Remote Sensor Design for Visual Recognition With Convolutional Neural Networks
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In situ liquid cell transmission electron microscopy (LC-TEM) allows dynamic nanoscale characterization of systems in a hydrated state. Although powerful, this technique remains impaired by issues of repeatability that limit experimental fidelity and hinder the identification and control of some variables underlying observed dynamics. We detail new LC-TEM devices that improve experimental reproducibility by expanding available imaging area and providing a platform for investigating electron flux history on the sample. Irradiation history is an important factor influencing LC-TEM results that has, to this point, been largely qualitatively and not quantitatively described. We use these devices to highlight the role of cumulative electron flux history on samples from both nanoparticle growth and biological imaging experiments and demonstrate capture of time zero, low-dose images on beam-sensitive samples. In particular, the ability to capture pristine images of biological samples, where the acquired image is the first time that the cell experiences significant electron flux, allowed us to determine that nanoparticle movement compared to the cell membrane was a function of cell damage and therefore an artifact rather than visualizing cell dynamics in action. Lastly, these results highlight just a subset of the new science that is accessible with LC-TEM through the new multiwindow devices with patterned focusing aides.
A circular economy (CE) aims to decouple human activities from economic activities and resource use, and its overall goal is reducing or avoiding negative environmental externalities. The newly developed Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework simulates changes in supply chain environmental impacts as it transitions toward circularity. This study expands CELAVI by incorporating detailed spatial resolution and real-world road routes connecting all facilities within the system. The case study on end-of-life decision making of wind turbine blades in the states of Iowa and Missouri explores how supply chain circularity and environmental impacts are affected by pathway costs and level of wind turbine installations. It demonstrates how high circularity costs might be beneficial for circularity transitions given revenue generated from circular pathways. Finally, impacts have important contributions to the supply chain design and thus show the importance of including detailed spatial resolution in CELAVI and CE studies in general.
Nanoscale control of matter is critical to the design of integrated nanosystems. Here, we describe a method to dynamically control directionality of microtubule (MT) motion using programmable magnetic fields. MTs are combined with magnetic quantum dots (i.e., MagDots) that are manipulated by external magnetic fields provided by magnetic nanowires. MT shuttles thus undergo both ATP-driven and externally-directed motion with a fluorescence component that permits simultaneous visualization of shuttle motion. This technology is used to alter the trajectory of MTs in motion and to pin MT motion. Ultimately, such an approach could be used to evaluate the MT-kinesin transport system and could serve as the basis for improved lab-on-a-chip technologies based on MT transport.
EDGE bioinformatics was developed to help biologists process Next Generation Sequencing data (in the form of raw FASTQ files), even if they have little to no bioinformatics expertise. EDGE is a highly integrated and interactive web-based platform that is capable of running many of the standard analyses that biologists require for viral, bacterial/archaeal, and metagenomic samples. EDGE provides the following analytical workflows: quality trimming and host removal, assembly and annotation, comparisons against known references, taxonomy classification of reads and contigs, whole genome SNP-based phylogenetic analysis, and PCR analysis. EDGE provides an intuitive web-based interface for user input, allows users to visualize and interact with selected results (e.g. JBrowse genome browser), and generates a final detailed PDF report. Results in the form of tables, text files, graphic files, and PDFs can be downloaded. A user management system allows tracking of an individual’s EDGE runs, along with the ability to share, post publicly, delete, or archive their results.
This dataset includes earthquake catalogues for the three stages of the 2022 well 16A(78)-32 stimulation provided by Geo Energie Suisse. Events in these catalogues have been visually inspected. There are additional events of lower signal to noise that were automatically detected. Those events will require additional analysis and processing. Times are recorded in UTC (Coordinate Universal Time), and the coordinate reference system is UTM Zone 12N, NAD83.
Sandia researchers are developing analytic techniques that efficiently detect patterns in high-volume, noisy, remote sensing and other geospatial data, improving an analysts’ ability to detect possibly off-normal events in complex homeland security, nuclear weapons, and emerging threat environments. High-consequence, national security decisions rely on timely, comprehensive answers to complex questions, yet critical gaps in our approach to these questions remain. PANTHER addresses these gaps through fundamental research on: geospatial-temporal feature extraction via image segmentation and classification; geospatial-temporal graph algorithms and computational geometry; and domain-relevant models of human perception and cognition informing the design of analytic systems. PANTHER’s cross-disciplinary R&D approach uses fundamental science and mathematics to understand how to maximize decision systems through rethinking key aspects of geospatial data analysis. New methods in motion and trajectory analysis support both rapid search for known trajectories as well as rapid clustering and anomaly detection. Thus, the perceptual and visual load on users is reduced by providing pattern analytics with elegant visual cues to spatial and temporal characteristics.
This experimental plan defines crystal settling experiments to be in support of the U.S. Department of Energy – Office of River Protection crystal tolerant glass program. The road map for development of crystal-tolerant high level waste glasses recommends that fluid dynamic modeling be used to better understand the accumulation of crystals in the melter riser and mechanisms of removal. A full-scale version of the Hanford Waste Treatment and Immobilization Plant (WTP) melter riser constructed with transparent material will be used to provide data in support of model development. The system will also provide a platform to demonstrate mitigation or recovery strategies in off-normal events where crystal accumulation impedes melter operation. Test conditions and material properties will be chosen to provide results over a variety of parameters, which can be used to guide validation experiments with the Research Scale Melter at the Pacific Northwest National Laboratory, and that will ultimately lead to the development of a process control strategy for the full scale WTP melter. The experiments described in this plan are divided into two phases. Bench scale tests will be used in Phase 1 (using the appropriate solid and fluid simulants to represent molten glass and spinel crystals) to verify the detection methods and analytical measurements prior to their use in a larger scale system. In Phase 2, a full scale, room temperature mockup of the WTP melter riser will be fabricated. The mockup will provide dynamic measurements of flow conditions, including resistance to pouring, as well as allow visual observation of crystal accumulation behavior.
The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) Morgantown, West Virginia site were used to characterize core of the Marcellus Shale from a vertical well, the Coldstream 1MH Well in Clearfield County, PA. The core is comprised primarily of the Marcellus Shale from a depth of 7,002 to 7,176 ft. The primary impetus of this work is a collaboration between West Virginia University (WVU) and NETL to characterize core from multiple wells to better understand the structure and variation of the Marcellus and Utica shale formations. As part of this effort, bulk scans of core were obtained from the Coldstream 1MH well, provided by the Energy Corporation of America (now Greylock Energy). This report, and the associated scans, provide detailed datasets not typically available from unconventional shales for analysis. The resultant datasets are presented in this report, and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/coldstream-1mh-well. All equipment and techniques used were non-destructive, enabling future examinations to be performed on these cores. None of the equipment used was suitable for direct visualization of the shale pore space, although fractures and discontinuities were detectable with the methods tested. Low resolution CT imagery with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with x-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for more detailed analysis as well as fractured zones. En echelon fractures were observed at 7,100 ft and were CT scanned using NETL’s industrial CT scanner at higher resolution. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provided a multi-scale analysis of this core and provides both a macro and micro description of the core that is relevant for many subsurface energy-related examinations that have traditionally been performed at NETL.
The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) Morgantown, West Virginia site were used to characterize core of the Marcellus Formation from a vertical well drilled in Greene County, Pennsylvania by the Energy Corporation of America. The core is from the Whipkey ST 1 well, in the Carmichaels Field, and is comprised primarily of the Marcellus Formation from depths of 7,719 to 7,910.8 ft. Core was provided by Tim Carr and Keithan Martin (West Virginia University and ORISE). The primary impetus of this work is a collaboration between West Virginia University (WVU) and NETL to characterize core from multiple wells to better understand the structure and variation of the Marcellus and Utica Shale Formations. As part of this effort, bulk scans of core were obtained from the Whipkey ST 1 well. This report, and the associated scans, provide detailed datasets not typically available from unconventional shales for analysis. The resultant datasets are presented in this report, and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/whipkey-well. All equipment and techniques used were non-destructive, enabling future examinations to be performed on these cores. None of the equipment used was suitable for direct visualization of the shale pore space, although fractures and discontinuities were detectable with the methods tested. Low resolution CT imagery with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for more detailed analysis as well as fractured zones. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provided a multi-scale analysis of this core and provided both a macro and micro description of the core that is relevant for many subsurface energy related examinations that have traditionally been performed at NETL.
The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) Morgantown, West Virginia site were used to characterize a core from the Rogersville Shale. This sample was taken from a vertical well, the Jay P. Smith #1 well (47-099-1572), drilled in Wayne County, West Virginia by the Exxon Company in the Elmwood Prospect. The core is comprised primarily of the Rogersville Shale from depths of 11,135 to 11,200.5 ft. This unit is a potential Cambrian oil/gas target, making it of recent interest to multiple groups. The core was provided by the West Virginia Geologic and Economic Survey (WVGES). The primary impetus of this work is a collaboration between WVGES and NETL to characterize core from multiple wells to better understand the structure and variation of key formations in West Virginia (e.g. Crandall et al., 2018a,b). As part of this effort, bulk scans of core were obtained from the Smith #1 well. This report, and the associated scans, provide detailed datasets not typically available from unconventional shales for analysis. The resultant datasets are presented in this report, and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/roger-well. All equipment and techniques used were non-destructive, enabling future examinations to be performed on these cores. None of the equipment used was suitable for direct visualization of the shale pore space, although fractures and discontinuities were detectable with the methods tested. Low resolution CT imagery with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for more detailed analysis as well as fractured zones. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provided a multi-scale analysis of this core and provides both a macro and micro description of the core that is relevant for many subsurface energy-related examinations that have traditionally been performed at NETL.
This test report provides the results of radiation tolerance robustness testing that was performed on samples of robotic components and an ultrasonic guided wave air-slot sensor that represent components/sub-systems of the Robotic Air-slot Volumetric Inspection System (RAVIS) that has been engineered for volumetric inspection of Hanford tank bottom plates via under-tank refractory pad air-slots. The specific components tested for 1) functionality during active irradiation and 2) tolerance to cumulative radiation dose (until failure or upon reaching a cumulative dose test limit) were: • four samples each of a printed circuit board (PCB) and direct current (DC) motor, which are robotic components, and • 26 ultrasonic piezoelectric elements (samples) inside an air-slot sensor. The robotic components are part of the RAVIS air-slot inspection crawler drive control system that is responsible for remote communication with and actuation of the air-slot inspection crawler. The failure of either of these components during under-tank deployment would require manual retrieval via the crawler’s tether, which risks damage to the robot/refractory/tank. Preemptive replacement of the components at appropriately conservative dose/time intervals informed by failure dose would reduce the likelihood of under-tank failure. The components were included in radiation tolerance testing to quantify their failure doses to inform replacement intervals. The air-slot sensor is responsible for collecting ultrasonic inspection data (scan images) for the tank bottom plates during under-tank deployment. Compromised signal quality due to elevated noise levels caused by gamma radiation would compromise inspection performance. The air-slot sensor was included in radiation tolerance testing to quantify the impact of active irradiation on sensor signal quality. The irradiation and in-situ functional tests of the PCBs, DC motors and air-slot sensor took place in June and July 2020 at the Pacific Northwest National Laboratory. Testing was performed at a gamma dose rate near 300 rad/hr., which, in the absence of under-tank dose rate data, has been conservatively estimated to be the upper-bound dose rate beneath the primary tanks at Hanford. Irradiation took place at elevated temperatures of 150-200°F to determine failure doses that reflect the compounding effects of gamma radiation and heat. The test results revealed: • The DC motors can tolerate being actively irradiated at the high dose rate at 200°F and can tolerate a cumulative dose of 300,000 rad, that which would be incurred after 5 years of service at the 300 rad/hr dose rate. The component therefore meets minimum and preferred radiation tolerance and lifecycle requirements for robotic components. • The air-slot sensor can tolerate being actively irradiated at the high dose rate at 150°F and can tolerate a cumulative dose of 60,000 rad, that which would be incurred after 1 year of service at the 300 rad/hr dose rate. The sensor therefore meets minimum radiation tolerance and lifecycle requirements. • The PCB can tolerate being actively irradiated at the high dose rate, but can only tolerate a cumulative dose of 19,000 rad at 150-200°F. The PCB does not meet minimum radiation tolerance and lifecycle requirements; however, because the component is considered replaceable, it can be replaced before a cumulative dose of 19,000 rad is reached, determined through either monitoring with a dosimeter or scheduled time intervals that are calculated based on conservative estimates of under-tank dose rates.
This project sets up a website to support the nascent Muon Catalyzed Fusion collaboration including development of particle accelerators and transport beamlines for muon beams. The website is envisioned as having the general public information pages and private pages for collaboration members. Multimedia elements like images, text animations, and video lectures, covering a broad spectrum of topics will populate the educational site, covering muon facilities, to comprehensive explorations and seminal documents that define the science of Muon Catalyzed Fusion, Acceleration, Applications, Instrumentation, Beamline Design, and beam dynamics design codes. Ensuring compatibility across devices and operating systems, it also features integration with Google Docs for collaboration, a code repository (GitHub), a blog platform with comments (WordPress), the potential for ChatGPT integration and interactive graph plotting with Python Plotty to enhance data visualization. This project will maintain public and protected private pages, due to the proprietary nature of the work or research in progress. The public sections will be built to foster dissemination of information and highlight recent work within the NK Labs collaboration, including lectures, published papers, and regular blog posts with open commenting. The private section will support unpublished or nonpublic research, by facilitating collaborative efforts through integrated Google Docs and Python Plotty for shared graphing work. Ultimately, this project strives to make complex scientific knowledge more accessible to the public, foster enhanced collaboration, and serve as a platform for sharing cutting-edge research in Muon Catalyzed Fusion and Accelerators.
The control room functions as the central brain of the grid, essential for balancing supply and demand and ensuring moment-to-moment grid reliability. Like the human brain, which processes sensory data to make decisions, control room operators analyze operational data from power generation, transmission, and distribution to make informed decisions. Currently, decision-making primarily rests with operators due to hardware and software limitations. However, with technological advancements, Digital Twins and AI are becoming high interest points in the control room's decision-making pilot programs. NREL is developing a comprehensive decision-making platform that integrates Digital Twins, AI, and advanced visualization techniques. As this integration progresses, the role of Digital Twins will evolve from conducting automated simulations to serving as a Trustworthy AI enabler, offering verification and validation of AI-generated response for power systems or providing physics-aware synthetic data of AI pre-training.
We investigate the intrinsic abundance ratio of {sup 13}CO to C{sup 18}O and the X-factor in L 1551 using the Nobeyama Radio Observatory (NRO) 45 m telescope. L 1551 is chosen because it is relatively isolated in the Taurus molecular cloud shielded from FUV photons, providing an ideal environment for studying the target properties. Our observations cover ∼40{sup ′}×40{sup ′} with a resolution of ∼30{sup ′′}, which make up maps with the highest spatial dynamical range to date. We derive the X{sub {sup 1}{sup 3}CO}/X{sub C{sup 1}{sup 8}O} value on the sub-parsec scales in the range of ∼3–27 with a mean value of 8.0 ± 2.8. Comparing to the visual extinction map derived from the Herschel observations, we found that the abundance ratio reaches its maximum at low A{sub V} (i.e., A{sub V} ∼ 1–4 mag), and decreases to the typical solar system value of 5.5 inside L 1551 MC. The high X{sub {sup 1}{sup 3}CO}/X{sub C{sup 1}{sup 8}O} value at the boundary of the cloud is most likely due to the selective FUV photodissociation of C{sup 18}O. This is in contrast with Orion-A where internal OB stars keep the abundance ratio at a high level, greater than ∼10. In addition, we explore the variation of the X-factor, because it is an uncertain, but widely used, quantity in extragalactic studies. We found that the X-factor ∝N{sub H{sub 2}{sup 1.0}}, which is consistent with previous simulations. Excluding the high density region, the average X-factor is similar to the Milky Way average value.
We conduct a search for strong gravitational lenses in the Dark Energy Survey (DES) Year 6 imaging data. We implement a pre-trained Vision Transformer (ViT) for our machine learning (ML) architecture and adopt interactive machine learning to construct a training sample with multiple classes to address common types of false positives. Our ML model reduces ∼236 million DES cutout images to 22,564 targets of interest, including ∼85% of previously reported galaxy–galaxy lens candidates discovered in DES. These targets were visually inspected by citizen scientists, who ruled out ∼90% as false positives. Of the remaining 2618 candidates, 149 were expert-classified as “definite” lenses and 516 as “probable” lenses, for a total of 665 systems, with 147 of these candidates being newly identified. Additionally, we trained a second ViT to find double-source plane lens systems, finding at least one double-source system. Our main ViT excels at identifying galaxy–galaxy lenses, consistently assigning high scores to candidates with high expert assessments. The top 800 ViT-scored images include ∼100 of our “definite” lens candidates. This selection is an order of magnitude higher in purity than previous convolutional neural-network-based lens searches and demonstrates the feasibility of applying our methodology for discovering large samples of lenses in future surveys.
EDGE bioinformatics was developed to help biologists process Next Generation Sequencing data (in the form of raw FASTQ files), even if they have little to no bioinformatics expertise. EDGE is a highly integrated and interactive web-based platform that is capable of running many of the standard analyses that biologists require for viral, bacterial/archaeal, and metagenomic samples. EDGE provides the following analytical workflows: quality trimming and host removal, assembly and annotation, comparisons against known references, taxonomy classification of reads and contigs, whole genome SNP-based phylogenetic analysis, and PCR analysis. EDGE provides an intuitive web-based interface for user input, allows users to visualize and interact with selected results (e.g. JBrowse genome browser), and generates a final detailed PDF report. Results in the form of tables, text files, graphic files, and PDFs can be downloaded. A user management system allows tracking of an individual’s EDGE runs, along with the ability to share, post publicly, delete, or archive their results.
A circular economy (CE) aims to decouple human activities from economic growth and resource use, and its overall goal is reducing or avoiding negative environmental externalities. The newly developed Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework simulates changes in supply chain environmental impacts as it transitions toward circularity. This study expands CELAVI by incorporating detailed spatial resolution and real-world road routes connecting all facilities within the system. The case study on end-of-life decision making of wind turbine blades in the states of Iowa and Missouri explores how supply chain circularity and environmental impacts are affected by pathway costs and level of wind turbine installations. It demonstrates how high circularity costs might be beneficial for circularity transitions given revenue generated from circular pathways. Finally, impacts have important contributions to the supply chain design and thus show the importance of including detailed spatial resolution in CELAVI and CE studies in general.