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At least 991 records · Page 55

SU-G-IeP3-05: Effects of Image Receptor Technology and Dose Reduction Software On Radiation Dose Estimates for Fluoroscopically-Guided Interventional (FGI) Procedures

Purpose: To investigate the effects of image receptor technology and dose reduction software on radiation dose estimates for most frequently performed fluoroscopically-guided interventional (FGI) procedures at a tertiary health care center. Methods: IRB approval was obtained for retrospective analysis of FGI procedures performed in the interventional radiology suites between January-2011 and December-2015. This included procedures performed using image-intensifier (II) based systems which were subsequently replaced, flat-panel-detector (FPD) based systems which were later upgraded with ClarityIQ dose reduction software (Philips Healthcare) and relatively new FPD system already equipped with ClarityIQ. Post procedure, technologists entered system-reported cumulative air kerma (CAK) and kerma-area product (KAP; only KAP for II based systems) in RIS; these values were analyzed. Data pre-processing included correcting typographical errors and cross-verifying CAK and KAP. The most frequent high and low dose FGI procedures were identified and corresponding CAK and KAP values were compared. Results: Out of 27,251 procedures within this time period, most frequent high and low dose procedures were chemo/immuno-embolization (n=1967) and abscess drainage (n=1821). Mean KAP for embolization and abscess drainage procedures were 260,657, 310,304 and 94,908 mGycm{sup 2}, and 14,497, 15,040 and 6307 mGycm{sup 2} using II-, FPD- and FPD with ClarityIQ- based systems, respectively. Statistically significant differences were observed in KAP values for embolization procedures with respect to different systems but for abscess drainage procedures significant differences were only noted between systems with FPD and FPD with ClarityIQ (p<0.05). Mean CAK reduced significantly from 823 to 308 mGy and from 43 to 21 mGy for embolization and abscess drainage procedures, respectively, in transitioning to FPD systems with ClarityIQ (p<0.05). Conclusion: While transitioning from II- to FPD- based systems was not associated with dose reduction for the most frequently performed FGI procedures, substantial dose reduction was noted with relatively newer systems and dose reduction software.

60 APPLIED LIFE SCIENCES↗

Stochastic joint inversion of hydrogeophysical data for salt tracer test monitoring and hydraulic conductivity imaging

The assessment of hydraulic conductivity of heterogeneous aquifers is a difficult task using traditional hydrogeological methods (e.g., steady state or transient pumping tests) due to their low spatial resolution. Geophysical measurements performed at the ground surface and in boreholes provide additional information for increasing the resolution and accuracy of the inverted hydraulic conductivity field. We used a stochastic joint inversion of Direct Current (DC) resistivity and Self-Potential (SP) data plus in situ measurement of the salinity in a downstream well during a synthetic salt tracer experiment to reconstruct the hydraulic conductivity field between two wells. The pilot point parameterization was used to avoid over-parameterization of the inverse problem. Bounds on the model parameters were used to promote a consistent Markov chain Monte Carlo sampling of the model parameters. To evaluate the effectiveness of the joint inversion process, we compared 8 cases in which the geophysical data are coupled or not to the in situ sampling of the salinity to map the hydraulic conductivity. We first tested the effectiveness of the inversion of each type of data alone (concentration sampling, self-potential, and DC resistivity), and then we combined the data two by two. We finally combined all the data together to show the value of each type of geophysical data in the joint inversion process because of their different sensitivity map. We also investigated a case in which the data were contaminated with noise and the variogram unknown and inverted stochastically. The results of the inversion revealed that incorporating the self-potential data improves the estimate of hydraulic conductivity field especially when the self-potential data were combined to the salt concentration measurement in the second well or to the time-lapse cross-well electrical resistivity data. Various tests were also performed to quantify the uncertainty in the inverted hydraulic conductivity field.

54 ENVIRONMENTAL SCIENCES↗

Classification of machine learning frameworks for data-driven thermal fluid models

Thermal fluid processes are inherently multi-physics and multi-scale, involving mass-momentum-energy transport phenomena at multiple scales. Thermal fluid simulation (TFS) is based on solving conservative equations, for which – except for “first-principles” direct numerical simulation – closure relations (CRs) are required to provide microscopic interactions or so-called sub-grid-scale physics. In practice, TFS is realized through reduced-order modeling, and its CRs as low-fidelity models can be informed by observations and data from relevant and adequately evaluated experiments and high-fidelity simulations. This paper is focused on data-driven TFS models, specifically on their development using machine learning (ML). Five ML frameworks are introduced including physics-separated ML (PSML or Type I ML), physics-evaluated ML (PEML or Type II ML), physics-integrated ML (PIML or Type III ML), physics-recovered (PRML or Type IV ML), and physics-discovered ML (PDML or Type V ML). The frameworks vary in their performance for different applications depending on the level of knowledge of governing physics, source, type, amount and quality of available data for training. Notably, outlined for the first time in this paper, Type III models present stringent requirements on modeling, substantial computing resources for training, and high potential in extracting value from “big data” in thermal fluid research. Here the current paper demonstrates and investigates ML frameworks in three examples. First, we utilize the heat diffusion equation with a nonlinear conductivity model formulated by convolutional neural networks (CNNs) and feedforward neural networks (FNNs) to illustrate the applications of Type I, Type II, Type III, and Type V ML. The results indicate a preference for Type II ML under deficient data support. Type III ML can effectively utilize field data, potentially generating more robust predictions than Type I and Type II ML. CNN-based closures exhibit more predictability than FNN-based closures, but CNN-based closures require more training data to obtain accurate predictions. Second, we illustrate how to employ Type I ML and Type II ML frameworks for data-driven turbulence modeling using reference works. Third, we demonstrate Type I ML by building a deep FNN-based slip closure for two-phase flow modeling. The results show that deep FNN-based closures exhibit a bounded error in the prediction domain.

42 ENGINEERING↗

First STAX detector installation at the National Institute for Radioelements (IRE)

The Source Term Analysis of Xenon (STAX) project has been installing stack detectors at medical isotope production facilities to measure radioxenon emissions to investigate the effect of radioxenon releases on nuclear explosion monitoring. This paper outlines the installation of the first STAX detection system at the National Institute for Radioelements (IRE) in Fleurus, Belgium which has been operating for over three years and transferring collected data to the STAX repository. Information about the equipment installed, the data flow established, and calculations for determination of radioxenon releases from the facility are presented. Further. data quality was investigated to confirm values reported by STAX automated data processing and in a comparison of collected STAX data with data collected by IRE for regulatory reporting.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-E-T-111: An Iterative Approach to Modelling Dosimetric Properties of a Varian MLC

Purpose: In effort to efficiently and accurately model MLC parameters for use in Varian Eclipse treatment planning system (TPS), an iterative technique for characterizing the dosimetric properties of MLCs has been developed. Methods: The initial characterization of the dosimetric leaf gap (DLG) and MLC transmission was performed using varied sizes of moving gaps and transmission measurements through central axis of the radiation beam. These values were determined during the initial data collection. After the initial values were determined and entered into the TPS, two plans were calculated to test the veracity of DLG and transmission independently. The plan used to determine the DLG has openings of varied sizes which are affected differently by the DLG. A large field uniform fluence that required a MLC carriage shift was used to determine the transmission value independent of DLG. After characterizing the dosimetric properties of the MLC independently, clinical IMRT plans were tested and used to tweak the final values. Results: This approach to modelling MLC dosimetric properties was employed for: standard 120 leaf MLC (SDMLC) and 120 leaf high definition MLC (HDMLC). Both types were successfully commissioned, tested, and approved for clinical use on 4 SDMLC machines and 2 HDMLC machines. The pass rate of clinical IMRT plans was 96.9% for 6MV and 98.3% for 10MV for SDMLC and 96.3% for 6MV, 96.5% for 6FFF, and 97.5% for 10FFF for HDMLCs using MapCheck2 with gamma analysis of 2%/2mm and 10% threshold. The final DLG and transmission parameters for 6X were 0.5mm and 0.01, and 1.35mm and 0.02 for HD and SD MLCs respectively. Conclusion: This iterative approach of determining dosimetric properties of MLCs is viable for both SDMLC and HDMLC and multiple energies. This approach accurately and efficiently determines the values needed for commissioning MLCs when they are employed for modulated therapies.

60 APPLIED LIFE SCIENCES↗

Advanced Code for Photocathode Design

The Phase I activity demonstrated that PhotoQE could be upgraded and modified to allow input using a graphical user interface. Specific calls to platform-dependent (e.g. IMSL) function calls were removed, and Fortran77 components were rewritten for Fortran95 compliance. The subroutines, specifically the common block structures and shared data parameters, were reworked to allow the GUI to update material parameter data, and the system was targeted for desktop personal computer operation. The new structures overcomes the previous rigid and unmodifiable library structures by implementing new, materials library data sets and repositioning the library values to external files. Material data may originate from published literature or experimental measurements. Further optimization and restructuring would allow custom and specific emission models for beam codes that rely on parameterized photoemission algorithms. These would be based on simplified and parametric representations updated and extended from previous versions (e.g., Modified Fowler-Dubridge, Modified Three-Step, etc.).

43 PARTICLE ACCELERATORS↗

Data acquisition and processing history for the Explorer 33 (AIMP-D) satellite

The quality control monitoring system, using accounting and quality control data bases, made it possible to perform an in-depth analysis. Results show that the percentage of useable data files for experimenter analysis was 97.7%; only 0.4% of the data sequences supplied to the experimenter exhibited missing data. The 50 percentile probability delay values (referenced to station record data) indicate that the analog tapes arrived within 11 days, the data were digitized within 4.2 weeks, and the experimenter tapes were delivered in 8.95 weeks or less.

Karras, T. J.↗

An expert system shell for inferring vegetation characteristics: Atmospheric techniques (Task G)

The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. The VEG Subgoals have been reorganized into categories. A new subgoal category 'Atmospheric Techniques' containing two new subgoals has been implemented. The subgoal Atmospheric Passes allows the scientist to take reflectance data measured at ground level and predict what the reflectance values would be if the data were measured at a different atmospheric height. The subgoal Atmospheric Corrections allows atmospheric corrections to be made to data collected from an aircraft or by a satellite to determine what the equivalent reflectance values would be if the data were measured at ground level. The report describes the implementation and testing of the basic framework and interface for the Atmospheric Techniques Subgoals.

Harrison, P. Ann↗

Observations and Modeling of the Transient General Circulation of the North Pacific Basin

The objective of this study was to clarify the role that interstellar-cloud chemistry played in forming the population of organic molecules presently found in carbonaceous meteorites. This goal was to be achieved by means of defining the isotopic components present in organic and related phases in the meteorites and thereby identify the processes and source reservoirs involved in organic synthesis in the early solar system. Isotopic analysis of separated amino acids from the Murchison meteorite yielded results that are complex and not fully interpretable at this time. Substantial inter-acid variability in D/H ratio was observed, some but not all of which could be attributed to exchange with terrestrial hydrogen. Pronounced, though smaller, variability was also found for N-15/N-14 ratios. For both D/H and N-15/N-14 data, observed meteoritic values were substantially greater than found in terrestrial materials, providing a robust constraint on degrees of possible terrestrial contamination. Also, C-13/C-12 ratios, though falling within the range of data found on earth, significantly exceeded those characteristic of naturally occurring terrestrial amino acids. Inter-acid variability in C-13/C-12 ratios was muted relative to that observed for D/H and N-15/N-14 but still lay well outside of experimental uncertainty. No systematic relationship could be observed between variations in H, C and N isotopes. Two anomalous components were also found during the course of this study. A highly (greater than 6% relative to terrestrial) N-15-depleted, N-rich compound, which has not yet been identified, co-eluted with some amino acids. Clearly the Murchison meteorite sampled nitrogen from a number of highly diverse isotopic reservoirs. In fact, from this and related studies, it is now apparent that the distribution of nitrogen isotopes in the primitive solar system was extremely inhomogeneous. The second anomalous result obtained in the present study was for an extract of 'ammonia' from Murchison. It should be noted that this sample consisted of ammonia that was probably derived from a number of different compounds present in the meteorite itself, possibly including amines and amides, as well as ammonia sensu strictu and ammonium slats. However, the significance of this analysis is that the N-15/N-14 ratio measured was much lower than those found for the meteoritic amino acids (+2% vs around + 9% relative to terrestrial). This raises an important question concerning the source of the ammonia that was involved in synthesis of the amino acids. This issue needs to be explored further.

Kerridge, John F.↗

Base Flow and Heat Transfer Characteristics of a Four-Nozzle Clustered Rocket Engine: Effect of Nozzle Pressure Ratio

The base pressure and heating characteristics of a four-nozzle clustered rocket configuration is studied numerically with the aid of OVERFLOW Navier-Stokes code. A pressure ratio (chamber pressure to freestream static pressure) range of 990 to 5,920 and a freestream Mach number range of 2.5 to 3.5 are studied. The qualitative trends of decreasing base pressure with increasing pressure ratio and increasing base heat flux with increasing pressure ratio are correctly predicted. However, the predictions for base pressure and base heat flux show deviations from the wind tunnel data. The differences in absolute values between the computation and the data are attributed to factors such as perfect gas (thermally and calorically perfect) assumption, turbulence model inaccuracies in the simulation, and lack of grid adaptation.

Nallasamy, R.↗

Test Data Monitor

The National Security Campus (NSC) collects a large amount of test data used The National Security Campus (NSC) collects a large amount of test data used to accept high value and high rigor product. The data has been used historically to support root cause analysis when anomalies are detected in down-stream processes. The opportunity to use the data for predictive failure analysis however, had never been exploited. The primary goal of the Test Data Monitor (TDM) software is to provide automated capabilities to analyze data in near-real-time and report trends that foreshadow actual product failures. To date, the aerospace industry as a whole is challenged at utilizing collected data to the degree that modern technology allows. As a result of the innovation behind TDM, Honeywell is able to monitor millions of data points through a multitude of SPC algorithms continuously and autonomously so that our personnel resources can more efficiently and accurately direct their attention to suspect processes or features. TDM’s capabilities have been recognized by our U.S. Department of Energy National Nuclear Security Administration (NNSA) sponsor for potential use at other sites within the NNSA. This activity supports multiple initiatives including expectations of the NNSA and broader corporate goals that center around data-based quality controls on production.

Bosas, Joseph↗

The Geothermal Data Repository: Five Years of Open Geothermal Data, Benefits to the Community: Preprint

In the five years since its inception, the Department of Energy's (DOE) Geothermal Data Repository (GDR) has grown from the simple idea of storing public data in a centralized location to a valuable tool at the center of the DOE open data movement where it is providing a tangible benefit to the geothermal scientific community. Throughout this time, the GDR project team has been working closely with the community to refine the data submission process, improve the quality of submitted data, and embrace modern proper data management strategies to maximize the value and utility of submitted data. This paper explores some of the motivations behind various improvements to the GDR over the last 5 years, changes in data submission trends, and the ways in which these improvements have helped to drive research, fuel innovation, and accelerate the adoption of geothermal technologies.

15 GEOTHERMAL ENERGY↗

The Geothermal Data Repository: Five Years of Open Geothermal Data, Benefits to the Community

In the five years since its inception, the Department of Energy's (DOE) Geothermal Data Repository (GDR) has grown from the simple idea of storing public data in a centralized location to a valuable tool at the center of the DOE open data movement where it is providing a tangible benefit to the geothermal scientific community. Throughout this time, the GDR project team has been working closely with the community to refine the data submission process, improve the quality of submitted data, and embrace modern proper data management strategies to maximize the value and utility of submitted data. This paper explores some of the motivations behind various improvements to the GDR over the last 5 years, changes in data submission trends, and the ways in which these improvements have helped to drive research, fuel innovation, and accelerate the adoption of geothermal technologies.

15 GEOTHERMAL ENERGY↗

Methodology for Generating Covariance Data of Thermal Neutron Scattering Cross Sections

This paper details and implements a framework for evaluating thermal neutron scattering cross sections that provide S(α,β) data and covariance data for hydrogen in light water. This methodology involves perturbing model parameters of molecular dynamics potentials and fitting the simulation results to experimental data. The framework is general and can be applied to any material or simulation method. The fit is made using the Unified Monte Carlo method to experimentally measure double-differential scattering cross sections of light water at the Spallation Neutron Source at Oak Ridge National Laboratory. Mean values and covariance data were generated for model parameters, phonon density of states, double-differential cross sections, and total scattering cross sections. These posterior parameter values were very similar to their prior values with a maximum relative error of 0.54%. This falls within in the Unified Monte Carlo–calculated uncertainties on the order of 2.7%. Additionally, posterior double-differential cross sections agree favorably with ENDF/B-VIII.0 cross sections. The new thermal scattering law was tested by comparing it against benchmarks from the International Criticality Safety Benchmark Evaluation Project Handbook, which showed a slight improvement over the ENDF/B-VIII.0 library. Additionally, the covariance matrix of the phonon density of states was validated to confirm that the spread of k eff from the density of states used to generate the covariance matrix was similar to the spread of k eff from the density of states of the sampled covariance matrix.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Estimating vegetative biomass from LANDSAT-1 imagery for range management

Evaluation of LANDSAT-1, band 5 data for use in estimation of vegetative biomass for range management decisions was carried out for five selected range sites in the Sandhills region of Nebraska. Analysis of sets of optical density-vegetative biomass data indicated that comparisons of biomass estimation could be made within one frame but not between frames without correction factors. There was high correlation among sites within sets of radiance value-vegetative biomass data and also between sets, indicating comparisons of biomass could be made within and between frames. Landsat-1 data are shown to be a viable alternative to currently used methods of determining vegetative biomass production and stocking rate recommendations for Sandhills rangeland.

Seevers, P. M.↗

Display of scientific data structures for algorithm visualization

We present a technique for defining graphical depictions for all the data types defined in an algorithm. The ability to display arbitrary combinations of an algorithm's data objects in a common frame of reference, coupled with interactive control of algorithm execution, provides a powerful way to understand algorithm behavior. Type definitions are constrained so that all primitive values occurring in data objects are assigned scalar types. A graphical display, including user interaction with the display, is modeled by a special data type. Mappings from the scalar types into the display model type provide a simple user interface for controlling how all data types are depicted, without the need for type-specific graphics logic.

Hibbard, William↗

Development and Testing of Neutron Cross Section Covariance Data for SCALE 6.2

Neutron cross-section covariance data are essential for many sensitivity/uncertainty and uncertainty quantification assessments performed both within the TSUNAMI suite and more broadly throughout the SCALE code system. The release of ENDF/B-VII.1 included a more complete set of neutron cross-section covariance data: these data form the basis for a new cross-section covariance library to be released in SCALE 6.2. A range of testing is conducted to investigate the properties of these covariance data and ensure that the data are reasonable. These tests include examination of the uncertainty in critical experiment benchmark model k eff values due to nuclear data uncertainties, as well as similarity assessments of irradiated pressurized water reactor (PWR) and boiling water reactor (BWR) fuel with suites of critical experiments. The contents of the new covariance library, the testing performed, and the behavior of the new covariance data are described in this paper. The neutron cross-section covariances can be combined with a sensitivity data file generated using the TSUNAMI suite of codes within SCALE to determine the uncertainty in system k eff caused by nuclear data uncertainties. The Verified, Archived Library of Inputs and Data (VALID) maintained at Oak Ridge National Laboratory (ORNL) contains over 400 critical experiment benchmark models, and sensitivity data are generated for each of these models. The nuclear data uncertainty in k eff is generated for each experiment, and the resulting uncertainties are tabulated and compared to the differences in measured and calculated results. The magnitude of the uncertainty for categories of nuclides (such as actinides, fission products, and structural materials) is calculated for irradiated PWR and BWR fuel to quantify the effect of covariance library changes between the SCALE 6.1 and 6.2 libraries. One of the primary applications of sensitivity/uncertainty methods within SCALE is the assessment of similarities between benchmark experiments and safety applications. This is described by a c k value for each experiment with each application. Several studies have analyzed typical c k values for a range of critical experiments compared with hypothetical irradiated fuel applications. The c k value is sensitive to the cross-section covariance data because the contribution of each nuclide is influenced by its uncertainty; large uncertainties indicate more likely bias sources and are thus given more weight. Changes in c k values resulting from different covariance data can be used to examine and assess underlying data changes. These comparisons are performed for PWR and BWR fuel in storage and transportation systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Aerosol-Induced Radiative Flux Changes Off the United States Mid-Atlantic Coast: Comparison of Values Calculated from Sunphotometer and In Situ Data with Those Measured by Airborne Pyranometer

The Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX) measured a variety of aerosol radiative effects (including flux changes) while simultaneously measuring the chemical, physical, and optical properties of the responsible aerosol particles. Here we use TARFOX-determined aerosol and surface properties to compute shortwave radiative flux changes for a variety of aerosol situations, with midvisible optical depths ranging from 0.06 to 0.55. We calculate flux changes by several techniques with varying degrees of sophistication, in part to investigate the sensitivity of results to computational approach. We then compare computed flux changes to those determined from aircraft measurements. Calculations using several approaches yield downward and upward flux changes that agree with measurements. The agreement demonstrates closure (i.e. consistency) among the TARFOX-derived aerosol properties, modeling techniques, and radiative flux measurements. Agreement between calculated and measured downward flux changes is best when the aerosols are modeled as moderately absorbing (midvisible single-scattering albedos between about 0.89 and 0.93), in accord with independent measurements of the TARPOX aerosol. The calculated values for instantaneous daytime upwelling flux changes are in the range +14 to +48 W/sq m for midvisible optical depths between 0.2 and 0.55. These values are about 30 to 100 times the global-average direct forcing expected for the global-average sulfate aerosol optical depth of 0.04. The reasons for the larger flux changes in TARFOX include the relatively large optical depths and the focus on cloud-free, daytime conditions over the dark ocean surface. These are the conditions that produce major aerosol radiative forcing events and contribute to any global-average climate effect.

Russell, P. B.↗