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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Monitoring pipeline integrity of underground gas storage facilities using membrane-based electrochemical sensors

Effective monitoring of internal corrosion risk is crucial to ensuring the safety and longevity of natural gas pipeline infrastructure. While electrochemical sensors are commonly used to assess corrosion rates and corrosion indicators in aqueous fluids, they are rarely used in gas pipelines as these fluids lack the ionic conductivity needed for electrochemical measurements. The inclusion of ion-conductive membranes into electrochemical sensors can extend their functionality into humidified gas streams, providing critical information about emerging corrosion events that are common during withdrawal season in pipeline systems downstream from underground storage facilities. In parallel, new protective films, like those obtained through cold spray coating, are being developed to protect oil and gas pipelines and recover losses in structural integrity due to corrosion damage. Herein, we demonstrate how membrane-based electrochemical sensors (MBES) can be used to monitor fluid corrosivity by examining their response to changes in water content for a wide range of fluid compositions. It was found that MBES readings were highly sensitive to water content changes with membrane conductivity measurements varying from 10 –6 to 10 –1 S cm -1 , and corrosion rate measurements which varied from 10 –7 to 1 mm y -1 . Electron microscopy confirmed that the self-healing characteristics of metal coating films were still active despite their inclusion into an MBES probe. In conclusion, these findings indicate that membrane-based corrosion monitoring can be expanded to monitor coated-pipeline materials and provide early detection of emerging corrosion upsets relevant to underground gas storage facilities.

Electrochemical sensor↗
DOE OSTI2021

Monitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies

Tropical leaf phenology-particularly its variability at the tree-crown scale-dominates the seasonality of carbon and water fluxes. However, given enormous species diversity, accurate means of monitoring leaf phenology in tropical forests is still lacking. Time series of the Green Chromatic Coordinate (GCC) metric derived from tower-based red-green-blue (RGB) phenocams have been widely used to monitor leaf phenology in temperate forests, but its application in the tropics remains problematic. To improve monitoring of tropical phenology, we explored the use of a deep learning model (i.e. superpixel-based Residual Networks 50, SP-ResNet50) to automatically differentiate leaves from non-leaves in phenocam images and to derive leaf fraction at the tree-crown scale. To evaluate our model, we used a year of data from six phenocams in two contrasting forests in Panama. Here, we first built a comprehensive library of leaf and non-leaf pixels across various acquisition times, exposure conditions and specific phenocams. We then divided this library into training and testing components. We evaluated the model at three levels: 1) superpixel level with a testing set, 2) crown level by comparing the model-derived leaf fractions with those derived using image-specific supervised classification, and 3) temporally using all daily images to assess the diurnal stability of the model-derived leaf fraction. Finally, we compared the model-derived leaf fraction phenology with leaf phenology derived from GCC. Our results show that: 1) the SP-ResNet50 model accurately differentiates leaves from non-leaves (overall accuracy of 93%) and is robust across all three levels of evaluations; 2) the model accurately quantifies leaf fraction phenology across tree-crowns and forest ecosystems; and 3) the combined use of leaf fraction and GCC helps infer the timing of leaf emergence, maturation and senescence, critical information for modeling photosynthetic seasonality of tropical forests. Collectively, this study offers an improved means for automated tropical phenology monitoring using phenocams.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Projected network performance for next generation aerosol monitoring systems

Aerosol monitoring for radioactivity is a mature and proven technology. However, by improving key specifications of aerosol monitoring equipment, more samples per day can be collected and analyzed with the same minimum detectable concentrations as current systems. This work models hypothetical releases of 140 Ba and 131 I over a range of magnitudes corresponding to the inventory produced from the fission of about 100 g to 1 kiloton TNT-equivalent of 235 U. The releases occur over an entire year to incorporate the natural variability in atmospheric transport. Sampling equipment located at the 79 locations for radionuclide stations identified in the Comprehensive Nuclear-Test-Ban Treaty (CTBT) for the International Monitoring System are used to determine the detections of the individual releases. Alternative collection schemes in next generation equipment that collect 2, 3, or 4 samples per day, rather than the current 1 sample per day, would result in detections in many more samples at more stations with detections for a given release level. The authors posit that next generation equipment will result in increased network resilience to outages and improved source-location capability for lower yield source releases. The application of dual-detector and coincidence measurements to these systems would significantly boost sensitivity for some isotopes and would further enhance the monitoring capability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Hydra: An AI-Based Framework for Interpretable and Portable Data Quality Monitoring

Hydra is an advanced framework designed for training and managing AI models for near real time data quality monitoring at Jefferson Lab. Deployed in all four experimental halls, Hydra has analyzed over 2 million images and has extended its capabilities to offline monitoring and validation. Hydra utilizes computer vision to continually analyze sets of images of monitoring plots generated 24/7 during experiments. Generally, these sets of images are produced at a rate and quantity that is exceedingly difficult for shift crews to effectively monitor. Significant effort has been devoted to enhancing Hydra’s user interface, to ensure that it provides clear, actionable insights for shift workers and other users. Gradient Weighted Class Activation Maps (GradCAM) provide added interpretability, allowing users to visualize important regions of the image for classification. Hydra has been containerized to enable the creation of portable demos and seamless integration with container-based technologies such as Kubernetes and Docker. With the user interface enhancements and containerization, Hydra can be rapidly deployed for new use cases and experiments. This talk will describe the Hydra framework, its user interface and experience, and the challenges inherent in its design and deployment.

Britton, Thomas [Thomas Jefferson National Acceler↗
DOE OSTI2022

Computer Vision-Enabled Smart Traffic Monitoring for Sustainable Transportation Management

Transportation accounts for a significant portion of total global energy consumption. Excessive energy consumption usually occurs in urban traffic environments with congestion and travel delays. With the advancement of remote sensing and computer vision technologies, real-time traffic conditions can be monitored. Therefore, sustainable transportation management strategies can be developed to optimize the overall energy and environment performance and reduce congestion and emissions. This work presents a smart traffic monitoring system based on remote camera sensors. Real-time and historical traffic conditions at the US Department of Energy’s Oak Ridge National Laboratory (ORNL) were monitored and analyzed to develop optimal transportation management strategies for sustainability. Computer vision algorithms were developed and applied to process the real-time camera data to obtain complete traffic information across the ORNL campus. Weeks of historical data were collected and processed to analyze the traffic and identify bottlenecks. The proposed traffic monitoring and management approach can be applied and extended to benefit other campuses or urban areas.

Shao, Yunli↗
DOE OSTI2020

In situ laser reflectivity to monitor and control the nucleation and growth of atomically thin 2D materials*

The growth of atomically thin two-dimensional (2D) layered and other quantum materials is typically performed without in situ monitoring or control. Here, a simple laser reflectivity approach is demonstrated to provide in situ control over sub-monolayer thickness and growth kinetics during pulsed laser deposition (PLD) of MoSe 2 layers. First, the general technique is presented with emphasis on designing the maximum sensitivity of the optical contrast through consideration of Fresnel's equations with proper choice of layer thickness, substrate, and laser monitoring wavelength, incidence angle, and laser polarization. Then the 632.8 nm optical reflectivity of MoSe 2 layers on SiO 2 /Si substrates was predicted and compared with in situ monitoring of MoSe 2 growth by PLD under actual growth conditions using a probe HeNe laser beam. The measurements showed high sensitivity and excellent agreement with MoSe 2 surface coverages calculated from atomic resolution STEM analysis of 2D layers deposited in arrested growth experiments. Finally, growth kinetics revealed by these measurements showed sigmoidal nucleation and growth stages in the formation of the 2D MoSe 2 layers that are described by a simple model, indicating the promise of the laser reflectivity technique for in situ monitoring and control of 2D materials deposition.

2D materials↗
DOE OSTI2020

Detection of very-high-energy gamma-ray transients with monitoring facilities

ABSTRACT The observation of very-high-energy γ-rays (VHE γ-rays, $E \gt 100\,$ GeV) has ledto the identification of extremely energetic processes and particle-acceleration sites both within our Galaxy and beyond. It is expected that VHE facilities, such as the Cherenkov Telescope Array, will explore these sources with an unprecedented level of detail. However, the transient and unpredictable nature of many important processes means that their observation requires the development of proper monitoring strategies. In this study, we estimate the properties of VHE transients that can be effectively detected by monitoring facilities. We use data collected by the Fermi-LAT instrument during its monitoring campaign to select events that are probably associated with VHE emission. We use this sample to estimate the frequency, the luminosity and the time-scales of various transients, focusing on blazar flares and gamma-ray bursts. We discuss how the balance between the field of view, sensitivity and duty cycle of an observatory affects the likelihood of detecting transients that occur at the inferred rates, and we conclude by describing the contribution that current and near-future monitoring facilities can make to the identification and study of VHE transient emission.

La Mura, G.↗
DOE OSTI2021

Slow control and monitoring system at the JSNS 2

The Sterile Neutrino Search at the J-PARC Spallation Neutron Source (JSNS$^2$) experiment aims to search for sterile neutrino oscillations using a neutrino beam from muon decays at rest. The JSNS$^2$ detector contains 17 tons of 0.1$\%$ gadolinium (Gd) loaded liquid scintillator (LS) as a neutrino target. Detector construction was completed in the spring of 2020. A slow control and monitoring system (SCMS) was implemented for reliable control and quick monitoring of the detector operational status and environmental conditions. It issues an alarm if any of the monitored parameters exceed a preset acceptable range. The SCMS monitors the high voltage of the photomultiplier tubes, the LS level in the detector, possible LS overflow and leakage, the temperature and air pressure in the detector, the humidity of the experimental hall, and the LS flow rate during filling and extraction. An initial 10 days of data-taking with a neutrino beam was done following a successful commissioning of the detector and SCMS in 2020 June. In this paper, we present a description of the assembly and installation of the SCMS and its performance.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

ROAM: A Remotely Operated Accelerator Monitor

Monitoring accelerators in operation is a well known challenge due to the radiation environment. However, there are significant benefits in being able to deploy particular sensors in specific locations of accelerator enclosures for monitoring or troubleshooting purposes. Learning from experience at other labs, we used Commercial Off The Shelf (COTS) components and an open source robot control software framework (ROS) to build a remotely controlled robot platform including a standard suite of instruments such as cameras, LIDAR, and ultrasound, with the ability to incorporate other ad-hoc sensors for specific measurements, such as a Gamma radiation monitor. Special attention was given to the robot's ability to maintain safety in the high risk environment of an accelerator, with multiple failure contingencies in place to ensure collision free operation. Testing was performed to prove the platform's viability and showcase its capability for accelerator monitoring.

Thayer, Thomas C.↗
DOE OSTI2025

Groundwater elevation data for monitoring wells within the East and Taylor River basins, Colorado (USA)

This dataset is comprised of temporal variations in groundwater elevation data for the 24 monitoring wells located throughout the East River watershed. Seasonal to annual variations in groundwater elevations are a critical property of mountainous watersheds needed to understand both hydrological and below ground biogeochemical processes. Such data serve as a critical constraint for numerical models describing coupled groundwater-surface water behavior within the watershed. Additionally, the offset between the maximum and minimum groundwater elevations defines the extent of the bedrock weathering zone, with annual excursions in the groundwater hydrographic (i.e., the rising and falling hydrographic limbs) imposing primary controls on bedrock saturation state and redox conditions that govern biogeochemical reactions impacting nitrogen, carbon, and metals cycling. Manufacturer-specific software is used to download pressure data from each transducer, with broadly available spreadsheet software (e.g. Microsoft Excel) used to convert temporal variations in water pressure to elevations in units of meters above mean sea level. As additional monitoring wells are installed within the East River watershed and new groundwater monitoring wells are installed in the Taylor River watershed, temporal groundwater elevation data will be included as a part of this master dataset. Details regarding the metadata associated with each monitoring well location, including well depths, screened intervals, well location coordinates, and bedrock type, are included, as is a standard operating procedure for generating groundwater elevation data from water pressure values recorded by the pressure transducers. This dataset includes: (1) a zip file (East_River_Watershed_Compiled_Groundwater_Elevation_Data_Plots.zip), containing (a) PNG of groundwater hydrographs, (b) a CSV file with groundwater elevation data, and (c) CSV file containing metadata organized by location; (2) an Excel file (East_River_Watershed_Compiled_Groundwater_Elevation_Data_Plots.xlsx) with the groundwater elevation data, groundwater hydrographs, and metadata organized by location; (3) a Word file (Groundwater_elevation_data_protocols.docx) and a PDF file version (Groundwater_elevation_data_protocols.pdf) containing field protocols and methods; (4) a location metadata (locations.csv) file; (5) a file level metadata (flmd.csv); and (6) data dictionary (dd.csv) file.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Pressurized Gas Beam Monitor for Extremely High Intensities – Phase II

A novel pressurized gas-filled multi-RF-cavity beam profile monitor has been studied that is simple and robust in high-radiation environments. Charged particles passing through each RF-cavity in the monitor produce intensity-dependent ionized plasma, which changes the gas permittivity. Standard RF techniques to measure the change in quality factor (Q) and frequency (f) as a function of time are then used to determine the change in permittivity and corresponding beam intensity in each cavity in the profile monitor. The sensitivity to beam intensity is adjustable using gas pressure and RF gradient. The performance of the gas-filled beam profile monitor has been numerically simulated to evaluate the sensitivity of permittivity measurements and the effectiveness of calibration strategies. An entire multi-RF-cavity system has been designed and a demonstration test has been prepared.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Virtual Metering for Monitoring Building Energy Consumption

The United States Department of Energy (DOE) has standard metering requirements of commercial buildings for optimizing energy performance. The guiding principles are to continuously track and optimize energy performance and install building-level meters for electricity, natural gas, and steam. Some buildings at Los Alamos National Laboratory (LANL) have physical submeters monitoring their energy consumption, but these meters have proven to be unreliable. And, in most cases, replacing them has proven to be a slow process. Installing new submeters also requires a temporary lockout of the circuit on which they are being installed. Many buildings at LANL contain laboratories with ongoing experiments or data centers, which makes an equipment power outage nearly impossible to plan. This inability to plan power outages results in long-term submeter failures. Although most submeters are eventually replaced, failures lead to missing consumption data for some unpredictable, extended time. A building automation system (BAS) is a system that provides control and monitoring on a building to maintain the operational performance of the building and occupancy comfort. Many buildings at LANL currently have a BAS, and all new renovations and installs will include installing a BAS if one does not already exist. The intended purpose for a BAS is primarily to monitor the health and efficiency of a building; however, it is also possible to calculate equipment power and energy consumption using BAS information. This project aims to use virtual meters to monitor building energy consumption as a cost-effective and minimally labor-intensive alternative to installing physical submeters. The fault detection and diagnostics tool, SkySpark, provides a centralized database for all the data from the various BAS that are active at LANL. This data includes the information that is needed to create virtual meters for heating, ventilating, and air conditioning (HVAC) systems in most buildings, including heating and cooling loads. 9 This report begins with a detailed summary of the project, including the reasoning, procedure, and results. The specific processes of creating the various virtual meters are then identified. Then the limitations are discussed. And, lastly, the results and future potential are presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Battery Monitoring System

The component that is powered by the battery pack being monitored is a valuable asset and must be in working condition at all times. Battery chemistry and characteristics have a major role in how to evaluate the state of the battery. The battery monitoring system has many parts that lead to an accurate battery reading. The components consist of a coulomb counting device, end of life voltage detection, a consideration of use for a real-time clock (RTC), temperature sensor, and non-volatile random-access memory (NVRAM). The combination of these elements allows the monitoring system to be highly reliant. Moving forward a better implementation of the ideas in this paper and further testing should ensure a high-quality battery monitoring system.

25 ENERGY STORAGE↗
DOE OSTI2020

Continuous Monitoring and Partial Water Softening for Cooling Tower Water Treatment

Cooling towers are an integral component of many refrigeration systems, providing comfort or process cooling across a broad range of applications. They are the point in the system where heat is dissipated to the atmosphere through the evaporative cooling process. Cooling towers are commonly found in industrial applications and are also often used in water-cooled chilled water plants in medium to large commercial buildings. Continuous monitoring and partial water softening for cooling towers used in medium to large commercial buildings are the focus of this paper. Cooling towers consume large amounts of water. Cooling tower-related water consumption is one of largest potable water loads within buildings in the United States, with substantial building water use associated with heating and cooling. Regional water shortages have highlighted a need to reduce water consumption; the U.S. General Services Administration (GSA) and Executive Order 13834 place priority on reducing water consumption. This priority has fueled interest in the identification, investigation, and potential broad deployment of cost-effective opportunities to reduce water use, such as alternative water treatment (AWT) technologies for cooling towers. Traditional water treatment approaches use chemicals to extend the ability of the water to hold scaling minerals in suspension, minimize corrosion, and prevent biological growth. This treatment protects the chillers and cooling tower equipment; however, even when chemicals are used regularly, a certain percentage of condenser water must be drained and made up with fresh water to maintain system water quality parameters. In addition, the use of chemicals sometimes creates a waste disposal issue and can cause building owners to incur additional fees, such as disposal or wastewater charges. To manage cooling tower water treatment, GSA typically contracts with a company specializing in conventional chemical maintenance for a fixed fee. While there are many types and vendors of AWT systems, this project assesses the effectiveness of one technology provided by Aqualogix. This system is a chilled water plant monitoring and control system aimed at optimizing system performance by reducing the blowdown occurrences used to remove mineral build-up. The technology consists of two components – continuous programmable logic control (PLC) monitoring and side-stream filtration with partial water softening. PLC monitoring calculates cycles of concentration (CoC) and determines the optimum amount of blowdown water required to satisfy all water chemistry requirements. Side-stream filtration removes suspended matter and improves biocide efficacy while precisely dispensing softened water to achieve optimal makeup water hardness. Unlike other AWT systems evaluated by GSA to date, this system does not replace the legacy treatment system but is used in addition to chemical water treatment. The vendor claims their technology will reduce water consumption, water discharge, and maintenance costs. The AWT system evaluated in this demonstration is a commercialized technology. Given its commercialized state, the system evaluated in this report is at a Technology Readiness Level 9 according to National Aeronautics and Space Administration (NASA) definitions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Development of a Beam Halo Monitor

Muons, Inc. proposed improved Residual-Gas luminescent Beam Profile Monitors for Intense Beams by adding novel features including a mirascope, a light collecting device devised in the 16th century by an inventor of the telescope. A modern mirascope consists of 2 paraboloids. Light generated by the beam is collected by the paraboloids and creates a beam image. By placing a lens near the image it is possible to collect almost 100% of the emitted light, up to ten times better than existing fluorescence profilometers. Intense (multi-MW) proton beams pose a challenge for beam profile measurements. Solid-based beam intercepting instrumentation produces unallowable levels of radiation at these high powers. An alternative is to use a zero-or-low mass device such as a residual-gas profile monitor, either through collection of ionization or fluorescence. Fluorescence has an intrinsic advantage over the usual collection of ionized electrons in that it is not affected by the strong and variable electric and magnetic fields created by the beam that can distort profiles and make calibration difficult. For this reason, we proposed the fluorescence technique using the mirascope and other methods to enhance light collection and versatility by modifying the residual gas and its spatial distribution. In Phase I, we designed a mirascope and its electronics for commissioning and beam tests in a proposed Phase II. The design was based on optical simulations done in Phase I, and a physics run plan was developed for optimizing and testing. The Phase II experimental site and program have been planned and our goal is to produce a universal low cost Mirascope Residual-Gas Luminescent Beam Profile Monitor that can replace all other profile monitors currently used in accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Charged Wellbore Casing Controlled Source Electromagnetics (CWC-CSEM) for Reservoir Imaging and Monitoring (Final report)

This project addresses the needs of the U.S. Department of Energy (DOE) to develop advanced monitoring technologies and protocols to track the fate of subsurface carbon dioxide (CO2) plumes for carbon storage. Specifically, the project seeks to develop and test a unique and novel system of technologies consisting of electromagnetic data acquisition, coupled multiphysics imaging, and reservoir model enhancement to understand the migration and long-term distribution of CO2 in the subsurface. The overarching objective is to develop an integrated approach for long term monitoring of carbon storage. The two main components of the project include the methodology development and the test of the method at a field site. The methodology component consists of 1) developing the field procedure and protocol for collecting time-lapse controlled-source electromagnetic (CSEM) data with source electric current injected into the subsurface through wellbore casings; 2) building of background 3D electrical conductivity utilizing multiple sources of data such as supplemental surface transient EM (TEM) surveys, well-logs, and seismic structural information, for enhancing CSEM signal from reservoir depths; and 3) coupled multiphysics simulations and inversion of CSEM data constrained by production data and by structural information from seismic imaging of the reservoir and overlying formations. The testing component used the field site of Bell Creek Oil Field, which served both as a field laboratory for the method development as well as a test site to evaluate the CSEM signal strengths and the methodology developed in this research project. We have accomplished all the proposed tasks and developed the methodology as planned. These include the procedure for time-lapse CSEM data acquisition, data processing techniques, integration with 3D conductivity model building, fast reservoir simulation for history matching using machine learning, and interpreting CSEM data with coupling to the reservoir modeling. Collectively, the outcome of these tasks form a coherent workflow that can be applied to monitor dedicated carbon storage in saline reservoirs. The testing component evaluated the applicability and limitations of the method, and concluded that the method would be ideal for monitoring dedicated carbon storage sites utilizing saline reservoirs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Detection Thresholds and Sensitivities of Geophysical Techniques for CO2 Plume Monitoring

This report assesses capabilities and limitations of different geophysical techniques for monitoring geologic sequestration of CO 2 . Seismic, gravity, electrical, and electromagnetic (EM) techniques are considered. Monitoring approaches for site characterization prior to CO 2 injection are different from those used while injecting CO 2 , or those suitable for post-injection monitoring. The focus of this study is on the aspects relevant to long-term monitoring of large areas in the post-injection phase, and specifically on early detection of secondary CO 2 plumes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Monitoring Radiochemical Processing Streams for the 238 Pu Supply Program with Process Pulse II

Oak Ridge National Laboratory (ORNL) is developing advanced spectroscopic and real-time monitoring capabilities to improve the timeliness of analytical measurements and process decisions for the 238Pu Supply Program. Reducing the time, resources, and costs associated with each production campaign is critical because overlapping campaigns will be required to meet the production goals of the National Aeronautics and Space Administration. Real-time, in situ analytical measurements in the heavily shielded hot cells at the Radiochemical Engineering Development Center (REDC) will allow for rapid process information feedback and operational benefits that help the 238Pu supply program scale-up production efforts. Noteworthy steps were taken during Campaign 5 to establish the ability to monitor processing streams in real time with spectrophotometry and a commercially available online monitoring software called The Unscrambler X Process Pulse II (PP) multivariate statistical process monitoring system by Camo Analytics (version 5.60). PP automates univariate-type calculations within the software itself and executes multivariate models built using The Unscrambler X (version 10.4 or newer). The Unscrambler is a commercially available data analysis software made by the same company. PP is composed of easy-to-use-tools for all personnel, including data scientists and technicians. The software can be used to plot analyte concentration profiles, spectral data, and other process variables in real time. All process data are represented in a single view with interactive charts useful for viewing how a process evolves over time.

07 ISOTOPE AND RADIATION SOURCES↗