to electric fields behaving differently between a flat and curved surface than between two flat surfaces. In this study, a laser is positioned incident to the cylindrical surface of the spindle, and a photodetector collects the total field produced by the diffraction around the target surface. The proposed sensor was compared with a CS within a range of 500 μm. The discrepancy between the proposed sensor and CS was 0.017% of the full range. Its sensing performance showed a resolution of 14 nm and a drift of less than 10 nm for 7 min of operation. This sensor was also used to measure dynamic characteristics of the spindle system (natural frequency 181.8 Hz, damping ratio 0.042) and spindle runout (22.0 μm at 2000 rpm). The combined standard uncertainty was estimated as 85.9 nm under current experiment conditions. It is anticipated that this measurement technique allows for in situ health monitoring of a precision spindle system in an accurate, convenient, and low cost manner.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Two-Stage Wildlife Event Classification for Edge Deployment

Camera-based wildlife monitoring is often overwhelmed by non-target triggers and slowed by manual review or cloud-dependent inference, which can prevent timely intervention for high stakes human–wildlife conflicts. Our key contribution is a deployable, fully offline edge vision sensor that achieves near-real-time, highly accurate wildlife event classification by combining detector-based empty-image suppression with a lightweight classifier trained with a staged transfer-learning curriculum. Specifically, Stage 1 uses a pretrained You Only Look Once (YOLO)-family detector for permissive animal localization and empty-trigger suppression, and Stage 2 uses a lightweight EfficientNet-based binary classifier to confirm puma on detector crops and gate downstream actions. Our design is robust to low-quality nighttime monochrome imagery (motion blur, low contrast, illumination artifacts, and partial-body captures) and operates using commercially available components in connectivity-limited settings. In field deployments running since May 2025, end-to-end latency from camera trigger to action command is approximately 4 s. Ablation studies using a dataset of labeled wildlife images (pumas, not pumas) show that the two-stage approach substantially reduces false alarms in identifying pumas relative to a full-image classifier while maintaining high recall. On the held-out test set (N = 1434 events), the proposed two-stage cascade achieves precision 0.983, recall 0.975, F1 0.979, accuracy 0.986, and balanced accuracy 0.983, with only 8 false positives and 12 false negatives. The system can be easily adapted for other species, as demonstrated by rapid retraining of the second stage to classify ringtails. Downstream responses (e.g., notifications and optional audio/light outputs) provide flexible actuation capabilities that can be configured to support intervention.

58 GEOSCIENCES↗
DOE OSTI2016

A fluid model for the edge pressure pedestal height and width in tokamaks based on the transport constraint of particle, energy, and momentum balance

A fluid model for the tokamak edge pressure profile required by the conservation of particles, momentum and energy in the presence of specified heating and fueling sources and electromagnetic and geometric parameters has been developed. Kinetics effects of ion orbit loss are incorporated into the model. The use of this model as a “transport” constraint together with a “Peeling-Ballooning (P-B)” instability constraint to achieve a prediction of edge pressure pedestal heights and widths in future tokamaks is discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

A region-appearance-based adaptive variational model for 3D liver segmentation

Purpose: Liver segmentation from computed tomography images is a challenging task owing to pixel intensity overlapping, ambiguous edges, and complex backgrounds. The authors address this problem with a novel active surface scheme, which minimizes an energy functional combining both edge- and region-based information. Methods: In this semiautomatic method, the evolving surface is principally attracted to strong edges but is facilitated by the region-based information where edge information is missing. As avoiding oversegmentation is the primary challenge, the authors take into account multiple features and appearance context information. Discriminative cues, such as multilayer consecutiveness and local organ deformation are also implicitly incorporated. Case-specific intensity and appearance constraints are included to cope with the typically large appearance variations over multiple images. Spatially adaptive balancing weights are employed to handle the nonuniformity of image features. Results: Comparisons and validations on difficult cases showed that the authors’ model can effectively discriminate the liver from adhering background tissues. Boundaries weak in gradient or with no local evidence (e.g., small edge gaps or parts with similar intensity to the background) were delineated without additional user constraint. With an average surface distance of 0.9 mm and an average volume overlap of 93.9% on the MICCAI data set, the authors’ model outperformed most state-of-the-art methods. Validations on eight volumes with different initial conditions had segmentation score variances mostly less than unity. Conclusions: The proposed model can efficiently delineate ambiguous liver edges from complex tissue backgrounds with reproducibility. Quantitative validations and comparative results demonstrate the accuracy and efficacy of the model.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Classification and Localization of Fracture-Hit Events in Low-Frequency Distributed Acoustic Sensing Strain Rate with Convolutional Neural Networks

Summary Distributed acoustic sensing (DAS) has been used in the oil and gas industry as an advanced technology for surveillance and diagnostics. Operators use DAS to monitor hydraulic fracturing activities, examine well stimulation efficacy, and estimate complex fracture system geometries. Particularly, low-frequency DAS can detect geomechanical events such as fracture hits because hydraulic fractures propagate and create strain rate variations in the rock. Analysis of DAS data today is mostly done post-job and subject to interpretation methods. However, the continuous and dense data stream generated live by DAS poses the opportunity for more efficient and accurate real-time data-driven analysis. The objective of this study is to develop a machine learning-based workflow that can identify and locate fracture-hit events in simulated strain rate responses correlated with low-frequency DAS data. In this paper, “fracture hit” refers to a hydraulic fracture originating from a stimulated well intersecting an offset well. We start with building a single fracture propagation model to produce strain rate patterns observed at a hypothetical monitoring well. This model is used to generate two sets of strain rate responses with one set containing fracture-hit events. The labeled synthetic data are then used to train a custom convolutional neural network (CNN) model for identifying the presence of fracture-hit events. The same model is trained again for locating the event with the output layer of the model replaced with linear units. We achieved near-perfect predictions for both event classification and localization. These promising results prove the feasibility of using CNN for real-time event detection from fiber-optic sensing data. Additionally, we use edge detection techniques to recognize fracture-hit event patterns in strain rate images. The fracture-hit location can be identified using recognized pixels in the image. The accuracy of edge detection-based location identification is also plausible, but edge detection is dependent on the assumption of pattern shape and image quality, hence it is less robust compared to CNN models. This comparison further supports the need for CNN applications in image-based real-time fiber-optic sensing event detection.

Engineering↗