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DOE OSTI2016

Predictive Big Data Analytics: A Study of Parkinson’s Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations

Background A unique archive of Big Data on Parkinson’s Disease is collected, managed and disseminated by the Parkinson’s Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson’s disease (PD) risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data–large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources–all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data. Methods and Findings Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i) introduce methods for rebalancing imbalanced cohorts, (ii) utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii) generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model-based predictive approaches, which failed to generate accurate and reliable diagnostic predictions. However, the results of several machine-learning based classification methods indicated significant power to predict Parkinson’s disease in the PPMI subjects (consistent accuracy, sensitivity, and specificity exceeding 96%, confirmed using statistical n-fold cross-validation). Clinical (e.g., Unified Parkinson's Disease Rating Scale (UPDRS) scores), demographic (e.g., age), genetics (e.g., rs34637584, chr12), and derived neuroimaging biomarker (e.g., cerebellum shape index) data all contributed to the predictive analytics and diagnostic forecasting. Conclusions Model-free Big Data machine learning-based classification methods (e.g., adaptive boosting, support vector machines) can outperform model-based techniques in terms of predictive precision and reliability (e.g., forecasting patient diagnosis). We observed that statistical rebalancing of cohort sizes yields better discrimination of group differences, specifically for predictive analytics based on heterogeneous and incomplete PPMI data. UPDRS scores play a critical role in predicting diagnosis, which is expected based on the clinical definition of Parkinson’s disease. Even without longitudinal UPDRS data, however, the accuracy of model-free machine learning based classification is over 80%. The methods, software and protocols developed here are openly shared and can be employed to study other neurodegenerative disorders (e.g., Alzheimer’s, Huntington’s, amyotrophic lateral sclerosis), as well as for other predictive Big Data analytics applications.

Science & Technology - Other Topics↗

DOE OSTI2017

Experiences of Vulnerable Residential Customer Subpopulations with Critical Peak Pricing

DOE decided to co-fund ten utilities to undertake eleven experimentally-designed Consumer Behavior Studies (CBS) that proposed to examine a wide range of the topics of interest to the electric utility industry. Each chosen utility was to design, implement and evaluate their own study in order to address questions of interest both to itself and to its applicable regulatory authority, whose approval was generally necessary for the study to proceed. The DOE Office of Energy Delivery and Electricity Reliability (OE), however, did set guidelines, both in the FOA and subsequently during the contracting period, for what would constitute an acceptable study under the Grant. To assist in ensuring these guidelines were adhered to, OE requested that LBNL act as project manager for these Consumer Behavior Studies to achieve consistency of experimental design and adherence to data collection and reporting protocols across the ten utilities. As part of its role, LBNL formed technical advisory groups (TAG) to separately assist each of the utilities by providing technical assistance in all aspects of the design, implementation and evaluation of their studies. LBNL was also given a unique opportunity to perform a comprehensive, cross-study analysis that uses the customer-level interval meter and demographic data made available by these utilities due to SGIG-imposed reporting requirements, in order to analyze critical policy issues associated with AMI-enabled rates and control/information technology. LBNL will publish the results of these analyses in a series of research reports, of which this is one, that attempt to address critical policy issues relating to a variety of topics including customer acceptance, retention and load response to time-based rates and various forms of enabling control and information technologies. This report extends the existing empirical literature on the experiences of low-income customers exposed to critical peak pricing, and provides the first glimpses into the experiences of the elderly and those who reported being chronically ill. Specifically, we analyzed two of the time-based rate consumer behavior studies, which were co-funded by the Department of Energy as part of the Smart Grid Investment Grant program.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Hot Springs and Geysers: Exploring Historical and Modern Impacts of Geothermal Energy Production on Associated Natural Surface Systems and Standardizing Management Practices

Surface thermal features, most notably hot springs and geysers are increasingly being recognized for their importance to ecosystems, indigenous cultures, and in some cases agriculture, recreation, and tourism. Geothermal project development poses a potential risk to these natural features but current regulatory requirements for assessing and managing these risks during exploration, permitting and monitoring are somewhat inconsistent and unpredictable across different geothermal fields. This has resulted in uncertainty and increases in exploration risk for geothermal energy developers that have led to costly project delays, cancellations, or hesitation to commit. Varying regulatory requirements may also influence public perception, fostering confusion, distrust and ultimately opposition to geothermal projects, further contributing to project delays or cancellations. At a time when there is an increasing urgency for reliable baseload clean energy, geothermal is a net-zero, renewable solution that additionally provides access to more equitable and environmentally just clean power. Continued integration of geothermal energy into the national energy roadmap can be facilitated through consistent and predictable permitting, providing regulators the framework they need, developers a clear path forward, and transparency that the public deserves. This project, currently in its beginning phases, seeks to address this important issue by providing a technical basis from which to build a preliminary protocol for assessing and managing potential impacts from new or existing geothermal energy projects to surface thermal features and their associated ecosystems. Development of this preliminary protocol will be informed by (1) a literature review of well-documented case studies in the western U.S. and New Zealand to understand the range of conditions that exemplify geothermal-surface thermal systems; (2) development of generic illustrative conceptual-numerical models to quantify, understand, and predict the first-order controls (e.g., pressure and permeability) on surface flows; and (3) additional independent and scientifically rigorous evaluations of geothermal-surface thermal system case studies from the Basin and Range Province that incorporate publicly available data as well as data provided by industry through data-sharing agreements. Learning from the successes of the process used to develop the Induced Seismicity Management Protocol (ISMP), we ultimately aim to use these initial efforts as a springboard for establishing a surface thermal feature management working group that will work collaboratively to finalize the protocol as well as co-create recommended best practices for implementation. We envision that the working group will primarily be composed of representatives from regulatory entities, government agencies, Tribes, academia, national laboratories, and industry, and will include early and regular engagement with community organizations and environmental groups. This will help ensure broad acceptance and implementation of the protocol, which will facilitate a more consistent, predictable, and standardized regulatory process, and help to ensure that geothermal energy continues to provide a reliable source of clean energy, and a pathway to achieving greater energy equity in the U.S.

Best Practices↗

DOE OSTI2023

Enhancement of operational Flexibility of Power Plants Using IN740

Headers are crucial components within diverse industries, especially in the energy sector, as they enable the efficient transfer of fluids. The selection of materials for headers is determined by their specific applications; for example, Grade 91 and Grade 92 steels are commonly utilized. In our research, we recommend the adoption of INCONEL alloy 740 due to its exceptional robustness and heat-resistant characteristics. One critical parameter in header systems is the heat transfer coefficient, which directly influences the efficiency of heat exchange processes and can thereby impact the structural integrity of the headers. This coefficient is closely linked with factors such as the Nusselt number, which is influenced by fluid flow characteristics and thermal properties. The flow direction within headers, whether unidirectional or multidirectional—significantly affects the overall dynamics of heat transfer. This research focuses on exploring the behavior of headers, a specific pipeline system component, using ANSYS simulation software. The study aims to predict heat transfer and mechanical behavior within headers under various conditions through steady-state and transient simulations (parts 1 and 2 of the report). Key parameters such as heat transfer coefficient, velocity, and temperature are examined with the goal of optimizing header design. Part 3 of the report addresses the critical yet underexplored relationship between pressure drop and heat transfer coefficients in the transient flow regime within headers, specifically focusing on smooth horizontal circular tubes. Limited experimental work has been conducted in this area, prompting the need for comprehensive analysis. By leveraging machine learning techniques, this research aims to establish a correlation between pressure drop and heat transfer across various flow conditions, including laminar, transient, quasi-turbulent, and turbulent regimes. The data utilized for this analysis were meticulously gathered from existing literature, capturing simultaneous measurements of pressure drops and heat transfer. Part 4: In the context of power plants, header pipes are essential components that significantly influence system performance by facilitating the collection and distribution of steam. This report highlights the critical role of header pipes in enhancing reliability, efficiency, and overall power plant performance. A key aspect of this investigation is shape optimization, which aims to maximize performance while minimizing material usage. By focusing on shape optimization, this research contributes to improved efficiency and a reduced environmental footprint for power plant installations. The methodology developed in this study emphasizes optimizing header shapes to decrease reliance on expensive alloy materials and lower maintenance costs. Furthermore, a case study was conducted using a header from an operational power plant to validate the proposed optimization techniques. Finally, part 5 addresses the challenges associated with flexible operations in boiler systems, the study outlines several strategies for enhancing the durability and reliability of steam headers. Key approaches include material selection, which involves utilizing advanced materials with superior high-temperature properties and enhanced fatigue resistance to extend the lifespan of steam headers. Design modifications are also recommended, focusing on implementing changes that mitigate thermal stress and cyclic loading to reduce the likelihood of failures under varying operating conditions. Additionally, the study emphasizes the importance of regular inspection and monitoring by establishing rigorous protocols to detect early signs of damage, allowing for timely maintenance and minimizing the risks of catastrophic failures. Furthermore, operational guidelines are developed to minimize the frequency and severity of thermal transients, ensuring stable and efficient operations. Collectively, these strategies provide a robust framework for overcoming the unique challenges posed by flexible operation in boiler systems, ultimately contributing to improved reliability and performance in power plant operations. Through this comprehensive approach, the study not only enhances the understanding of pressure drop and heat transfer relationships but also promotes advancements in design and operation that will benefit the entire power generation industry.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2016

One-step facile synthesis of noble metal nanocrystals with tunable morphology in a nematic liquid crystalline medium

The present study describes in-situ synthesis of noble metal nano structures (MNCs) (Au and Ag) within a nematic liquid crystalline medium MBBA [N-(4-methoxybenzylidene)-4-butylaniline] without using any seed mediated growth protocol or without using any external stabilizing or reducing agent. Detailed Transmission Electron Microscopy (TEM) study indicates that apart from Kinetic based mechanism, the thermodynamical parameters also influence greatly the morphological evolution of these MNCs. The MNCs are of diverse shapes including nano prisms, hexagons, urchins, cubes, and rods which depend on the time of reaction and the choice of nanoparticle precursor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Fatiguing contractions increase protein S-glutathionylation occupancy in mouse skeletal muscle

Protein S-glutathionylation is an important reversible post-translational modification implicated in redox signaling. Oxidative modifications to protein thiols can alter the activity of metabolic enzymes, transcription factors, kinases, phosphatases, and the function of contractile proteins. NADPH oxidase (NOX) associated reactive oxygen species (ROS), have been implicated in this redox signaling. However, the extent to which muscle contraction induces oxidative modifications in redox sensitive thiols is not known. In this study, we performed acute fatiguing contractions using an in vivo stimulation protocol on anesthetized CB6F1 (BALB/cBy x C57BL/6) mice. Contraction force and kinetics were monitored by a force transducer throughout the 15 minutes of fatiguing stimulations. The right (stimulated) and left (unstimulated) gastrocnemius were collected 60 minutes after the last stimulation and processed for redox proteomics assay for S-glutathionylation. Using a selective reduction with a glutaredoxin enzyme cocktail and resin-assisted capture technique, we quantified the levels of site-specific protein S-glutathionylation at rest and following fatiguing contractions in gastrocnemius muscles in adult mice. Redox proteomics revealed over 2,200 sites of S-glutathionylation modifications, of which 1290 were significantly increased after fatiguing contractions. Muscle contraction leads to the greatest increase in S-glutathionylation in the mitochondria and extracellular space and the smallest increase in the nucleus. Modification of proteins throughout the muscle fiber, including those associated with metabolism, muscle contraction, and stress response, are consistent with an important role for redox control of muscle physiology and adaptive processes. This study lays the groundwork for future investigation into the altered exercise adaptation associated with chronic conditions, such as sarcopenia, the age-related loss of muscle mass and function.

muscle contraction, Post-translational modificatio↗

DOE OSTI2025

Predicting receptor-ligand pairing preferences in plant-microbe interfaces via molecular dynamics and machine learning

Microbiome assembly, structure, and dynamics significantly influence plant health. Secreted microbial signaling molecules initiate and mediate symbiosis by binding to structurally compatible plant receptors. For example, lipo-chitooligosaccharides (LCOs), produced by nitrogen-fixing rhizobial bacteria and various fungi, are recognized by plant lysin motif receptor-like kinases (LysM-RLKs), which activate the common symbiotic pathway. Accurately predicting these molecular interactions could reveal complementary signatures underlying the initial stages of endosymbiosis. Despite the breakthrough in protein-ligand structure prediction with deep learning-based tools, such as AlphaFold3, the large size and highly flexible nature of signaling compounds like LCOs present major challenges for detailed structural characterization and binding-affinity prediction. Typical structure-/physics-based methods of ligand virtual screening are designed for small, drug-like molecules, often rely on high-resolution, experimentally determined structures of the protein receptors, and rarely achieve sufficient sampling to obtain converged thermodynamic quantities with large ligands. In this study, we developed a hybrid molecular dynamics/machine learning (MD/ML) approach capable of predicting binding affinity rankings with high accuracy in systems involving large, flexible ligands, despite limited experimental structural information. Using coarse initial structural models, the predictions using the MD/ML workflow achieved strong alignment with experimental trends, particularly in the top-affinity tier for four legume LysM-RLKs (LYR3) binding to LCOs and a chitooligosaccharide. Furthermore, the MD-based conformation selection protocol provided critical structural insights into substrate specificity and binding mechanisms. This study demonstrates a powerful method to screen for challenging cognate ligand-receptors and advance our understanding of the molecular basis of microbial colonization in plants.

Lipo-chitooligosaccharides↗

DOE OSTI2014

Model-based analysis of thromboxane B{sub 2} and prostaglandin E{sub 2} as biomarkers in the safety evaluation of naproxen

The assessment of safety in traditional toxicology protocols relies on evidence arising from observed adverse events (AEs) in animals and on establishing their correlation with different measures of drug exposure (e.g., C{sub max} and AUC). Such correlations, however, ignore the role of biomarkers, which can provide further insight into the underlying pharmacological mechanisms. Here we use naproxen as a paradigm drug to explore the feasibility of a biomarker-guided approach for the prediction of AEs in humans. A standard toxicology protocol was set up for the evaluation of effects of naproxen in rat, in which four doses were tested (7.5, 15, 40 and 80 mg/kg). In addition to sparse blood sampling for the assessment of exposure, thromboxane B{sub 2} and prostaglandin E{sub 2} were also collected in satellite groups. Nonlinear mixed effects modelling was used to evaluate the predictive performance of the approach. A one-compartmental model with first order absorption was found to best describe the pharmacokinetics of naproxen. A nonlinear relationship between dose and bioavailability was observed which leads to a less than proportional increase in naproxen concentrations with increasing doses. The pharmacodynamics of TXB{sub 2} and PGE{sub 2} was described by direct inhibition models with maximum pharmacological effects achieved at doses > 7.5 mg/kg. The predicted PKPD relationship in humans was within 10-fold of the values previously published. Moreover, our results indicate that biomarkers can be used to assess interspecies differences in PKPD and extrapolated data from animals to humans. Biomarker sampling should be used systematically in general toxicity studies. - Highlights: • Prediction of a drug's safety profile from preclinical protocols remains challenging. • Pharmacokinetic measures of safe exposure (e.g., AUC) ignore the role of biomarkers. • PKPD relationships enable the evaluation of adverse events in a mechanistic manner. • Major differences exist between rats and humans in the effects of naproxen on TXB{sub 2}. • A biomarker-guided approach may facilitate the prediction of adverse events in humans.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Analysis of humidity sensitivity of silicon strip sensors for ATLAS upgrade tracker, pre- and post-irradiation

During the prototyping phase of the new ATLAS Inner-Tracker (ITk) strip sensors, a degradation of the device breakdown voltage at high humidity was observed. Although the degradation was temporary, showing a fast recovery in dry conditions, the study of the influence of humidity on the sensor performance was critical to establish counter-measures and handling protocols during production testing in order to ensure the proper performance of the upgraded detector. The work presented here has the objective to study for the first time the breakdown voltage deterioration in presence of ambient humidity of ATLAS ITk production-layout strip sensors with different surface properties, before and after proton, neutron and gamma irradiations. A study of the humidity sensitivity of miniature ATLAS ITk strip sensors, before and after proton irradiations, is also presented to compare the sensitivity of devices with different sizes. The sensors were also exposed for several days to high humidity with the aim to recreate and evaluate the influence of the detector integration environment expected during the Large Hadron Collider (LHC) Long Shutdown 3 (LS3) in 2026, where the sensors will be exposed to ambient humidity for prolonged times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2012

Antiscatter grids in mobile C-arm cone-beam CT: Effect on image quality and dose

Purpose: X-ray scatter is a major detriment to image quality in cone-beam CT (CBCT). Existing geometries exhibit strong differences in scatter susceptibility with more compact geometries, e.g., dental or musculoskeletal, benefiting from antiscatter grids, whereas in more extended geometries, e.g., IGRT, grid use carries tradeoffs in image quality per unit dose. This work assesses the tradeoffs in dose and image quality for grids applied in the context of low-dose CBCT on a mobile C-arm for image-guided surgery. Methods: Studies were performed on a mobile C-arm equipped with a flat-panel detector for high-quality CBCT. Antiscatter grids of grid ratio (GR) 6:1-12:1, 40 lp/cm, were tested in ''body'' surgery, i.e., spine, using protocols for bone and soft-tissue visibility in the thoracic and abdominal spine. Studies focused on grid orientation, CT number accuracy, image noise, and contrast-to-noise ratio (CNR) in quantitative phantoms at constant dose. Results: There was no effect of grid orientation on possible gridline artifacts, given accurate angle-dependent gain calibration. Incorrect calibration was found to result in gridline shadows in the projection data that imparted high-frequency artifacts in 3D reconstructions. Increasing GR reduced errors in CT number from 31%, thorax, and 37%, abdomen, for gridless operation to 2% and 10%, respectively, with a 12:1 grid, while image noise increased by up to 70%. The CNR of high-contrast objects was largely unaffected by grids, but low-contrast soft-tissues suffered reduction in CNR, 2%-65%, across the investigated GR at constant dose. Conclusions: While grids improved CT number accuracy, soft-tissue CNR was reduced due to attenuation of primary radiation. CNR could be restored by increasing dose by factors of {approx}1.6-2.5 depending on GR, e.g., increase from 4.6 mGy for the thorax and 12.5 mGy for the abdomen without antiscatter grids to approximately 12 mGy and 30 mGy, respectively, with a high-GR grid. However, increasing the dose poses a significant impediment to repeat intraoperative CBCT and can cause the cumulative intraoperative dose to exceed that of a single diagnostic CT scan. This places the mobile C-arm in the category of extended CBCT geometries with sufficient air gap for which the tradeoffs between CNR and dose typically do not favor incorporation of an antiscatter grid.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2019

Assessment of attenuation correction for myocardial PET imaging using combined PET/MRI

Objective: To evaluate the frequency of artifacts in MR-based attenuation correction (AC) maps and their impact on the quantitative accuracy of PET-based flow and metabolism measurements in a cohort of consecutive heart failure patients undergoing combined PET/MR imaging. Methods: Myocardial viability studies were performed in 20 patients following a dual-tracer protocol involving the assessment of myocardial perfusion ({sup 13}N-NH{sub 3}: 813 ± 86 MBq) and metabolism ({sup 18}F-FDG: 335 ± 38 MBq). All acquisitions were performed using a fully-integrated PET/MR system, with standard DIXON-attenuation correction (DIXON-AC) mapping for each PET scan. All AC maps were examined for spatial misalignment with the emission data, total lung volume, susceptibility artifacts, and tissue inversion (TI). Misalignment and susceptibility artifacts were corrected using rigid co-registration and retrospective filling of the susceptibility-induced gaps, respectively. The effects of the AC artifacts were evaluated by relative difference measures and perceived changes in clinical interpretations. Results: Average respiratory misalignment of (7 ± 4) mm of the PET-emission data and the AC maps was observed in 18 (90%) patients. Substantial changes in the lung volumes of the AC maps were observed in the test–retest analysis (ratio: 1.0 ± 0.2, range: 0.8-1.4). Susceptibility artifacts were observed in 10 (50%) patients, while six (30%) patients had TI artifacts. Average differences of 14 ± 10% were observed for PET images reconstructed with the artifactual AC maps. The combined artifact effects caused false-positive findings in three (15%) patients. Conclusion: Standard DIXON-AC maps must be examined carefully for artifacts and misalignment effects prior to AC correction of cardiac PET/MRI studies in order to avoid misinterpretation of biased perfusion and metabolism readings from the PET data.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

Experimental-based mechanistic study and optimization of hydrothermal liquefaction of anaerobic digestates

Valorization of agricultural and food waste digestates is crucial for sustainable waste management to reduce environmental impacts and improve the economics of commercial farms. Hydrothermal liquefaction (HTL) of anaerobic digestates was evaluated to recover resources by converting them into carbon-dense biocrude oil and a nutrient-rich HTL aqueous phase (HTL-AP) coproduct. The effects of HTL temperature (280–360 °C), reaction time (10–50 min), feedstock pH (2.5–8.5), digestate salt content (1–5 wt%), and digestate cellulose-to-lignin ratio (0.2–1.8) on energy and nutrient recovery were systematically investigated in a set of well-designed experiments following a half-fractional central composite protocol. Response surface analysis combined with HTL product characterization and comparative literature study produced a comprehensive reaction pathway for HTL of anaerobic digestates. Moreover, this analysis revealed the importance of acidic feedstocks (pH 3.00–5.53), high reaction temperatures (337–360 °C), and reaction times <45 or 45–50 min for digestates with Cel/Lig >1 or <1, for maximizing the energy recovered in biocrude (high carbon yield and low heteroatom content) and the amounts of P, NH 3 –N, and Mg distributed in the HTL-AP. Acidic conditions catalyzed biocrude production, inhibited the Maillard reaction (lowering the nitrogen content in biocrude), and partitioned nutrients into the HTL-AP. Higher reaction temperatures coupled with longer reaction times activated hydro-denitrogenation and deoxygenation reactions to improve biocrude quality. Finally, this work provides not only validated methods to achieve targeted resource recovery for specific feedstock compositions using HTL, but also a comprehensive mechanistic understanding of the HTL of biomass waste for controlling target product characteristics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

A round-robin gamma stereotactic radiosurgery dosimetry interinstitution comparison of calibration protocols

Purpose: Absorbed dose calibration for gamma stereotactic radiosurgery is challenging due to the unique geometric conditions, dosimetry characteristics, and nonstandard field size of these devices. Members of the American Association of Physicists in Medicine (AAPM) Task Group 178 on Gamma Stereotactic Radiosurgery Dosimetry and Quality Assurance have participated in a round-robin exchange of calibrated measurement instrumentation and phantoms exploring two approved and two proposed calibration protocols or formalisms on ten gamma radiosurgery units. The objectives of this study were to benchmark and compare new formalisms to existing calibration methods, while maintaining traceability to U.S. primary dosimetry calibration laboratory standards. Methods: Nine institutions made measurements using ten gamma stereotactic radiosurgery units in three different 160 mm diameter spherical phantoms [acrylonitrile butadiene styrene (ABS) plastic, Solid Water, and liquid water] and in air using a positioning jig. Two calibrated miniature ionization chambers and one calibrated electrometer were circulated for all measurements. Reference dose-rates at the phantom center were determined using the well-established AAPM TG-21 or TG-51 dose calibration protocols and using two proposed dose calibration protocols/formalisms: an in-air protocol and a formalism proposed by the International Atomic Energy Agency (IAEA) working group for small and nonstandard radiation fields. Each institution’s results were normalized to the dose-rate determined at that institution using the TG-21 protocol in the ABS phantom. Results: Percentages of dose-rates within 1.5% of the reference dose-rate (TG-21 + ABS phantom) for the eight chamber-protocol-phantom combinations were the following: 88% for TG-21, 70% for TG-51, 93% for the new IAEA nonstandard-field formalism, and 65% for the new in-air protocol. Averages and standard deviations for dose-rates over all measurements relative to the TG-21 + ABS dose-rate were 0.999 ± 0.009 (TG-21), 0.991 ± 0.013 (TG-51), 1.000 ± 0.009 (IAEA), and 1.009 ± 0.012 (in-air). There were no statistically significant differences (i.e., p > 0.05) between the two ionization chambers for the TG-21 protocol applied to all dosimetry phantoms. The mean results using the TG-51 protocol were notably lower than those for the other dosimetry protocols, with a standard deviation 2–3 times larger. The in-air protocol was not statistically different from TG-21 for the A16 chamber in the liquid water or ABS phantoms (p = 0.300 and p = 0.135) but was statistically different from TG-21 for the PTW chamber in all phantoms (p = 0.006 for Solid Water, 0.014 for liquid water, and 0.020 for ABS). Results of IAEA formalism were statistically different from TG-21 results only for the combination of the A16 chamber with the liquid water phantom (p = 0.017). In the latter case, dose-rates measured with the two protocols differed by only 0.4%. For other phantom-ionization-chamber combinations, the new IAEA formalism was not statistically different from TG-21. Conclusions: Although further investigation is needed to validate the new protocols for other ionization chambers, these results can serve as a reference to quantitatively compare different calibration protocols and ionization chambers if a particular method is chosen by a professional society to serve as a standardized calibration protocol.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2022

Microgrid Communications Using the Open-Source Open Field Message Bus (OpenFMB) Framework Applied to a 480V, 100kW Laboratory Microgrid

Microgrids require an extensive communication infrastructure to allow interoperability between the microgrid controller and assets. However, the lack of standardization of data structures combined with the variety of communication protocols poses several challenges to the implementation of a communication network. This paper presents an application of the open-source Open Field Message Bus (OpenFMB) framework to simplify the communication layer in microgrids. This work leverages the OpenFMB protocol translation and data model extensions to reduce the complexity in the microgrid communications. Conducted in a laboratory microgrid, the case study demonstrates how the OpenFMB provides predefined data models and simplifies the communication layer by providing information exchange between multiple legacy communication protocols.

Ferrari Maglia, Max↗

DOE OSTI2011

Potential underestimation of the internal target volume (ITV) from free-breathing CBCT

Purpose: Localization prior to delivery of SBRT to free-breathing patients is performed by aligning the planning internal target volume (ITV) from 4DCT with an on-board free-breathing cone-beam CT (FB-CBCT) image. The FB-CBCT image is assumed to also generate an ITV that captures the full range of motion, due to the acquisition spanning multiple respiratory cycles. However, the ITV could potentially be underestimated when the ratio of time spent in inspiration versus time spent in expiration (I/E ratio) deviates from unity. Therefore, the aim of this study was to investigate the effect of variable I/E ratios on the FB ITV generated from a FB-CBCT scan. Methods: This study employed both phantom and patient imaging data. For the phantom study, five periodic respiratory cycles were simulated with different I/E ratios. Six patient respiratory cycles with variable I/E ratios were also selected. All profiles were then programmed into a motion phantom for imaging and modified to exhibit three peak-to-peak motion amplitudes (0.5, 1.0, and 2.0 cm). Each profile was imaged using two spherical targets with 1.0 and 3.0 cm diameters. 2D projections were acquired with full gantry rotation of a kiloVoltage (kV) imager mounted onto the gantry of a modern linear accelerator. CBCT images were reconstructed from 2D projections using a standard filtered back-projection reconstruction algorithm. Quantitative analyses for the phantom study included computing the change in contrast along the direction of target motion as well as determining the area (which is proportional to the target volume) inside of the contour extracted using a Canny edge detector. For the patient study, projection data that were previously acquired under an investigational 4D CBCT slow-gantry imaging protocol were used to generate both FB-CBCT and 4D CBCT images. Volumes were then manually contoured from both datasets (using the same window and level) for quantitative comparison. Results: The phantom study indicated a reduction in contrast at the inferior edge of the ITV (corresponding to inspiration) as the ratio decreased, for both simulated and patient respiratory cycles. For the simulated phantom respiratory cycles, the contrast reduction of the smallest I/E ratio was 27.6% for the largest target with the smallest amplitude and 89.7% for the smallest target with the largest amplitude. For patient respiratory cycles, these numbers were 22.3% and 94.0%, respectively. The extracted area from inside of the target contours showed a decreasing trend as the I/E ratio decreased. In the patient study, the FB-CBCT ITVs of both lung tumors studied were underestimated when compared with their corresponding 4D CBCT ITV. The underestimations found were 40.1% for the smaller tumor and 24.2% for the larger tumor. Conclusions: The ITV may be underestimated in a FB-CBCT image when a patient's respiratory pattern is characterized by a disparate length of time spent in inspiration versus expiration. Missing the full target motion information during on-board verification imaging may result in localization errors.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2019

Experimental Electron Density Distribution in Actinide Compounds – an Experimental Atoms in Molecules (AIM) Approach

Understanding the basic chemistry of the actinides, in particular of uranium, is essential to address issues related to nuclear fuels, nuclear waste and environmental concerns. Atoms in general are chemically bound to their neighbors via the distribution of electrons within the intervening space. However, this only represents a small proportion of the total electrons, the others are tightly bound to the atomic nuclei and do not participate in chemical bonding. The distribution of electrons in crystalline materials may be examined using the scattering of X-rays. As all electrons scatter X-rays, obtaining the information about the bonding electrons in the presence of a large excess of “irrelevant” electrons requires extremely accurate scattering measurements. Indeed, until recently this was considered impossible for elements as heavy as uranium. In our current project we have made significant improvements in the data quality obtainable for uranium containing compounds. In order to determine the electron density distribution we fit a mathematical model describing the scattering effect to the observed scattering data. This mathematical model has a number of variable parameters that describe the radial and angular distribution of electrons around an atomic center. We have developed such a model to be particularly useful for elements as heavy as uranium. Given the best fit parameters from this model, we are able to map the electron distribution around all atoms in a chemical compound. The topology of this distribution provides us with important characteristics with regard to the chemical bonds. We have now applied these methods to several uranium compounds. In particular we have studied the bonds made by uranium to oxygen, fluorine and chlorine in a number of different environments. The experimental protocols and data analysis protocols developed during this project will permit others in the field to explore the chemical bonding of other heavy element systems. From the few compounds studied to date, we are already discovering the parameters that are characteristic of bonding in such systems, and providing essential experimental benchmarks for theoreticians.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

MO-E-17A-10: Evaluation of Body and Head Dimensions of Pediatric Patients as a Function of Age

Purpose: Phantom development in medical physics plays an important role in radiation dose assessment and image quality evaluation, and this is especially true in the pediatric patient population. The purpose of this investigation was to establish the relationship between patient age and patient size, focusing on the abdomen-pelvis and head effective diameters, for patients ranging in age from newborn to 18 years. Methods: A dose reporting tool for computed tomography systems was installed at our institution to achieve compliance with state law commencing on July 1, 2012. The software records a number of patient-specific data, and also reports CT dose metrics (CTDIvol and DLP) into the patients interpretive report. The database generated by the software was mined to determine patient effective diameter as a function of age for pediatric patients aged 0–18 years. CT protocols including abdomen-pelvis and routine head were evaluated, and specific to this study the patients age, gender and equivalent diameter were recorded. Results: Six age ranges were evaluated: A(0–3), B(4–6), C(7–9), D(10–12),E(13–15),F(16–18). For the torso in these groups based upon 694 patients, median effective diameters were 147, 167, 184, 214, 231, 246 mm, respectively. For the head (N=1833), median diameters were 143, 157, 162, 168, 174, and 174, respectively. Conclusion: A solid understanding of the approximate dimensions of pediatric patients as a function of age is useful in the development of age-based imaging protocols and dose assessments. CT dose-reporting tools generate a great deal of data with respect to body dimensions automatically. In this study, median equivalent diameters for the abdomen-pelvis and head of pediatric patients were evaluated. These data may prove useful in the development of both mathematical and physical phantoms for dosimetry and image quality assessment.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Developing Science-based fueling protocols for 250-bar hydrogen tanks onboard hydrogen ferries: Experiments and modeling

Combined modeling and experimental studies are reported of the fueling of a large (28 kg capacity) 250-bar Type IV hydrogen tank of the type being deployed on early hydrogen ferries, such as the MV Sea Change. The primary goal was to determine how such tanks can be successfully fueled with hydrogen (state of charge greater than 97%) within 45 minutes without exceeding the 82 °C temperature limit for such tanks. The modeling studies show that a gas injector is needed to avoid thermal stratification during hydrogen fueling which can result in potential hot spots. Empirically, precooling of the hydrogen to 0 °C was found to be needed in some of the cases examined, as ambient conditions greatly affected the need for a precooling to achieve the 45-minute fill time desired by end users. The experimental results afforded a calibration of the engineering model SOFIL for these large 250-bar tanks, which now enables using SOFIL to predict volume-averaged hydrogen fueling temperatures to an accuracy of ±2.7°C for these tanks. The model can therefore be used to evaluate potential scenarios for development of a standardized fueling methodology for ferries utilizing large Type-IV tanks.

08 HYDROGEN↗