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At least 379 records · Page 21

A Microwave Photonics Optical Fiber Method for Measuring Distributed Strain for Hydrologic Applications in the Vadose and Saturated Zones

Distributed strain measurements appear to hold significant potential for monitoring hydrologic processes. Coherence-length-gated Microwave Photonics Interferometry (CMPI) is a distributed sensing technique that measures strain in an optical fiber by reading optical interference phase changes in the microwave domain. The technique provides 10nε resolution when cm spatial resolution is applied. CMPI was used to measure the strain caused by small periodic variations in air pressure (25 Pa amplitude and 4 Hz) in a sand-filled laboratory column used to represent barometric loading in the vadose zone. The strain varied as a periodic function with an amplitude that decreased and a phase that increased with depth. The distribution of amplitude and phase of the strain depended on the water saturation, permeability, and presence of a barrier at the top of the sand. A theoretical analysis suggests that the air pressure diffusivity estimated from pressure data is similar to the diffusivity estimated from the distributed strain. These results indicated that the CMPI distributed strain measurement system could be used to improve monitoring and characterization of the vadose and underlying saturated zone.

Hua, Liwei↗

Network, system, and status software enhancements for the autonomously managed electrical power system breadboard. Volume 2: Protocol specification

This volume (2 of 4) contains the specification, structured flow charts, and code listing for the protocol. The purpose of an autonomous power system on a spacecraft is to relieve humans from having to continuously monitor and control the generation, storage, and distribution of power in the craft. This implies that algorithms will have been developed to monitor and control the power system. The power system will contain computers on which the algorithms run. There should be one control computer system that makes the high level decisions and sends commands to and receive data from the other distributed computers. This will require a communications network and an efficient protocol by which the computers will communicate. One of the major requirements on the protocol is that it be real time because of the need to control the power elements.

Mckee, James W.↗

Demonstrating Distribution System Resiliency through Grid-Edge Microgrids, on a Multi-Site Networked Hardware-in-Loop Platform

With the increasing penetration of Distributed Energy Resources (DERs) at the grid-edge, power systems include more energy storage, remote switches, relays, voltage regulators, and other intelligent electronic devices (IED). Effective control of these grid-edge devices by using Advanced Distribution Management Systems (ADMS) can yield substantial improvements to the resiliency and power quality of distribution systems. In this paper, improvements to the resiliency of a distribution system are demonstrated using a multi-site evaluation environment consisting of a real-time Hardware-in-Loop (HIL) setup in which DERs and other IEDs are modeled; and an ADMS which monitors and is able to control the distribution system assets. The HIL model and the ADMS are located 2400 km away, with communication between the sites enabled by a data manager using Distributed Network Protocol 3 (DNP3), demonstrating the system's capabilities even over long distances. After a simulated transmission system failure in the HIL demonstration setup, DERs and other devices are operated to restore critical loads and node voltage profile (to within the 'nominal +/-5%' band) in the distribution system.

ADMS↗

Brief communication: Monitoring snow depth using small, cheap, and easy-to-deploy snow–ground interface temperature sensors

Abstract. Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. We trained a random forest machine learning model to predict snow depth from variability in snow–ground interface temperature. The model performed well on Alaska's Seward Peninsula where it was trained and at Arctic evaluation sites (RMSE ≤ 0.15 m). It performed poorly at temperate sites with deeper snowpacks, partially due to training data limitations. Small temperature sensors are cheap and easy to deploy, so this technique enables spatially distributed and temporally continuous snowpack monitoring at high latitudes to an extent previously infeasible.

54 ENVIRONMENTAL SCIENCES↗

Single Stage Rocket Technology's real time data system

The Single Stage Rocket Technology (SSRT) Delta Clipper Experimental (DC-X) Program is a United States Air Force Ballistic Missile Defense Organization (BMDO) rapid prototyping initiative that is currently demonstrating technology readiness for reusable suborbital rockets. The McDonnell Douglas DC-X rocket performed technology demonstrations at the U.S. Army White Sands Missile Range in New Mexico from April-October in 1993. The DC-X Flight Operations Control Center (FOCC) contains the ground control system that is used to monitor and control the DC-X vehicle and its Ground Support Systems (GSS). The FOCC is operated by a flight crew of three operators. Two operators manage the DC-X Flight Systems and one operator is the Ground Systems Manager. A group from McDonnell Douglas Aerospace at KSC developed the DC-X ground control system for the FOCC. This system is known as the Real Time Data System (RTDS). The RTDS is a distributed real time control and monitoring system that utilizes the latest available commercial off-the-shelf computer technology. The RTDS contains front end interfaces for the DC-X RF uplink/downlink and fiber optic interfaces to the GSS equipment. This paper describes the RTDS architecture and FOCC layout. The DC-X applications and ground operations are covered.

Voglewede, Steven D.↗

Code Description for "Brief Communication: Monitoring snow depth using small, cheap, and easy-to-deploy ground surface temperature sensors"

Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. We train a random forest machine learning model to predict snow depth from variability in ground surface temperature. To our knowledge, this is the first time that small ground surface temperature sensors have been used to estimate snow depth. The model performs well at sites where the model was trained and at pan-arctic evaluation sites (RMSE <= 0.15 m). Small temperature sensors are cheap and easy-to-deploy, so this technique enables spatially distributed and temporally continuous snowpack monitoring to an extent previously infeasible. The model is flexible and can be applied to datasets retroactively to retrieve snow depth estimates at additional sites. This code package includes a *.joblib file of the trained random forest model and a *.ipynb file showing how to clean input data, train the random forest model, and apply the model.

Bachand, Claire↗

Geophysical and Environmental Monitoring Data, Lower Watershed, Teller Road Mile Marker 27, Seward Peninsula, Alaska, 2017-2019

This data set contains geophysical and environmental monitoring data acquired between September 2017 and 2019 at the lower Teller watershed, Seward Peninsula, Alaska. Geophysical data comprises processed resistivity data, acquired daily between Spring and Fall of 2018 and 2019, and a baseline measurement of Fall 2017. The environmental monitoring data comprises depth resolved, distributed soil moisture and soil temperature data. These measurements were obtained used Decagon 5TE sensors placed at 0.1 m, 0.2 m , 0.3 m, and 0.4 m depth. In addition, temperature data at 0.5 m, 1.0 m, and 1.5 m were acquired using Hobo temperature sensors. Data were collected to improve our understanding of the hydrological response of discontinuous permafrost systems, in particular focusing on multi-annual dynamics and short term disturbances, such as snowmelt or precipitation events. The electrical resistivity tomography (ERT) monitoring data are included as processed resistivity models, with model cells x dimension equal to the distance along the profile, and model z dimension being elevation. The start and end point of the transect are (UTM Zone 3N): E 454881.66 m, N 7178949.45 m, and E 454772.60, N 7178885.81. Locations of the soil moisture and temperature sensors are provided in the data package. This dataset is discussed in detail in the Uhlemann, S. et al 2021 paper listed in the references. This dataset includes one *.pdf user guide and 315 *.csv data files included within four zipped files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Passive Neutron Instrumentation and Applications

This chapter presents a description of most of the instruments that are currently in use for the measurement of plutonium and uranium using passive methods (without an external source). This includes the acquisition electronics as well as Singles counting methods, coincidence counting methods and multiplicity counting methods. The Singles counting applications include the measurement of waste and curium bearing materials. The coincidence counting applications include bulk plutonium, bulk uranium, waste and holdup measurements and fresh fuel assemblies. The multiplicity application description includes advantages and disadvantages and multiplicity detector design. There is also a description of some non-3He systems. The chapter concludes with a description of additional concepts: neutron imagers, list-mode data analysis, distributed source term analysis, unattended monitoring and MCNP modeling for detector design.

Coincidence shift register↗

Distributive, Non-destructive Real-time System and Method for Snowpack Monitoring

A ground-based system that provides quasi real-time measurement and collection of snow-water equivalent (SWE) data in remote settings is provided. The disclosed invention is significantly less expensive and easier to deploy than current methods and less susceptible to terrain and snow bridging effects. Embodiments of the invention include remote data recovery solutions. Compared to current infrastructure using existing SWE technology, the disclosed invention allows more SWE sites to be installed for similar cost and effort, in a greater variety of terrain; thus, enabling data collection at improved spatial resolutions. The invention integrates a novel computational architecture with new sensor technologies. The invention's computational architecture is based on wireless sensor networks, comprised of programmable, low-cost, low-powered nodes capable of sophisticated sensor control and remote data communication. The invention also includes measuring attenuation of electromagnetic radiation, an approach that is immune to snow bridging and significantly reduces sensor footprints.

Frolik, Jeff↗

Southeast Michigan Health & Air Quality: Identifying Trends of Ground-level Ozone Precursors in Southeast Michigan and Northern Ohio

Pollutants resulting from industrial activity can react with sunlight to create ground-level ozone, a harmful pollutant that can exacerbate respiratory health issues such as asthma. Due to a history of heavy industrialization, residents of southeast Michigan and northern Ohio are especially susceptible to ground-level ozone. NASA DEVELOP, in partnership with the Michigan Department of Environment, Great Lakes, and Energy’s (EGLE) Air Quality Division and the Lake Michigan Air Directors Consortium (LADCO), investigated the effectiveness of Earth observations (EO) in monitoring pollutants that contribute to ground-level ozone. The team used the European Space Agency’s TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5P, and NASA’s Ozone Monitoring Instrument (OMI) aboard Aura, to measure nitrogen dioxide (NO2), formaldehyde (HCHO), and methane (CH4) from 2019 to 2021 (May-September). The team oversampled the EO data on monthly, yearly, and 3-year time scales where possible to enhance more localized pollutant trends. Specifically, TROPOMI effectively monitored NO2 from space, indicating sub-city distributions on a monthly timescale. Contrastingly, the measurements of HCHO were predominately noisy, and therefore failed to show any distribution trends. Lastly, CH4 trends were identifiable yet coarse, hinting that EO monitoring in the case of CH4 is not beneficial for our partners. The end products provide the partners with insight on the utility of EO in measuring certain ozone precursors and can be used to guide ground-level ozone reduction strategies throughout the region.

Mariam Moeen↗

Long-term variations in abundance and distribution of sulfuric acid vapor in the Venus atmosphere inferred from Pioneer Venus and Magellan radio occultation studies

Radio occultation experiments have been used to study various properties of planetary atmospheres, including pressure and temperature profiles, and the abundance profiles of absorbing constituents in those planetary atmospheres. However, the reduction of amplitude data from such experiments to determine abundance profiles requires the application of the inverse Abel transform (IAT) and numerical differentiation of experimental data. These two operations preferentially amplify measurement errors above the true signal underlying the data. A new technique for processing radio occultation data has been developed that greatly reduces the errors in the derived absorptivity and abundance profiles. This technique has been applied to datasets acquired from Pioneer Venus Orbiter radio occultation studies and more recently to experiments conducted with the Magellan spacecraft. While primarily designed for radar studies of the Venus surface, the high radiated power (EIRP) from the Magellan spacecraft makes it an ideal transmitter for measuring the refractivity and absorptivity of the Venus atmosphere by such experiments. The longevity of the Pioneer Venus Orbiter has made it possible to study long-term changes in the abundance and distribution of sulfuric acid vapor, H2SO4(g), in the Venus atmosphere between 1979 and 1992. The abundance of H2SO4(g) can be inferred from vertical profiles of 13-cm absorptivity profiles retrieved from radio occultation experiments. Data from 1979 and 1986-87 suggest that the abundance of H2SO4(g) at latitudes northward of 70 deg decreased over this time period. This change may be due to a period of active volcanism in the late 1970s followed by a relative quiescent period, or some other dynamic process in the Venus atmosphere. While the cause is not certain, such changes must be incorporated into dynamic models of the Venus atmosphere. Potentially, the Magellan spacecraft will extend the results of Pioneer Venus Orbiter and allow the continued monitoring of the abundance of distribution of H2SO4(g) in the Venus atmosphere, as well as other interesting atmospheric properties. Without such measurements it will be difficult to address other issues such as the short-term spatial variability of the abundance of H2SO4(g) at similar latitudes in Venus atmosphere, and the identities of particles responsible for large-scale variations observed in NIR images.

Jenkins, J. M.↗

The future of subsurface monitoring: AEC’s breakthroughs in CCS technology

Carbon capture and storage (CCS) has emerged as a key solution in the fight against climate change. However, for CCS to succeed, it is crucial to ensure that the sequestered CO2 stays safely trapped underground. The U.S. Department of Energy (DOE) has emphasized the need for advancements in subsurface monitoring, measurement, reporting, and verification. Aside from caprock integrity failure, the other primary failure points usually involve defective cement in the casing annulus of wellbores or plugged and abandoned wells. In addition, many energy producers (e.g., oil and gas, geothermal) and storage and disposal operators (e.g., H2 and water) must deal with the same issue. Poorly placed or degraded cement can create pathways for gas or fluid to escape from casing annuli and in plugged and abandoned or orphan wells, posing environmental risks. Yet, a reliable and cost-effective way to monitor cement and well integrity over multiple decades is still unavailable. Traditional geophysical methods like 4D seismic imaging and surface-based electromagnetic monitoring lack the resolution and accuracy for detecting these types of failures (Vasco et al., 2022; Fawad and Mondol, 2021). Wireline logging is expensive to run continuously and is obtrusive to the operation. While fiber optics can potentially be a solution, its bulkiness can significantly compromise the cement's integrity. To address these challenges, the Advanced Energy Consortium (AEC) at The University of Texas at Austin’s Bureau of Economic Geology (the Bureau) has been pioneering research in subsurface monitoring using its portfolio of distributed autonomous microfabricated sensors for harsh subsurface environments since 2008. A class of these microsensors [System on a Chip (SoC)] can be mixed in cement and permanently placed without compromising the cement column; the sensors would then communicate with each other or a data acquisition (DAQ) master node. Another class of the AEC microsensors can be fully autonomous, with rechargeable micro-batteries capable of exceeding 100°C, flash memory, and, currently, a pressure and temperature sensor. They are designed to circulate in mud, geothermal fluids, U-loops, or pipelines. They can log data into memory and are unobtrusive to operations. Our team has been working on a multi-year DOE-funded project (DE-FE0031856)—supported by $2.95M in federal funding and $0.75M in cost-matching from the AEC—to demonstrate SoC sensor utility for CO2 leakage monitoring in CCS applications. This multi-institutional collaboration developed a novel sensing architecture utilizing radiofrequency (RF) microsensors embedded within the cement sheath. These sensors detect CO2 migration and are interrogated via a Smart Casing Collar (SCC).

58 GEOSCIENCES↗

Residual Temperature Bias Effects in Stratospheric Species Distributions from LIMS

The Nimbus 7 Limb Infrared Monitor of theStratosphere (LIMS) instrument operated from 25 Octo-ber 1978 through 28 May 1979. Its version 6 (V6) profileswere processed and archived in 2002. We present severaldiagnostic examples of the quality of the V6 stratospheric species distributions based on their level 3 zonal Fourier co-efficient products. In particular, we show that there are smalldifferences in the ascending (A) minus descending (D) or-bital temperature–pressure orT(p) profiles (theirA−Dval-ues) that affect (A−D) species values. SystematicA−Dbi-ases inT(p) can arise from small radiance biases and/or fromviewing anomalies along orbits. There can also be (A−D)differences inT(p) due to not resolving and correcting forall of the atmospheric temperature gradient along LIMS tan-gent view-paths. An error inT(p) affects species retrievalsthrough (1) the Planck blackbody function in forward calcu-lations of limb radiance that are part of the iterative retrievalalgorithm of LIMS, and (2) the registration of the measuredLIMS species radiance profiles in pressure altitude, mainlyfor the lower stratosphere. There are clearA−Ddifferencesfor ozone, H2O, and HNO3but not for NO2. Percentage differences are larger in the lower stratosphere for ozone andH2O because those species are optically thick. We evaluateV6 ozone profile biases in the upper stratosphere with the aid of comparisons against a monthly climatology of UV–ozone soundings from rocketsondes. We also provide resultsof time series analyses of V6 ozone, H2O, and potential vor-ticity for the middle stratosphere to show that their average(A+D) V6 level 3 products provide a clear picture of the evolution of those tracers during Northern Hemisphere win-ter. We recommend that researchers use the average V6 level3 product for their science studies of stratospheric ozone andH2O, while keeping in mind that there are uncorrected non-local thermodynamic equilibrium effects in daytime ozone inthe lower mesosphere and in daytime H2O in the uppermoststratosphere. We also point out that the present-day Soundingof the Atmosphere using Broadband Emission Radiometry(SABER) experiment provides measurements and retrievalsof temperature and ozone that are nearly free of anomalousdiurnal variations and of effects from gradients at low and middle latitudes.

Ellis Remsberg↗

Miniaturized ultrafine particle sizer and monitor

An apparatus for measuring particle size distribution includes a charging device and a precipitator. The charging device includes a corona that generates charged ions in response to a first applied voltage, and a charger body that generates a low energy electrical field in response to a second applied voltage in order to channel the charged ions out of the charging device. The corona tip and the charger body are arranged relative to each other to direct a flow of particles through the low energy electrical field in a direction parallel to a direction in which the charged ions are channeled out of the charging device. The precipitator receives the plurality of particles from the charging device, and includes a disk having a top surface and an opposite bottom surface, wherein a predetermined voltage is applied to the top surface and the bottom surface to precipitate the plurality of particles.

Chen, Da-Ren↗

Neutrino Beam Monitoring

Accelerator facilities produce neutrino beams from meson decays in a decay volume. Experiments measure event rates that depend on flux, cross sections, and detector response, so the flux is predicted using hadron production and beamline modeling and constrained by beam instrumentation, since near detectors alone cannot separate flux from cross section. Proton, hadron, and muon monitors can track the parent particle distributions and beam conditions, providing the inputs needed for flux predictions in long-baseline experiments such as NOvA, T2K, and DUNE. This talk reviews how beam monitors are used in practice to understand neutrino flux. Proton beam monitors tell where the beam hits the target and how stable it is. Farther downstream, hadron and muon monitors sample particles produced in meson decays. Because those muons come from the same parents as the neutrinos, their profiles reveal focusing, alignment shifts, and other changes in the beam, and they are routinely used to detect problems and guide flux predictions. The muon information can be used more quantitatively; for example, to infer the parent meson phase space, and fast radiation-hard timing detectors can add sensitivity to the momentum dependence of the focusing. These developments show both how tightly beam measurements can constrain the flux and where the current limits still lie. These approaches complement monitored-beam concepts, in which the decay region is instrumented to detect charged leptons from meson decays and to measure the neutrino flux directly.

Ganguly, Sudeshna [Fermilab] (ORCID:00000003163482↗

Neutrino Beam Monitoring

Accelerator facilities produce neutrino beams from meson decays in a decay volume. Experiments measure event rates that depend on flux, cross sections, and detector response, so the flux is predicted using hadron production and beamline modeling and constrained by beam instrumentation, since near detectors alone cannot separate flux from cross section. Proton, hadron, and muon monitors can track the parent particle distributions and beam conditions, providing the inputs needed for flux predictions in long-baseline experiments such as NOvA, T2K, and DUNE. This talk reviews how beam monitors are used in practice to understand neutrino flux. Proton beam monitors tell where the beam hits the target and how stable it is. Farther downstream, hadron and muon monitors sample particles produced in meson decays. Because those muons come from the same parents as the neutrinos, their profiles reveal focusing, alignment shifts, and other changes in the beam, and they are routinely used to detect problems and guide flux predictions. The muon information can be used more quantitatively; for example, to infer the parent meson phase space, and fast radiation-hard timing detectors can add sensitivity to the momentum dependence of the focusing. These developments show both how tightly beam measurements can constrain the flux and where the current limits still lie. These approaches complement monitored-beam concepts, in which the decay region is instrumented to detect charged leptons from meson decays and to measure the neutrino flux directly.

Ganguly, Sudeshna [Fermilab] (ORCID:00000003163482↗

Transport processes in the stratosphere: Model simulations and comparisons with satellite observations

A three dimensional atmospheric model was used to study transport processes and to simulate the distribution of chemically active species in the stratosphere. The present results are part of a long term simulation of the seasonally varying structure of stratospheric trace constituents. The occurrence of a midwinter stratospheric warming and the associated transport of O3 and HNO3 during the simulation are described. Comparison of the simulated distributions of O3 and HNO3 are made with data from the Limb Infrared Monitor of the Stratosphere (LIMS) experiment. In addition, distributions of Ertel's potential vorticity on isentropic surfaces (IPV) are evaluated as a diagnostic for interpreting transport processes. Comparisons are made with IPV distributions inferred from LIMS temperature data.

Grose, W. L.↗

Distributed fiber optic strain sensing of bending deformation of a well mockup in the laboratory

Well integrity is critical to the safety and success of subsurface energy exploration and management, as leakage of fluids from subsurface reservoirs is often induced by compromised wells. This study investigates bending deformation of a mockup of an oil/gas well that is subjected to loads expected in deviated wells under reservoir compaction and assesses the feasibility of utilizing distributed fiber optic strain sensing to monitor the deformation. Here, a well mockup, which consists of outer and inner steel pipes with a cemented annulus, is tested under three-point bending loading and its strain and curvature development is monitored by Brillouin optical time domain reflectometry/analysis (BOTDR/A) as well as optical frequency domain reflectometry (OFDR). The primary objective of this research is to assess the strain sensing performance of newly fabricated fiber optic cables and to identify key cable characteristics which could improve the quality of distributed strain measurements with BOTDR/A. Results show that the tight-buffered cable is best suited for strain sensing as its maximum errors in the strain measurement were -36% and -24% against conventional sensors at the maximum elastic and plastic bending loads, respectively, whereas those of the non-tight-buffered cable were -45% and -71%, respectively. Similar trends were obtained in the bending curvature measurement. The detailed design of the tight-buffered cable is presented to elucidate key characteristics of such a cable, which will facilitate accurate distributed strain sensing in oil and gas wells.

42 ENGINEERING↗