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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Connecting AmeriFlux to the Globe, Extending the Partnership with Global Flux Network FLUXNET

We propose a project that will extend and expand the activities and contributions of AmeriFlux, to the global stage by working with our international partners to continue operating and expand the functioning of global FLUXNET database. One goal is to produce the next-generation FLUXNET dataset. This will be an integrated dataset on carbon, water and energy fluxes, on meteorological conditions and on the structure and function of the ecosystems; we have to potential to construct a new database, double the size of the La Thuile dataset, with over 2000 site-years of trace gas flux measurements, and supporting meteorological and site meta-data from over 400 sites world-wide. The production of the next FLUXNET database is critical to the activities of this ROSE’s solicitation because these data will drive many of the carbon cycle synthesis activities and the model parameterization and validation activities. A second goal is to build the next-generation, data-system that will house, distribute and query data and discover new information by the broader biogeoscience user community. The third goal is to use these data in synthesis activities that improve our understanding on how climate, weather, ecological, physiological and soil factors govern the exchange of carbon, water and energy between vegetation and the atmosphere at multiple time and space scales. The fourth goal is to act as a coordinator of the project to recruit data, to organize a workshop/conference and to build a community of data sharing and interaction across vast cultural spectrum of participating scientists. The rationale for proposing this work is based on the fact that the vast databases that are produced by flux networks cannot perpetuate and evolve without continued support of the intellectual activities of scientists who produce data, expert in databases, and scientists who use data for modeling. The actuality of a flux network takes human intervention to recruit data from different countries and cultures, to build trust to share data in open-access format, to support data users, and to collaborate. Specifically, we will develop an updated data portal that is easy to navigate and conducive for distributing, visualization, evaluation and discovery of the multiple types of flux and environmental data and information. We will foster collaboration and interactions with our national and international partners and the recruitment of data by: 1) continuing the periodic publication of the newsletter, FLUXLETTER; 2) by hosting an international conference; 3) by coordinating and launching multi-investigator data synthesis activities; and 4) by developing tools that coordinate the development of research papers resulting from the dataset. Data products include raw and gap-filled data at their native time steps (30 minute averages), data products that are integrated on daily and annual time scales and value added products like ecosystem respiration and canopy photosynthesis. Uncertainty analysis and quality control metrics will be produced in coordination with AmeriFlux and ICOS. We will also work with colleagues to expand the scope of FLUXNET beyond carbon dioxide and water vapor, and start archiving the growing methane flux databases that are being collected, world-wide. The interpretation of the flux data relies on good meta-data. We will work with data providers to populate and expand the meta-data archives. We will also work with collaborators to incorporate data from remote sensing products such as MODIS and Landsat, from corresponding climate and weather stations. Another goal is to incorporate new data on canopy structure, with recent LIDAR acquisitions, to populate the data archive with automated soil respiration and understory flux measurements, where available and local climate records for corresponding sites. And, we will collaborate with the TRY database, by merging flux data with plant trait information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Occupancy-Driven Stochastic Decision Framework for Ranking Commercial Building Loads

For effective integration of building operations into the evolving demand response programs of the power grid, real-time decisions concerning the use of building appliances for grid services must excel on multiple criteria, ranging from the added value to occupants' comfort to the quality of the grid services. In this paper, we present a data-driven stochastic decision-support framework to dynamically rank load control alternatives in a commercial building, addressing the needs of multiple decision criteria (e.g. occupant comfort, grid service quality) under uncertainties in occupancy patterns. We adopt a stochastic multi-criteria decision algorithm recently applied to prioritize residential on/off loads, and extend it to i) consider complex load control decisions (e.g. dimming of lights, changing zone temperature set-points) in a commercial building; and ii) systematically integrate zonal occupancy patterns to better identify short-term (and time-varying) opportunities for grid service participation. We evaluate the performance of the proposed framework for curtailment of air-conditioning, lighting, and plug-loads in a multi-zone commercial office building for a range of design choices. With the help of a prototype system that integrates an interactive \textit{Data Analytics and Visualization} frontend we demonstrate a way for the building operators to monitor and change in real-time the available flexibility in energy consumption and to develop trust in the decision recommendations by interpreting the rationale behind the ranking.

Jain, Milan↗
DOE OSTI2015

Analyzing simulation-based PRA data through traditional and topological clustering: A BWR station blackout case study

Here, dynamic probabilistic risk assessment (DPRA) methodologies couple system simulator codes (e.g., RELAP and MELCOR) with simulation controller codes (e.g., RAVEN and ADAPT). Whereas system simulator codes model system dynamics deterministically, simulation controller codes introduce both deterministic (e.g., system control logic and operating procedures) and stochastic (e.g., component failures and parameter uncertainties) elements into the simulation. Typically, a DPRA is performed by sampling values of a set of parameters and simulating the system behavior for that specific set of parameter values. For complex systems, a major challenge in using DPRA methodologies is to analyze the large number of scenarios generated, where clustering techniques are typically employed to better organize and interpret the data. In this paper, we focus on the analysis of two nuclear simulation datasets that are part of the risk-informed safety margin characterization (RISMC) boiling water reactor (BWR) station blackout (SBO) case study. We provide the domain experts a software tool that encodes traditional and topological clustering techniques within an interactive analysis and visualization environment, for understanding the structures of such high-dimensional nuclear simulation datasets. We demonstrate through our case study that both types of clustering techniques complement each other for enhanced structural understanding of the data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Discovering strongly lensed quasar candidates with catalogue-based methods from DESI Legacy Surveys

The Hubble tension, revealed by a ~5σ discrepancy between measurements of the Hubble-Lemaitre constant among observations of the early and local Universe, is one of the most significant problems in modern cosmology. In order to better understand the origin of this mismatch, independent techniques to measure H 0 , such as strong lensing time delays, are required. Notably, the sample size of such systems is key to minimising the statistical uncertainties and cosmic variance, which can be improved by exploring the datasets of large-scale sky surveys such as Dark Energy Spectroscopic Instrument (DESI). We identify possible strong lensing time-delay systems within DESI by selecting candidate multiply imaged lensed quasars from a catalogue of 24 440 816 candidate QSOs contained in the ninth data release of the DESI Legacy Imaging Surveys (DESI-LS). Using a friend-of-friends-like algorithm on spatial co-ordinates, our method generates an initial list of compact quasar groups. This list is subsequently filtered using a measure of the similarity of colours among a group’s members and the likelihood that they are quasars. A visual inspection finally selects candidate strong lensing systems based on the spatial configuration of the group members. We identified 620 new candidate multiply imaged lensed quasars (101 grade-A, 214 grade-B, 305 grade-C). This number excludes 53 known spectroscopically confirmed systems and existing candidate systems identified in other similar catalogues. When available, these new candidates will be further checked by combining the spectroscopic and photometric data from DESI.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

YOUNG STELLAR OBJECTS IN THE GOULD BELT

We present the full catalog of Young Stellar Objects (YSOs) identified in the 18 molecular clouds surveyed by the Spitzer Space Telescope “cores to disks” (c2d) and “Gould Belt” (GB) Legacy surveys. Using standard techniques developed by the c2d project, we identify 3239 candidate YSOs in the 18 clouds, 2966 of which survive visual inspection and form our final catalog of YSOs in the GB. We compile extinction corrected spectral energy distributions for all 2966 YSOs and calculate and tabulate the infrared spectral index, bolometric luminosity, and bolometric temperature for each object. We find that 326 (11%), 210 (7%), 1248 (42%), and 1182 (40%) are classified as Class 0 + I, Flat-spectrum, Class II, and Class III, respectively, and show that the Class III sample suffers from an overall contamination rate by background Asymptotic Giant Branch stars between 25% and 90%. Adopting standard assumptions, we derive durations of 0.40–0.78 Myr for Class 0 + I YSOs and 0.26–0.50 Myr for Flat-spectrum YSOs, where the ranges encompass uncertainties in the adopted assumptions. Including information from (sub)millimeter wavelengths, one-third of the Class 0 + I sample is classified as Class 0, leading to durations of 0.13–0.26 Myr (Class 0) and 0.27–0.52 Myr (Class I). We revisit infrared color–color diagrams used in the literature to classify YSOs and propose minor revisions to classification boundaries in these diagrams. Finally, we show that the bolometric temperature is a poor discriminator between Class II and Class III YSOs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Overview of New Tools to Perform Safety Analysis: BWR Station Black Out Test Case

Dynamic Probabilistic Risk Assessment (DPRA) methodologies couple system simulator codes (e.g., RELAP, MELCOR) with simulation controller codes (e.g., RAVEN, ADAPT). While system simulator codes accurately model system dynamics deterministically, simulation controller codes introduce both deterministic (e.g., system control logic, operating procedures) and stochastic (e.g., component failures, parameter uncertainties) elements into the simulation. Typically, a DPRA is performed by: 1) sampling values of a set of parameters from the uncertainty space of interest (using the simulation controller codes), and 2) simulating the system behavior for that specific set of parameter values (using the system simulator codes). For complex systems, one of the major challenges in using DPRA methodologies is to analyze the large amount of information (i.e., large number of scenarios ) generated, where clustering techniques are typically employed to allow users to better organize and interpret the data. In this paper, we focus on the analysis of a nuclear simulation dataset that is part of the Risk Informed Safety Margin Characterization (RISMC) Boiling Water Reactor (BWR) station blackout (SBO) case study. We apply a software tool that provides the domain experts with an interactive analysis and visualization environment for understanding the structures of such high-dimensional nuclear simulation datasets. Our tool encodes traditional and topology-based clustering techniques, where the latter partitions the data points into clusters based on their uniform gradient flow behavior. We demonstrate through our case study that both types of clustering techniques complement each other in bringing enhanced structural understanding of the data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Investigation of Correlation Methods for Use in Criticality Safety

Although their adoption by practitioners has been limited, the introduction of similarity indices in criticality safety was a major step forward in reducing the reliance on expert judgement in discerning applicable experiments for the validation of new appliations in criticality safety analyses. Similarity indices have been successfully employed in bias trending and data assimilation techniques, but it is often unclear which acceptance criteria should be used. In their 2004 paper, Broadhead et al. specify the most widely used similarity parameter, ck, as an acceptance cutoff at 0.9. (Broadhead et al., ”Sensitivity and Uncertainty-Based Criticality Safety Validation Techniques,” Nucl. Sci. Eng. 146, 340–366, 2004). Experiments with a ck < 0.9 are often not considered applicable for code validation. This heuristic is based on quantitative studies and engineering judgement, but in some cases, experiments with ck < 0.9 can be used to accurately estimate computational bias. This suggests that further analysis is needed to determine what components of ck are driving applicability and accuracy in bias estimation. For cases in which applicable experiments may not be available (as is the case with UF6 transport canisters), understanding what distinguishes experiments in providing adequate bias estimates aside from just the similarity index is particularly necessary. To further the goal to better interpret ck values, several visualization tools were developed to assist in the investigation of which components of ck are driving applicability.

ck↗
DOE OSTI2023

MaNGA DynPop – I. Quality-assessed stellar dynamical modelling from integral-field spectroscopy of 10K nearby galaxies: a catalogue of masses, mass-to-light ratios, density profiles, and dark matter

ABSTRACT This is the first paper in our series on the combined analysis of the Dynamics and stellar Population (DynPop) for the MaNGA survey in the final SDSS Data Release 17 (DR17). Here, we present a catalogue of dynamically determined quantities for over 10 000 nearby galaxies based on integral-field stellar kinematics from the MaNGA survey. The dynamical properties are extracted using the axisymmetric Jeans Anisotropic Modelling (JAM) method, which was previously shown to be the most accurate for this kind of study. We assess systematic uncertainties using eight dynamical models with different assumptions. We use two orientations of the velocity ellipsoid: either cylindrically aligned JAMcyl or spherically aligned JAMsph. We also make four assumptions for the models’ dark versus luminous matter distributions: (1) mass-follows-light, (2) free NFW dark halo, (3) cosmologically constrained NFW halo, (4) generalized NFW dark halo, i.e. with free inner slope. In this catalogue, we provide the quantities related to the mass distributions (e.g. the density slopes and enclosed mass within a sphere of a given radius for total mass, stellar mass, and dark matter mass components). We also provide the complete models which can be used to compute the full luminous and mass distribution of each galaxy. Additionally, we visually assess the qualities of the models to help with model selections. We estimate the observed scatter in the measured quantities which decreases as expected with improvements in quality. For the best data quality, we find a remarkable consistency of measured quantities between different models, highlighting the robustness of the results.

Astronomy & Astrophysics↗
DOE OSTI2014

SU-E-J-126: Respiratory Gating Quality Assurance: A Simple Method to Achieve Millisecond Temporal Resolution

Purpose: Low temporal latency between a gating on/off signal and a linac beam on/off during respiratory gating is critical for patient safety. Although, a measurement of temporal lag is recommended by AAPM Task Group 142 for commissioning and annual quality assurance, there currently exists no published method. Here we describe a simple, inexpensive, and reliable method to precisely measure gating lag at millisecond resolutions. Methods: A Varian Real-time Position Management™ (RPM) gating simulator with rotating disk was modified with a resistive flex sensor (Spectra Symbol) attached to the gating box platform. A photon diode was placed at machine isocenter. Output signals of the flex sensor and diode were monitored with a multichannel oscilloscope (Tektronix™ DPO3014). Qualitative inspection of the gating window/beam on synchronicity were made by setting the linac to beam on/off at end-expiration, and the oscilloscope's temporal window to 100 ms to visually examine if the on/off timing was within the recommended 100-ms tolerance. Quantitative measurements were made by saving the signal traces and analyzing in MatLab™. The on and off of the beam signal were located and compared to the expected gating window (e.g. 40% to 60%). Four gating cycles were measured and compared. Results: On a Varian TrueBeam™ STx linac with RPM gating software, the average difference in synchronicity at beam on and off for four cycles was 14 ms (3 to 30 ms) and 11 ms (2 to 32 ms), respectively. For a Varian Clinac™ 21EX the average difference at beam on and off was 127 ms (122 to 133 ms) and 46 ms (42 to 49 ms), respectively. The uncertainty in the synchrony difference was estimated at ±6 ms. Conclusion: This new gating QA method is easy to implement and allows for fast qualitative inspection and quantitative measurements for commissioning and TG-142 annual QA measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

SU-E-J-145: Geometric Uncertainty in CBCT Extrapolation for Head and Neck Adaptive Radiotherapy

Purpose: One primary limitation of using CBCT images for H'N adaptive radiotherapy (ART) is the limited field of view (FOV) range. We propose a method to extrapolate the CBCT by using a deformed planning CT for the dose of the day calculations. The aim was to estimate the geometric uncertainty of our extrapolation method. Methods: Ten H'N patients, each with a planning CT (CT1) and a subsequent CT (CT2) taken, were selected. Furthermore, a small FOV CBCT (CT2short) was synthetically created by cropping CT2 to the size of a CBCT image. Then, an extrapolated CBCT (CBCTextrp) was generated by deformably registering CT1 to CT2short and resampling with a wider FOV (42mm more from the CT2short borders), where CT1 is deformed through translation, rigid, affine, and b-spline transformations in order. The geometric error is measured as the distance map ||DVF|| produced by a deformable registration between CBCTextrp and CT2. Mean errors were calculated as a function of the distance away from the CBCT borders. The quality of all the registrations was visually verified. Results: Results were collected based on the average numbers from 10 patients. The extrapolation error increased linearly as a function of the distance (at a rate of 0.7mm per 1 cm) away from the CBCT borders in the S/I direction. The errors (μ±σ) at the superior and inferior boarders were 0.8 ± 0.5mm and 3.0 ± 1.5mm respectively, and increased to 2.7 ± 2.2mm and 5.9 ± 1.9mm at 4.2cm away. The mean error within CBCT borders was 1.16 ± 0.54mm . The overall errors within 4.2cm error expansion were 2.0 ± 1.2mm (sup) and 4.5 ± 1.6mm (inf). Conclusion: The overall error in inf direction is larger due to more large unpredictable deformations in the chest. The error introduced by extrapolation is plan dependent. The mean error in the expanded region can be large, and must be considered during implementation. This work is supported in part by Varian Medical Systems, Palo Alto, CA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A model-independent data assimilation (MIDA) module and its applications in ecology

Abstract. Models are an important tool to predict Earth system dynamics. An accurate prediction of future states of ecosystems depends on not only model structures but also parameterizations. Model parameters can be constrained by data assimilation. However, applications of data assimilation to ecology are restricted by highly technical requirements such as model-dependent coding. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module. MIDA works in three steps including data preparation, execution of data assimilation, and visualization. The first step prepares prior ranges of parameter values, a defined number of iterations, and directory paths to access files of observations and models. The execution step calibrates parameter values to best fit the observations and estimates the parameter posterior distributions. The final step automatically visualizes the calibration performance and posterior distributions. MIDA is model independent, and modelers can use MIDA for an accurate and efficient data assimilation in a simple and interactive way without modification of their original models. We applied MIDA to four types of ecological models: the data assimilation linked ecosystem carbon (DALEC) model, a surrogate-based energy exascale earth system model: the land component (ELM), nine phenological models and a stand-alone biome ecological strategy simulator (BiomeE). The applications indicate that MIDA can effectively solve data assimilation problems for different ecological models. Additionally, the easy implementation and model-independent feature of MIDA breaks the technical barrier of applications of data–model fusion in ecology. MIDA facilitates the assimilation of various observations into models for uncertainty reduction in ecological modeling and forecasting.

58 GEOSCIENCES↗
DOE OSTI2014

SU-E-J-231: Comparison of 3D Angiogram and MRI in Delineating the AVM Target for Frameless Stereotactic Radiosurgery

Purpose: Stereotactic radiation therapy (SRT) provides an excellent alternative to embolization and surgical excision for the management of appropriately selected cerebral arteriovenous malformations (AVMs). The currently accepted standard for delineating AVMs is planar digital subtraction angiography (DSA). DSA can be used to acquire a 3D data set that preserves osseous structures (3D-DA) at the time of the angiography for SRT planning. Magnetic resonance imaging (MRI) provides an alternative noninvasive method of visualizing the AVM nidus with comparable spatial resolution. We utilized 3D-DA and T1 post-contrast MRI data to evaluate the differences in SRT target volumes. Methods: Four patients underwent 3D-DA and high-resolution MRI. 3D T1 post-contrast images were obtained in all three reconstruction planes. A planning CT was fused with MRI and 3D-DA data sets. The AVMs were contoured utilizing one of the image sets at a time. Target volume, centroid, and maximum and minimum dimensions were analyzed for each patient. Results: Targets delineated using post-contrast MRI demonstrated a larger mean volume. AVMs >2 cc were found to have a larger difference between MRI and 3D-DA volumes. Larger AVMs also demonstrated a smaller relative uncertainty in contour centroid position (1 mm). AVM targets <2 cc had smaller absolute differences in volume, but larger differences in contour centroid position (2.5 mm). MRI targets demonstrated a more irregular shape compared to 3D-DA targets. Conclusions: Our preliminary data supports the use of MRI alone to delineate AVM targets >2 cc. The greater centroid stability for AVMs >2 cc ensures accurate target localization during image fusion. The larger MRI target volumes did not result in prohibitively greater volumes of normal brain tissue receiving the prescription dose. The larger centroid instability for AVMs <2 cc precludes the use of MRI alone for target delineation. We recommend incorporating a 3D-DA for these patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Conditional Tree Reduction in the ADAPT Framework

Probabilistic Risk Assessment (PRA) uses fault tree/event tree analysis to evaluate the environmental impacts of nuclear power plants due to internal or external initiating events. In a fault tree, basic failure events are assembled using primarily And/Or logic to determine the combinations of failures that lead to failure of the system as a whole. An event tree is forward-facing, and begins with a single initiating event. From there the analysis considers what event may occur next, and branches out among the possible configurations of occurrence and non-occurrence of that event. This branching continues until end states are reached. End states may include a safe and stable configuration of the plant, or any number of differing failure states. Both fault and event trees require basic event probabilities as inputs to provide insight on the likelihood of different outcomes. PRA has been applied to nuclear power plants as an analysis tool since the 1975 Reactor Safety Study. In a traditional PRA, the order of events is prescribed by the analyst and each event is typically a binary aleatory uncertainty: occurrence or non-occurrence. Discrete dynamic event tree (DDET) analysis eliminates this subjectivity in ordering of events by using the output of a dynamic system model (simulator) to inform the branching. Branching conditions are triggered by the existence of a relevant plant state in the code, and therefore only occur as physically appropriate. The DDET approach also allows consideration of both epistemic and aleatory uncertainties on a phenomenologically and stochastically consistent platform. A DDET may be orders of magnitude larger than a traditional event tree for the same initiating event, as more of the uncertainty space is likely to be explored and the tree does not require manual assembly. Because of the size, manual inspection of the entire DDET is often infeasible. This problem may be approached from the front by reducing the number of sampled branching values or by online pruning of the tree, thus reducing the total number of branches. Utilizing post-processing techniques to draw actionable insights via clustering has also been proposed. One post-processing tool to reduce the DDET according to user-defined rules has been recently implemented in the Analysis of Dynamic Accident Progression Trees (ADAPT) DDET driver code. The tool creates a 'slice' of the DDET comprised of the set of branches that meet a set of user-input rules, for immediate visualization or for further calculations conditional on the rules being met. This extension is expected to ease analysis of the results of large and complex DDETs, leading to greater applicability of DDETs in PRA. It should be emphasized that this tool is a visualization aide and does not impact the theoretical basis of the DDET approach. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Towards resolving protein structures at the atomic scale using atom probe tomography

In the field of Structural Biology, Atom Probe Tomography (APT) is in the nascent stages of development wherein coarse-grained visuals of proteins have been captured. The characterization of organic samples or biomolecules through the technique is currently limited to the detection of a few dominant signatures. The problem of indecipherable characterization can inherently be traced back to multiple forms of technique-specific responses to organic samples and consequent triggers leading to organic-sample and sample-medium interactions. While it is possible for captured manifestations of protein reconstructions to seemingly appear intact from a basic visual purview, the parameter-protein associative responses throughout the structure as a direct consequence of the inherent workings of the technique (until harmonized with organic sample complexity and behavior) and field evaporation-based factors make non-aberrative atomic associations infeasible. The work focused on identifying and theorizing the (above stated and other) fundamental mechanisms that stronghold the study of intricate atomic to higher order associations in proteins through APT. Attempts at structure elucidation of the cryogenic sample under study, through indirect associations (and methods) based on other imaging techniques, further revealed the distinct and highly distortive nature at the atomic scale deterring structural tunability and thus characterization of APT based cryogenic samples under analysis. As a direct counter to the atomic scale characterization problem, by taking the experiment-specific uncertainties, and probable APT-centric organic sample-based variabilities into account, a basic result is extracted and presented. Through mass-spectrometric and computational analysis, specific individual amino acids (Sulfur-containing protein-bound amino acids) in proteins and aspects of protein structure (probable backbone fragments, partial sequence - partial backbone portions) have been identified and characterized. Under analysis considerations, a few of the simplest known and easily inferable segments that favor structural deteriorations in the reconstructions are stated. Additionally, to overcome technique-specific deterrents to the characterization of biomolecules in cryogenic sample medium, the development of a protein-labeling strategy tailored to APT is suggested.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Hydrogen density mapping in biomolecular crystals through dynamic nuclear polarization

Many fundamental biological processes, including those in photosynthetic reaction centers and enzyme active sites, involve charge and energy transfer, bond cleavage, protonation and hydrogen bonding. Because H atoms play such central roles in these reactions, accurately determining their positions is essential. Yet, conventional X-ray crystallography primarily resolves the heavy atoms in biological structures and provides limited insight into hydrogen, even at atomic resolution. Neutron macromolecular crystallography (NMC) overcomes this limitation by offering exceptional sensitivity to hydrogen and deuterium. Here, we present a theoretical framework for the development of dynamic nuclear polarization NMC (DNP-NMC) techniques, which exploit the alignment of neutron and proton nuclear spins to enhance and tune the hydrogen signal contribution. The DNP-NMC approach advances the resolution of H atoms within biomolecular crystals, whether bound to protein residues or present in solvent. The method establishes key relationships for the coherent structure factor of polarized neutron scattering from hydrogenous matter. It theoretically achieves full accuracy in phase reconstruction and offers a path to improve neutron structure determination, achieving accuracies exceeding ≳80% by incorporating titration states. Using a variant of the hybrid input/output phase-retrieval algorithm, it allows recovery of the hydrogen density with ≳90% phase accuracy. In conclusion, we further discuss sources of experimental uncertainty for the upcoming DNP-enabled, quasi-Laue IMAGINE-X experiment at Oak Ridge National Laboratory's High Flux Isotope Reactor.

dynamic nuclear polarization↗
DOE OSTI2015

Objective assessment in digital images of skin erythema caused by radiotherapy

Purpose: Skin toxicity caused by radiotherapy has been visually classified into discrete grades. The present study proposes an objective and continuous assessment method of skin erythema in digital images taken under arbitrary lighting conditions, which is the case for most clinical environments. The purpose of this paper is to show the feasibility of the proposed method. Methods: Clinical data were gathered from six patients who received carbon beam therapy for lung cancer. Skin condition was recorded using an ordinary compact digital camera under unfixed lighting conditions; a laser Doppler flowmeter was used to measure blood flow in the skin. The photos and measurements were taken at 3 h, 30, and 90 days after irradiation. Images were decomposed into hemoglobin and melanin colors using independent component analysis. Pixel values in hemoglobin color images were compared with skin dose and skin blood flow. The uncertainty of the practical photographic method was also studied in nonclinical experiments. Results: The clinical data showed good linearity between skin dose, skin blood flow, and pixel value in the hemoglobin color images; their correlation coefficients were larger than 0.7. It was deduced from the nonclinical that the uncertainty due to the proposed method with photography was 15%; such an uncertainty was not critical for assessment of skin erythema in practical use. Conclusions: Feasibility of the proposed method for assessment of skin erythema using digital images was demonstrated. The numerical relationship obtained helped to predict skin erythema by artificial processing of skin images. Although the proposed method using photographs taken under unfixed lighting conditions increased the uncertainty of skin information in the images, it was shown to be powerful for the assessment of skin conditions because of its flexibility and adaptability.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Review of NDE Methods for Detection and Monitoring of Atmospheric SCC in Welded Canisters for the Storage of Used Nuclear Fuel

Dry cask storage systems (DCSSs) for used nuclear fuel (UNF) were originally envisioned for storage periods of short duration (~ a few decades). However, uncertainty challenges the opening of a permanent repository for UNF implying that UNF will need to remain in dry storage for much longer durations than originally envisioned (possibly for centuries). Thus, aging degradation of DCSSs becomes an issue that may not have been sufficiently considered in the design phase and that can challenge the efficacy of very long-term storage of UNF. A particular aging degradation concern is atmospheric stress corrosion cracking (SCC) of DCSSs located in marine environments. In this report, several nondestructive (NDE) methods are evaluated with respect to their potential for effective monitoring of atmospheric SCC in welded canisters of DCSSs. Several of the methods are selected for evaluation based on their usage for in-service inspection applications in the nuclear power industry. The technologies considered include bulk ultrasonic techniques, acoustic emission, visual techniques, eddy current, and guided ultrasonic waves.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

A Review of NDE Methods for Detecting and Monitoring of Atmospheric SCC in Dry Cask Storage Canisters for Used Nuclear Fuel

Dry cask storage systems (DCSSs) for used nuclear fuel (UNF) were originally envisioned for storage periods of short duration (~ a few decades). However, uncertainty challenges the opening of a permanent repository for UNF implying that UNF will need to remain in dry storage for much longer durations than originally envisioned (possibly for centuries). Thus, aging degradation of DCSSs becomes an issue that may not have been sufficiently considered in the design phase and that can challenge the efficacy of very long-term storage of UNF. A particular aging degradation concern is atmospheric stress corrosion cracking (SCC) of DCSSs located in marine environments. In this report, several nondestructive (NDE) methods are evaluated with respect to their potential for effective monitoring of atmospheric SCC in welded canisters of DCSSs. Several of the methods are selected for evaluation based on their usage for in-service inspection applications in the nuclear power industry. The technologies considered include bulk ultrasonic techniques, acoustic emission, visual techniques, eddy current, and guided ultrasonic waves.

Atmospheric Stress Corrosion Cracking↗