Search NASA⌕ Search

SEARCH · Search NASA

Results for “depth data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Simulation of the transport, vertical distribution, optical properties and radiative impact of smoke aerosols with the ALADIN regional climate model during the ORACLES-2016 and LASIC experiments

Estimates of the direct radiative effect (DRE) from absorbing smoke aerosols over the southeast Atlantic Ocean (SAO) require simulation of the microphysical and optical properties of stratocumulus clouds as well as of the altitude and shortwave (SW) optical properties of biomass burning aerosols (BBAs). In this study, we take advantage of the large number of observations acquired during the ObseRvations of Aerosols above Clouds and their intEractionS (ORACLES-2016) and Layered Atlantic Smoke Interactions with Clouds (LASIC) projects during September 2016 and compare them with datasets from the ALADIN-Climate (Aire Limitée Adaptation dynamique Développement InterNational) regional model. The model provides a good representation of the liquid water path but the low cloud fraction is underestimated compared to satellite data. The modeled total-column smoke aerosol optical depth (AOD) and above-cloud AOD are consistent ( ~0.7 over continental sources and ~0.3 over the SAO at 550 nm) with the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), Ozone Monitoring Instrument (OMI) or Moderate Resolution Imaging Spectroradiometer (MODIS) data. The simulations indicate smoke transport over the SAO occurs mainly between 2 and 4 km, consistent with surface and aircraft lidar observations. The BBA single scattering albedo is slightly overestimated compared to the Aerosol Robotic Network (AERONET) and more significantly when compared to Ascension Island surface observations. The difference could be due to the absence of internal mixing treatment in the ALADIN-Climate model. The SSA overestimate leads to an underestimation of the simulated SW radiative heating compared to ORACLES data. ALADIN-Climate simulates a positive (monthly mean) SW DRE of about +6 W m -2 over the SAO (20 ° S–10 ° N and 10 ° W–20 ° E) at the top of the atmosphere and in all-sky conditions. Over the continent, the presence of BBA is shown to significantly decrease the net surface SW flux, through direct and semi-direct effects, which is compensated by a decrease (monthly mean) in sensible heat fluxes ( -25 W m -2 ) and surface land temperature ( -1.5 ° C) over Angola, Zambia and the Democratic Republic of the Congo, notably. The surface cooling and the lower tropospheric heating decrease the continental planetary boundary layer height by about ~200 m.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Remote sensing of regional pyroclastic deposits on the north central portion of the lunar nearside

High-resolution 3.0-cm radar data for the Rima Bode regional pyroclastic deposit and a number of UV-visible reflectance spectra for regional pyroclastic deposits on the north-central portion of the lunar nearside are analyzed and compared to existing data. The data obtained indicate that small craters in this deposit excavated loose unwelded pyroclastic particles, suggesting that welded layers or lenses do not exist at depths within the deposit's core area. The 70-cm radar data indicate that the Roma Bode deposit is thinner than the pyroclastic unit on the Aristarchus Plateau. The surfaces of all these regional pyroclastic deposits are dominated by ilmenite-rich black spheres, and contamination by low-Ti, nonpyroclastic debris appears to be minimal. The fine-grained block-free uncontaminated Rima Bode would be ideal for lunar mining operations and for rapidly covering lunar base modules with an adequate thickness of shielding material for protection from meteorite impact and space radiation.

Hawke, B. R.↗
NASA NTRS2024

Northern Colorado Water Resources: Using Earth Observations to Assess Relationships between Snowpack and Wildfires for Water Utility Management

In recent years, wildfires in the western U.S. have increased in size, frequency, and severity. Colorado is no exception to this trend, with many recent wildfires raising concerns. The Cameron Peak and East Troublesome Fires, the two largest recorded wildfires in Colorado history, burned over 400,000 acres in 2020. Wildfires pose a significant threat to high-elevation ecosystems, especially in terms of disturbances to watershed resources. Colorado’s annual water supply is dependent upon the melt and runoff of high-elevation snowpack, thus understanding wildfire effects is crucial. This project partnered with Northern Water, a water management company in Colorado, to explore fire impacts on Colorado Front Range watersheds and water supply forecasts. We investigated the use of remote sensing to study the influences of wildfire on snow depth, as Northern Water had previously relied on field-based observations of snowpack for their water supply forecasts. This project utilized airborne LiDAR data from Airborne Snow Observatories, Inc., Landsat 8 OLI derived products, as well as in situ snow survey data from Colorado State University to assess and model changes in snowpack over time. We uncovered key drivers of change in snowpack such as burn severity and snow zone and created a random forest model to determine and investigate their relationships. Despite temporal data availability limitations, analysis also showed that remotely-sensed snow depth measurements were strongly correlated with in situ snow depth measurements, revealing the accuracy and feasibility of using remote sensing technologies to study landscape-scale snowpack characteristics for water utility management purposes.

airborne LiDAR↗
DOE OSTI2019

Second data release of the Hyper Suprime-Cam Subaru Strategic Program

This paper presents the second data release of the Hyper Suprime-Cam Subaru Strategic Program, a wide-field optical imaging survey using the 8.2 m Subaru Telescope. We report the release includes data from 174 nights of observation through 2018 January. The Wide layer data cover about 300 deg$^2$ in all five broad-band filters ($grizy$) to the nominal survey exposure (10 min in $gr$ and 20 min in $izy$). Partially observed areas are also included in the release; about 1100 deg$^2$ is observed in at least one filter and one exposure. The median seeing in the i-band is ${0_{.}^{\prime \prime }6}$, demonstrating the superb image quality of the survey. The Deep (26 deg$^2$) and UltraDeep (4 deg$^2$) data are jointly processed and the UltraDeep-COSMOS field reaches an unprecedented depth of $i\sim 28$ at $5 \, \sigma$ for point sources. In addition to the broad-band data, narrow-band data are also available in the Deep and UltraDeep fields. This release includes a major update to the processing pipeline, including improved sky subtraction, PSF modeling, object detection, and artifact rejection. The overall data quality has been improved, but this release is not without problems; there is a persistent deblender problem as well as new issues with masks around bright stars. The user is encouraged to review the issue list before utilizing the data for scientific explorations. All the image products as well as catalog products are available for download. The catalogs are also loaded into a database, which provides an easy interface for users to retrieve data for objects of interest. In addition to these main data products, detailed galaxy shape measurements withheld from Public Data Release 1 (PDR1) are now available to the community. The shape catalog is drawn from the S16A internal release, which has a larger area than PDR1 (160 deg$^2$). All products are available at the data release site, https://hsc-release.mtk.nao.ac.jp/.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1996

Visible and Infrared Radiative Relationships as Measured by Satellite and Lidar

The impact of cirrus clouds on the heat balance of the Earth is dependent on their reflectivity of solar radiation and their absorptivity of terrestrial radiation. Any prediction of cloud cover changes that accompany climate change will have to know whether the visible/IR radiative characteristics of the clouds will also change. Few measurements of cirrus clouds have been made where both visible and IR data were collected simultaneously. To obtain the visible optical depths of cirrus clouds, the High Spectral Resolution Lidar (HSRL) and the Volume Imaging Lidar (VIL) were used. The VIL produced visible backscatter images of the clouds by scanning across the wind. Time advection was used to construct a horizontal image of visible backscatter from the VIL data. The HSRL was used to calibrate the VIL signal into backscatter cross sections of particulates.

Wylie, Donald↗
DOE OSTI2020

General Analysis of Data Collected from DOE Lidar Buoy Deployments Off Virginia and New Jersey

Pacific Northwest National Laboratory (PNNL) operates two AXYS WindSentinel lidar buoys for the U.S. Department of Energy’s Wind Energy Technologies. The purpose of these buoys is to collect hub-height winds and supporting meteorological and oceanographic information to facilitate the development of offshore wind energy in the U.S. In general, each buoy is deployed for a year or more at a given location in order to capture at least a full annual cycle of weather conditions. The initial deployment for one buoy was off the coast of Virginia beginning in 2015, and the other buoy was first deployed off the coast of New Jersey beginning in 2016. Over the last two years, PNNL has had an opportunity to analyze the data collected during these first two deployments. This report describes a substantial analysis of data collected by the two lidar buoys operated off the coasts of Virginia and New Jersey. The centerpiece instrument for each buoy as deployed off Virginia and New Jersey is a lidar system, which is designed to measure the horizontal wind vector from approximately 40 m to 200 m above the sea surface with vertical resolution of 40 m. Since the initial deployments, the original lidars have been replaced with more powerful Leosphere 866 v2 systems. The analyses in this report will apply to the original Vindicator systems. In addition to the wind profiles from the lidars, the buoys collect near-surface measurements of wind speed and direction, air temperature, relative humidity, barometric pressure, and solar irradiance. Oceanographic variables measured include the two-dimensional wave spectrum, water temperature and conductivity, and ocean current vectors to a depth of 90 m. An assessment of overall data recovery and a basic analysis of the data collected was provided in a previous report This report substantially extends that analysis. The various sections describe the development and application of an inertial measurement unit (IMU) data recovery scheme for the New Jersey deployment; a climatological analysis of winds at hub height and at the surface together with thermodynamic variables measured at the surface for the full deployment periods; an analysis of oceanographic observations describe sea state; the development of a refinement for NOAA’s WaveWatch III model to allow its application to near-shore areas; a basic climatology of ocean currents observed from the buoys; an analysis of observed winds in the framework of Monin-Obukhov Similarity Theory; and the development and evaluation of techniques to extract turbulence intensity and turbulence kinetic energy from the lidars. The analyses contained in this report provide a great deal of new information about offshore conditions on the U.S. East Coast. In addition, the experience gained will inform both configurations and analysis of data from future deployments of these lidar buoy systems.

17 WIND ENERGY↗
NASA NTRS2015

Flight Test Series 3: Flight Test Report

This document is a flight test report from the Operational perspective for Flight Test Series 3, a subpart of the Unmanned Aircraft System (UAS) Integration in the National Airspace System (NAS) project. Flight Test Series 3 testing began on June 15, 2015, and concluded on August 12, 2015. Participants included NASA Ames Research Center, NASA Armstrong Flight Research Center, NASA Glenn Research Center, NASA Langley Research center, General Atomics Aeronautical Systems, Inc., and Honeywell. Key stakeholders analyzed their System Under Test (SUT) in two distinct configurations. Configuration 1, known as Pairwise Encounters, was subdivided into two parts: 1a, involving a low-speed UAS ownship and intruder(s), and 1b, involving a high-speed surrogate ownship and intruder. Configuration 2, known as Full Mission, involved a surrogate ownship, live intruder(s), and integrated virtual traffic. Table 1 is a summary of flights for each configuration, with data collection flights highlighted in green. Section 2 and 3 of this report give an in-depth description of the flight test period, aircraft involved, flight crew, and mission team. Overall, Flight Test 3 gathered excellent data for each SUT. We attribute this successful outcome in large part from the experience that was acquired from the ACAS Xu SS flight test flown in December 2014. Configuration 1 was a tremendous success, thanks to the training, member participation, integration/testing, and in-depth analysis of the flight points. Although Configuration 2 flights were cancelled after 3 data collection flights due to various problems, the lessons learned from this will help the UAS in the NAS project move forward successfully in future flight phases.

Unmanned↗
NASA NTRS1991

Monitoring global snow cover

A snow model that supports the daily, operational analysis of global snow depth and age has been developed. It provides improved spatial interpolation of surface reports by incorporating digital elevation data, and by the application of regionalized variables (kriging) through the use of a global snow depth climatology. Where surface observations are inadequate, the model applies satellite remote sensing. Techniques for extrapolation into data-void mountain areas and a procedure to compute snow melt are also contained in the model.

Armstrong, Richard↗
DOE OSTI2019

Application of the PHDS Germanium Gamma-ray Imager (GeGI) in Facility Decontamination Assessment - 19471

As part of a site wide investigation, U.S. EPA Region 5 had to assess the nature and extent of contamination in a former radioactive source manufacturing facility. This work involved verification of the radioisotope expected, ensuring no other radioisotopes were present, and quantification of the activity and areal extent of contamination throughout the facility. The device used to support this assessment work was the Germanium Gamma-ray Imager (GeGI) manufactured by PHDS Co. of Knoxville, Tennessee. GeGI is a germanium-semiconductor imaging detector system that provides identification, location, and quantification of radioactive materials within its field of view. GeGI provides the highest fidelity radiological assay information including the best gamma-ray energy resolution and spatial localization of any existing technology, including gamma-ray energy resolution of ∼0.3% full-width half-max (FWHM) at 662 keV and angular location resolution ∼ +/-1 degree. The GeGI is a mechanically cooled, portable system well-suited to field operations. PHDS Co. also provided on-site support during assessment operations and performed subsequent data analysis. Gamma-ray spectral data and associated images were collected with GeGI in six primary areas of the facility having significant residual contamination. A total of 61 gamma-ray spectrum/image sets were collected over the course of three working days (22 Compton images and 39 Pinhole/Compton images). During data collection, Compton imaging was used as the means by which to identify and prioritize hotspots. After contaminated regions were identified via Compton imaging, short-distance Pinhole spectrum/image sets were collected for additional analysis. All of the spectrum/image sets were analyzed to determine the radioisotope distribution within the GeGI field of view, as well as to provide an estimate of the activity associated with each hotspot. It was determined that the nature of residual contamination present was distributed across specific areas of elevated activity, where in some areas there was significant accumulation of contaminated material. It was also determined that no discrete sources of high-activity were present, as would be expected in the case of radioactive material product intended for sealed source manufacture. Results included the activity of residual contamination for each of the areas assessed, and an estimate of the physical area over which that contamination was distributed. It was anticipated by EPA that if decontamination were to be performed that it would involve some type of concrete scabbling or other means of physical removal of contaminated material. The GeGI data could be used to estimate the areal extent (square footage) of concrete removal that would be required for decontamination. Using the activity estimate data from the GeGI along with an estimated depth of concrete removal, planning could be performed for decontamination work (equipment and personnel), waste collection, packaging, transportation, and disposal, along with an associated cost estimate. With regard to health and safety, use of the GeGI reduced the radiation dose to the EPA R5 staff performing the assessment work. The GeGI is a non-destructive device that supports assessment of radioactively contaminated areas and sources from a distance, reducing the need for close contact to radiation, and the time necessary for personnel to operate near such hazards. Use of the GeGI in this facility assessment was our first attempt to apply this technology in what proved to be a quick and efficient decontamination assessment method. The GeGI can assess the nature and extent of residual contamination in a facility, first by quickly identifying the areas of elevated activity, followed by refined measurement and assessment of those elevated areas. The GeGI data can then be used to develop planning and a cost estimate of required decontamination and waste management activities. Since it's a non-destructive gamma identification and imaging device, it can reduce the distance of workers from radioactive sources and the dose incurred from assessment work. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Modeling Transient Soil Moisture Limitations on Microbial Carbon Respiration

Soil microorganisms are known to survive periods of aridity and to recover rapidly after wetting events, with the ability to transition between a dormant state in dry conditions and an active state in wet conditions. While this dynamic behavior has been previously incorporated into soil carbon respiration modeling frameworks, a direct comparison between this active-dormant transition mechanism and a more simplified first-order model has yet to be made. Here, we demonstrate the necessary extent of model complexity needed to reproduce transient carbon respiration rates obtained from a set of soil incubation experiments implemented over a range of soil depths and time intervals. Two approaches are tested, one uses simplified first-order kinetics, whereas the other employs a transition between active and dormant biomass. The performance of each model is evaluated using an Akaike Information Criterion (AIC) based on the accuracy with which they reproduce an experimental dataset consisting of two sets of time series soil incubations collected across a range of time and depth resolutions. Based on the AIC evaluation and model-data comparison, we conclude that a dormancy-enabled model featuring two distinct microbial strategists performs best for the majority of the soil profile (above 108 cm) for both high and low depth resolution and sampling frequency, despite the added parameters required. In contrast, the first-order model achieves better AIC scores when simulating our deepest soils (112–165 cm), where moisture fluctuations are expected to be less prevalent. These findings guide how and where we choose to apply more cost intensive models.

58 GEOSCIENCES↗
DOE OSTI2023

Willingness to Receive mHealth Services Among Patients with Diabetes on Chronic Follow-up in Public Hospitals in Eastern Ethiopia: Multicenter Mixed-Method Study

Background: Management of diabetes requires a long-term care strategy, including support for adherence to a healthy lifestyle and treatment. Exploring the willingness of patients with diabetes to receive mHealth services is essential for designing efficient and effective services. This study aimedto determine willingness to receive mHealth services and associated factors, as well as explore the barriers to receive mHealth services among patients with diabetes. Methods: A multicenter mixed-method study was employed from September 1 to November 30, 2022. For the quantitative part, a total of 365 patients with diabetes receiving chronic follow-up at three public hospitals were enrolled. Data were gathered using structured questionnaires administered by interviewers, entered into Epi-data version 4.6, and analyzed using Stata version 17. A binary and multivariable logistic regression model was computed to identify the associated factors. For qualitative, eight key informants and seven in-depth interviews were conducted. After verbatim transcription and translation, the data were thematically analyzed using ATLAS.ti V. 7.5. Results: Overall, 77.3% had access to a mobile phone, and 74.5% of them were willing to receive mHealth services. Higher odds of willingness to receive mHealth services were reported among patients with an age below 35 years [AOR = 4.11 (1.15– 14.71)], attended formal education [AOR = 2.63 (1.19– 5.77)], without comorbidity [AOR = 3.6 (1.54– 8.41)], < 1-hour travel to reach a health facility [AOR = 3.57 (1.03– 12.36)], answered unknown calls [AOR = 2.3 (1.04– 5.13)], and were satisfied with health-care provider service [AOR = 2.44 (1.04– 5.72)]. In the qualitative part, infrastructure, health facilities, socioeconomic factors, and patients’ behavioral factors were major identified barriers to receiving mHealth services. Conclusion: In this study, the willingness to receive mHealth services for those who have access to mobile phones increased. Additionally, the study highlighted common barriers to receiving mHealth services.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1991

Recent studies of the optical properties of dust and cloud particles in the Mars atmosphere and the interannual frequency of global dust storms

The results of research with two distinctly separate sets of observations yield new information on the optical properties of particulate scatterers in the Mars atmosphere, and on the interannual variability of the abundance of such scatterers in the Mars atmosphere. The first set of observations were taken by the IRTM (Infrared Thermal Mapper) instrument onboard the Viking Orbiters, during the period 1976 to 1980. Several hundred emission phase function (EPF) sequences were obtained over the Viking mission, in which the IRTM visual brightness channel observed the same area of surface/atmosphere as the spacecraft passed overhead. The 1 to 2 percent accuracy of calibration and the phase-angle coverage that characterizes these data make them ideally suited to determining both the optical depths and optical properties of dust and cloud scatterers in the Mars atmosphere versus latitude, longitude, seasons (L sub s), and surface elevation over the extended period of Viking observations. The EPF data were analyzed with a multiple scattering radiative transfer code to determine dust single scattering albedos which are distinctly higher than indicated by the Viking Lander observations. The second set of observations regard ground-based observations of the 1.3 to 2.6 mm rotational transitions of CO in the Martian atmosphere. The low-to-mid latitude average of the atmospheric temperature profile (0 to 70 km altitude) were derived from a number of such observations over the 1980 to 1990 period.

Clancy, R. T.↗
NASA NTRS1988

Mass extinctions in the deep sea

The character of mass extinctions can be assessed by studying extinction patterns of organisms, the fabric of the extinction, and assessing the environmental niche and mode of life of survivors. Deep-sea benthic foraminifera have been listed as little affected by the Cretaceous-Tertiary (K-T) mass extinction, but very few quantitative data are available. New data on deep-sea Late Maestrichtian-Eocene benthic foraminifera from Maud Rise (Antractica) indicate that about 10 percent of the species living at depths of 2000 to 2500 m had last appearances within 1 my of the Cretaceous-Tertiary (K-T) boundary, versus about 25 percent of species at 1000 to 1500 m. Many survivors from the Cretaceous became extinct in a period of global deep-sea benthic foraminiferal extinction at the end of the Paleocene, a time otherwise marked by very few extinctions. Preliminary conclusions suggest that the deep oceanic environment is essentially decoupled from the shallow marine and terrestrial environment, and that even major disturbances of one of these will not greatly affect the other. This gives deep-sea benthic faunas a good opportunity to recolonize shallow environments from greater depths and vice versa after massive extinctions. The decoupling means that data on deep-sea benthic boundary was caused by the environmental effects of asteriod impact or excessive volcanism. The benthic foraminiferal data strongly suggest, however, that the environmental results were strongest at the Earth's surface, and that there was no major disturbance of the deep ocean; this pattern might result both from excessive volcanism and from an impact on land.

Thomas, E.↗
NASA NTRS1993

A new method for recognizing quadric surfaces from range data and its application to telerobotics and automation

The problem of recognizing and positioning of objects in three-dimensional space is important for robotics and navigation applications. In recent years, digital range data, also referred to as range images or depth maps, have been available for the analysis of three-dimensional objects owing to the development of several active range finding techniques. The distinct advantage of range images is the explicitness of the surface information available. Many industrial and navigational robotics tasks will be more easily accomplished if such explicit information can be efficiently interpreted. In this research, a new technique based on analytic geometry for the recognition and description of three-dimensional quadric surfaces from range images is presented. Beginning with the explicit representation of quadrics, a set of ten coefficients are determined for various three-dimensional surfaces. For each quadric surface, a unique set of two-dimensional curves which serve as a feature set is obtained from the various angles at which the object is intersected with a plane. Based on a discriminant method, each of the curves is classified as a parabola, circle, ellipse, hyperbola, or a line. Each quadric surface is shown to be uniquely characterized by a set of these two-dimensional curves, thus allowing discrimination from the others. Before the recognition process can be implemented, the range data have to undergo a set of pre-processing operations, thereby making it more presentable to classification algorithms. One such pre-processing step is to study the effect of median filtering on raw range images. Utilizing a variety of surface curvature techniques, reliable sets of image data that approximate the shape of a quadric surface are determined. Since the initial orientation of the surfaces is unknown, a new technique is developed wherein all the rotation parameters are determined and subsequently eliminated. This approach enables us to position the quadric surfaces in a desired coordinate system. Experiments were conducted on raw range images of spheres, cylinders, and cones. Experiments were also performed on simulated data for surfaces such as hyperboloids of one and two sheets, elliptical and hyperbolic paraboloids, elliptical and hyperbolic cylinders, ellipsoids and the quadric cones. Both the real and simulated data yielded excellent results. Our approach is found to be more accurate and computationally inexpensive as compared to traditional approaches, such as the three-dimensional discriminant approach which involves evaluation of the rank of a matrix. Finally, we have proposed one other new approach, which involves the formulation of a mapping between the explicit and implicit forms of representing quadric surfaces. This approach, when fully realized, will yield a three-dimensional discriminant, which will recognize quadric surfaces based upon their component surfaces patches. This approach is faster than prior approaches and at the same time is invariant to pose and orientation of the surfaces in three-dimensional space.

Alvertos, Nicolas↗
NASA NTRS2013

Soft Decision Analyzer

The Soft Decision Analyzer (SDA) is an instrument that combines hardware, firmware, and software to perform realtime closed-loop end-to-end statistical analysis of single- or dual- channel serial digital RF communications systems operating in very low signal-to-noise conditions. As an innovation, the unique SDA capabilities allow it to perform analysis of situations where the receiving communication system slips bits due to low signal-to-noise conditions or experiences constellation rotations resulting in channel polarity in versions or channel assignment swaps. SDA s closed-loop detection allows it to instrument a live system and correlate observations with frame, codeword, and packet losses, as well as Quality of Service (QoS) and Quality of Experience (QoE) events. The SDA s abilities are not confined to performing analysis in low signal-to-noise conditions. Its analysis provides in-depth insight of a communication system s receiver performance in a variety of operating conditions. The SDA incorporates two techniques for identifying slips. The first is an examination of content of the received data stream s relation to the transmitted data content and the second is a direct examination of the receiver s recovered clock signals relative to a reference. Both techniques provide benefits in different ways and allow the communication engineer evaluating test results increased confidence and understanding of receiver performance. Direct examination of data contents is performed by two different data techniques, power correlation or a modified Massey correlation, and can be applied to soft decision data widths 1 to 12 bits wide over a correlation depth ranging from 16 to 512 samples. The SDA detects receiver bit slips within a 4 bits window and can handle systems with up to four quadrants (QPSK, SQPSK, and BPSK systems). The SDA continuously monitors correlation results to characterize slips and quadrant change and is capable of performing analysis even when the receiver under test is subjected to conditions where its performance degrades to high error rates (30 percent or beyond). The design incorporates a number of features, such as watchdog triggers that permit the SDA system to recover from large receiver upsets automatically and continue accumulating performance analysis unaided by operator intervention. This accommodates tests that can last in the order of days in order to gain statistical confidence in results and is also useful for capturing snapshots of rare events.

Steele, Glen↗
DOE OSTI2023

Generalized Quantum Convolution for Multidimensional Data

The convolution operation plays a vital role in a wide range of critical algorithms across various domains, such as digital image processing, convolutional neural networks, and quantum machine learning. In existing implementations, particularly in quantum neural networks, convolution operations are usually approximated by the application of filters with data strides that are equal to the filter window sizes. One challenge with these implementations is preserving the spatial and temporal localities of the input features, specifically for data with higher dimensions. In addition, the deep circuits required to perform quantum convolution with a unity stride, especially for multidimensional data, increase the risk of violating decoherence constraints. In this work, we propose depth-optimized circuits for performing generalized multidimensional quantum convolution operations with unity stride targeting applications that process data with high dimensions, such as hyperspectral imagery and remote sensing. We experimentally evaluate and demonstrate the applicability of the proposed techniques by using real-world, high-resolution, multidimensional image data on a state-of-the-art quantum simulator from IBM Quantum.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Muon Borehole Detector Design for Use in 4-D Density Overburden Monitoring

The increase of atmospheric CO2 concentrations has initiated research into carbon sequestration methods. One possibility is to store CO2 in subsurface porous reservoirs. The monitoring of the injected CO2 plume is vital because escaping CO2 poses health and environmental risks. Typically, seismic reflection methods are used to determine the change in density due to the replacement of brine by CO2 in the reservoir, but this is expensive and not continuous. A potential alternative is to use cosmic muon tomography to measure density changes in the reservoir as a function of time. This paper describes the development of a muon detector that will be capable of being deployed in boreholes. The detector has the required dimensions, an angular resolution of approximately 2 degrees, and is robust. The design is based on alternating layers of scintillating rods, which can provide 4-D tomographic data to detect small changes in density at depths up to approximately 2 km. Geant4, a Monte Carlo simulation code, is being used to develop models to guide the design of the physical configuration. Preliminary testing and measurements have been performed to validate the simulation predictions and optimize the performance of the system. The simulation and preliminary experimental results are presented here.

Borehole Detector, CO¬2 Sequestration, Geant4, Muo↗
DOE OSTI2025

miniDOT Logger Dissolved Oxygen and Temperature Data of Wetland Surface Water, Old Woman Creek NERR, Huron, OH, 2022-06-15 to 2023-12-15

This dataset contains timeseries data of dissolved oxygen (DO) and temperature measurements of the surface water in a wetland at Old Woman Creek Estuarine Research Reserve in Huron, OH. Dissolved oxygen and temperature measurements were made in the overlying water column of wetland to assess how oxygen changed over time with hydrological events. Measurements were collected by a miniDOT Logger. Data was collected over 1.5 years (June 2022 to December 2023). The miniDOT_DO_Temp_DataFile.csv contains the DO and temperature measurements that were collected every 10 minutes. The water levels of the site varied over-time as the wetland flooded and dried. So, sometimes the miniDOT logger would be out of the water column, resulting in high oxygen levels. Depth of the water column was recorded at every in-person site visit. The miniDOT_Depth_DataFile.csv contains the hand-measured surface water depth measurements for comparison to the logger-collected data. Information on the deployment and measurement methods can be found in the miniDOT_InstallationMethods.csv file.

54 ENVIRONMENTAL SCIENCES↗