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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Parameterization of photon beam dosimetry for a linear accelerator

Purpose: In radiation therapy, accurate data acquisition of photon beam dosimetric quantities is important for (1) beam modeling data input into a treatment planning system (TPS), (2) comparing measured and TPS modeled data, (3) the quality assurance process of a linear accelerator’s (Linac) beam characteristics, (4) the establishment of a standard data set for comparison with other data, etcetera. Parameterization of the photon beam dosimetry creates a data set that is portable and easy to implement for different applications such as those previously mentioned. The aim of this study is to develop methods to parameterize photon beam dosimetric quantities, including percentage depth doses (PDDs), profiles, and total scatter output factors (S{sub cp}). Methods: S{sub cp}, PDDs, and profiles for different field sizes, depths, and energies were measured for a Linac using a cylindrical 3D water scanning system. All data were smoothed for the analysis and profile data were also centered, symmetrized, and geometrically scaled. The S{sub cp} data were analyzed using an exponential function. The inverse square factor was removed from the PDD data before modeling and the data were subsequently analyzed using exponential functions. For profile modeling, one halfside of the profile was divided into three regions described by exponential, sigmoid, and Gaussian equations. All of the analytical functions are field size, energy, depth, and, in the case of profiles, scan direction specific. The model’s parameters were determined using the minimal amount of measured data necessary. The model’s accuracy was evaluated via the calculation of absolute differences between the measured (processed) and calculated data in low gradient regions and distance-to-agreement analysis in high gradient regions. Finally, the results of dosimetric quantities obtained by the fitted models for a different machine were also assessed. Results: All of the differences in the PDDs’ buildup and the profiles’ penumbra regions were less than 2 and 0.5 mm, respectively. The differences in the low gradient regions were 0.20% ± 0.20% (<1% for all) and 0.50% ± 0.35% (<1% for all) for PDDs and profiles, respectively. For S{sub cp} data, all of the absolute differences were less than 0.5%. Conclusions: This novel analytical model with minimum measurement requirements was proved to accurately calculate PDDs, profiles, and S{sub cp} for different field sizes, depths, and energies.

61 RADIATION PROTECTION AND DOSIMETRY↗
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 OSTI2015

SU-E-T-597: Parameterization of the Photon Beam Dosimetry for a Commercial Linear Accelerator

Purpose: In radiation therapy, accurate data acquisition of photon beam dosimetric quantities is important for (1) beam modeling data input into a treatment planning system (TPS), (2) comparing measured and TPS modelled data, (3) a linear accelerator’s (linac) beam characteristics quality assurance process, and (4) establishing a standard data set for data comparison, etcetera. Parameterization of the photon beam dosimetry creates a portable data set that is easy to implement for different applications such as those previously mentioned. The aim of this study is to develop methods to parameterize photon percentage depth doses(PDD), profiles, and total scatter output factors(Scp). Methods: Scp, PDDs and profiles for different field sizes (from 2×2 to 40×40cm{sup 2}), depths and energies were measured in a linac using a three-dimensional water tank. All data were smoothed and profile data were also centered, symmetrized and geometrically scaled. The Scp and PDD data were analyzed using exponential functions. For modelling of open and wedge field profiles, each side was divided into three regions described by exponential, sigmoid and Gaussian equations. The model’s equations were chosen based on the physical principles described by these dosimetric quantities. The equations’ parameters were determined using a least square optimization method with the minimal amount of measured data necessary. The model’s accuracy was then evaluated via the calculation of absolute differences and distance–to–agreement analysis in low gradient and high gradient regions, respectively. Results: All differences in the PDDs’ buildup and the profiles’ penumbra regions were less than 2 mm and 0.5 mm, respectively. Differences in the low gradient regions were 0.20 ± 0.20% and 0.50 ± 0.35% for PDDs and profiles, respectively. For Scp data, all differences were less than 0.5%. Conclusion: This novel analytical model with minimum measurement requirements proved to accurately calculate PDDs, profiles, and Scp for different field sizes, depths and energies.

61 RADIATION PROTECTION AND DOSIMETRY↗
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↗
DOE OSTI2013

PCR-Induced Transitions Are the Major Source of Error in Cleaned Ultra-Deep Pyrosequencing Data

Ultra-deep pyrosequencing (UDPS) is used to identify rare sequence variants. The sequence depth is influenced by several factors including the error frequency of PCR and UDPS. This study investigated the characteristics and source of errors in raw and cleaned UDPS data. UDPS of a 167-nucleotide fragment of the HIV-1 SG3Δenv plasmid was performed on the Roche/454 platform. The plasmid was diluted to one copy, PCR amplified and subjected to bidirectional UDPS on three occasions. The dataset consisted of 47,693 UDPS reads. Raw UDPS data had an average error frequency of 0.30% per nucleotide site. Most errors were insertions and deletions in homopolymeric regions. We used a cleaning strategy that removed almost all indel errors, but had little effect on substitution errors, which reduced the error frequency to 0.056% per nucleotide. In cleaned data the error frequency was similar in homopolymeric and non-homopolymeric regions, but varied considerably across sites. These site-specific error frequencies were moderately, but still significantly, correlated between runs (r = 0.15–0.65) and between forward and reverse sequencing directions within runs (r = 0.33–0.65). Furthermore, transition errors were 48-times more common than transversion errors (0.052% vs. 0.001%; p<0.0001). Collectively the results indicate that a considerable proportion of the sequencing errors that remained after data cleaning were generated during the PCR that preceded UDPS. A majority of the sequencing errors that remained after data cleaning were introduced by PCR prior to sequencing, which means that they will be independent of platform used for next-generation sequencing. The transition vs. transversion error bias in cleaned UDPS data will influence the detection limits of rare mutations and sequence variants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Programmable stream prefetch with resource optimization

A stream prefetch engine performs data retrieval in a parallel computing system. The engine receives a load request from at least one processor. The engine evaluates whether a first memory address requested in the load request is present and valid in a table. The engine checks whether there exists valid data corresponding to the first memory address in an array if the first memory address is present and valid in the table. The engine increments a prefetching depth of a first stream that the first memory address belongs to and fetching a cache line associated with the first memory address from the at least one cache memory device if there is not yet valid data corresponding to the first memory address in the array. The engine determines whether prefetching of additional data is needed for the first stream within its prefetching depth. The engine prefetches the additional data if the prefetching is needed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Planck intermediate results: XLVII. Planck constraints on reionization history

In this paper, we investigate constraints on cosmic reionization extracted from the Planck cosmic microwave background (CMB) data. We combine the Planck CMB anisotropy data in temperature with the low-multipole polarization data to fit ΛCDM models with various parameterizations of the reionization history. We obtain a Thomson optical depth τ = 0.058 ± 0.012 for the commonly adopted instantaneous reionization model. This confirms, with data solely from CMB anisotropies, the low value suggested by combining Planck 2015 results with other data sets, and also reduces the uncertainties. We reconstruct the history of the ionization fraction using either a symmetric or an asymmetric model for the transition between the neutral and ionized phases. To determine better constraints on the duration of the reionization process, we also make use of measurements of the amplitude of the kinetic Sunyaev-Zeldovich (kSZ) effect using additional information from the high-resolution Atacama Cosmology Telescope and South Pole Telescope experiments. The average redshift at which reionization occurs is found to lie between z = 7.8 and 8.8, depending on the model of reionization adopted. Using kSZ constraints and a redshift-symmetric reionization model, we find an upper limit to the width of the reionization period of Δz < 2.8. In all cases, we find that the Universe is ionized at less than the 10% level at redshifts above z ≃ 10. This suggests that an early onset of reionization is strongly disfavoured by the Planck data. Finally, we show that this result also reduces the tension between CMB-based analyses and constraints from other astrophysical sources.

79 ASTRONOMY AND ASTROPHYSICS↗
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↗
DOE OSTI2019

Anatomy of a Cooling Flow: The Feedback Response to Pure Cooling in the Core of the Phoenix Cluster

We present new, deep observations of the Phoenix cluster from the Chandra X-ray Observatory, the Hubble Space Telescope, and the Karl Jansky Very Large Array. These data provide an order of magnitude improvement in depth and/or angular resolution at X-ray, optical, and radio wavelengths, yielding an unprecedented view of the core of the Phoenix cluster. We find that the one-dimensional temperature and entropy profiles are consistent with expectations for pure-cooling hydrodynamic simulations and analytic descriptions of homogeneous, steady-state cooling flow models. In the inner ~10 kpc, the cooling time is shorter by an order of magnitude than any other known cluster, while the ratio of the cooling time to freefall time approaches unity, signaling that the ICM is unable to resist multiphase condensation on kpc scales. When we consider the thermodynamic profiles in two dimensions, we find that the cooling is highly asymmetric. The bulk of the cooling in the inner ~20 kpc is confined to a low-entropy filament extending northward from the central galaxy. We detect a substantial reservoir of cool (10^4 K) gas (as traced by the [OII] doublet), which is coincident with the low-entropy filament. The bulk of this cool gas is draped around and behind a pair of X-ray cavities, presumably bubbles that have been inflated by radio jets, which are detected for the first time on kpc scales. These data support a picture in which AGN feedback is promoting the formation of a multiphase medium via a combination of ordered buoyant uplift and locally enhanced turbulence. These processes ought to counteract the tendency for buoyancy to suppress condensation, leading to rapid cooling along the jet axis. The recent mechanical outburst has sufficient energy to offset cooling, and appears to be coupling to the ICM via a cocoon shock, raising the entropy in the direction orthogonal to the radio jets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Point Cloud Based Approach to Stem Width Extraction of Sorghum

A revolution in the field of genomics has produced vast amounts of data and furthered our understanding of the genotypephenotype map, but is currently constrained by manually intensive or limited phenotype data collection. We propose an algorithm to estimate stem width, a key characteristic used for biomass potential evaluation, from 3D point cloud data collected by a robot equipped with a depth sensor in a single pass in a standard field. The algorithm applies a two step alignment to register point clouds in different frames, a Frangi filter to identify stemlike objects in the point cloud and an orientation based filter to segment out and refine individual stems for width estimation. Individually, detected stems which are split due to occlusions are merged and then registered with previously found stems in previous camera frames in order to track temporally. We then refine the estimates to produce an accurate histogram of width estimates per plot. Since the plants in each plot are genetically identical, distributions of the stem width per plot can be useful in identifying genetically superior sorghum for biofuels.

09 BIOMASS FUELS↗
DOE OSTI2015

MERIDIONAL FLOW IN THE SOLAR CONVECTION ZONE. II. HELIOSEISMIC INVERSIONS OF GONG DATA

Meridional flow is thought to play a very important role in the dynamics of the solar convection zone; however, because of its relatively small amplitude, precisely measuring it poses a significant challenge. Here we present a complete time–distance helioseismic analysis of about 2 years of ground-based Global Oscillation Network Group (GONG) Doppler data to retrieve the meridional circulation profile for modest latitudes in an attempt to corroborate results from other studies. We use an empirical correction to the travel times due to an unknown center-to-limb systematic effect. The helioseismic inversion procedure is first tested and reasonably validated on artificial data from a large-scale numerical simulation followed by a test to broadly recover the solar differential rotation found from global seismology. From GONG data, we measure poleward photospheric flows at all latitudes with properties that are comparable with earlier studies and a shallow equatorward flow about 65 Mm beneath the surface, in agreement with recent findings from Helioseismic and Magnetic Imager (HMI) data. No strong evidence of multiple circulation cells in depth or latitude is found, yet the whole phase space has not yet been explored. Tests of mass flux conservation are then carried out on the inferred GONG and HMI flows and compared to a fiducial numerical baseline from models, and we find that the continuity equation is poorly satisfied. While the two disparate data sets do give similar results for about the outer 15% of the interior radius, the total inverted circulation pattern appears to be unphysical in terms of mass conservation when interpreted over modest time scales. We can likely attribute this to both the influence of realization noise and subtle effects in the data and measurement procedure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

SU-E-T-554: Monte Carlo Calculation of Source Terms and Attenuation Lengths for Neutrons Produced by 50–200 MeV Protons On Brass

Purpose: We used TOPAS (TOPAS wraps and extends Geant4 for medical physicists) to compare Geant4 physics models with published data for neutron shielding calculations. Subsequently, we calculated the source terms and attenuation lengths (shielding data) of the total ambient dose equivalent (TADE) in concrete for neutrons produced by protons in brass. Methods: Stage1: The Bertini and Binary nuclear models available in Geant4 were compared with published attenuation at depth of the TADE in concrete and iron. Stage2: Shielding data of the TADE in concrete was calculated for 50– 200 MeV proton beams on brass. Stage3: Shielding data from Stage2 was extrapolated for 235 MeV proton beams. This data was used in a point-line-source analytical model to calculate the ambient dose per unit therapeutic dose at two locations inside one treatment room at the Francis H Burr Proton Therapy Center. Finally, we compared these results with experimental data and full TOPAS simulations. Results: At larger angles (∼130o) the TADE in concrete calculated with the Bertini model was about 9 times larger than that calculated with the Binary model. The attenuation length in concrete calculated with the Binary model agreed with published data within 7%±0.4% (statistical uncertainty) for the deepest regions and 5%±0.1% for shallower regions. For iron the agreement was within 3%±0.1%. The ambient dose per therapeutic dose calculated with the Binary model, relative to the experimental data, was a ratio of 0.93±0.16 and 1.23±0.24 for two locations. The analytical model overestimated the dose by four orders of magnitude. These differences are attributed to the complexity of the geometry. Conclusion: The Binary and Bertini models gave comparable results, with the Binary model giving the best agreement with published data at large angle. Shielding data we calculated using the Binary model is useful for fast shielding calculations with other analytical models. This work was supported by National Cancer Institute Grant R01CA140735.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

{sup 33}S for Neutron Capture Therapy: Nuclear Data for Monte Carlo Calculations

A study of the nuclear data required for the Monte Carlo simulation of boron neutron capture therapy including the {sup 33}S isotope as an enhancer of the dose at small depths has been performed. In particular, the controversy on the available data for the {sup 33}S(n, α) cross section will be shown, which motivates new measurements. In addition to this, kerma factors for the main components of tissue are calculated with the use of fitting functions. Finally, we have applied these data to a potential neutron capture treatment with boron and sulfur addition to tissue in which part of the hydrogen atoms are replaced by deuterium, which improves the procedure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Discharge data collected within the East River for the Lawrence Berkeley National Laboratory Watershed Function Science Focus Area (water years 2015-present)

Discharge data collected at the East River in the Upper Colorado River Basin for the Lawrence Berkeley National Laboratory's Watershed Function Scientific Focus Area. Files contain instantaneous observed discharge data, corrected 10 min and mean daily discharge. Several sites also contain temperature and transducer depth. Please contact Rosemary Carroll if you have any questions or wish to access the raw data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Method for implementing depth deconvolution algorithm for enhanced thermal tomography 3D imaging

A computer-implemented method, apparatus, and computer program product implement enhanced thermal tomography three-dimensional (3D) thermal effusivity imaging. Experimental thermal imaging data is acquired. A response function is derived and a convolution formulation is constructed from the experimental thermal imaging data. A deconvolution solution procedure is implemented that includes constructing a matrix solution equation with a damping parameter, and solving the matrix solution equation with a selected number of iterations to construct a plurality of effusivity images. Using the novel depth deconvolution algorithm with experimental data acquired from a one-sided pulsed thermal-imaging system provides greater sensitivity for internal sample features substantially eliminating degradation in depth resolution.

36 MATERIALS SCIENCE↗