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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Experimental evaluation and basis function optimization of the spatially variant image-space PSF on the Ingenuity PET/MR scanner

Purpose: The Ingenuity time-of-flight (TF) PET/MR is a recently developed hybrid scanner combining the molecular imaging capabilities of PET with the excellent soft tissue contrast of MRI. It is becoming common practice to characterize the system's point spread function (PSF) and understand its variation under spatial transformations to guide clinical studies and potentially use it within resolution recovery image reconstruction algorithms. Furthermore, due to the system's utilization of overlapping and spherical symmetric Kaiser-Bessel basis functions during image reconstruction, its image space PSF and reconstructed spatial resolution could be affected by the selection of the basis function parameters. Hence, a detailed investigation into the multidimensional basis function parameter space is needed to evaluate the impact of these parameters on spatial resolution. Methods: Using an array of 12 × 7 printed point sources, along with a custom made phantom, and with the MR magnet on, the system's spatially variant image-based PSF was characterized in detail. Moreover, basis function parameters were systematically varied during reconstruction (list-mode TF OSEM) to evaluate their impact on the reconstructed resolution and the image space PSF. Following the spatial resolution optimization, phantom, and clinical studies were subsequently reconstructed using representative basis function parameters. Results: Based on the analysis and under standard basis function parameters, the axial and tangential components of the PSF were found to be almost invariant under spatial transformations (∼4 mm) while the radial component varied modestly from 4 to 6.7 mm. Using a systematic investigation into the basis function parameter space, the spatial resolution was found to degrade for basis functions with a large radius and small shape parameter. However, it was found that optimizing the spatial resolution in the reconstructed PET images, while having a good basis function superposition and keeping the image representation error to a minimum, is feasible, with the parameter combination range depending upon the scanner's intrinsic resolution characteristics. Conclusions: Using the printed point source array as a MR compatible methodology for experimentally measuring the scanner's PSF, the system's spatially variant resolution properties were successfully evaluated in image space. Overall the PET subsystem exhibits excellent resolution characteristics mainly due to the fact that the raw data are not under-sampled/rebinned, enabling the spatial resolution to be dictated by the scanner's intrinsic resolution and the image reconstruction parameters. Due to the impact of these parameters on the resolution properties of the reconstructed images, the image space PSF varies both under spatial transformations and due to basis function parameter selection. Nonetheless, for a range of basis function parameters, the image space PSF remains unaffected, with the range depending on the scanner's intrinsic resolution properties.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Reaction History Uncertainty Propagation from Flux to α and from Time to α [Slides]

We discuss uncertainty propagation in reaction history data from underground nuclear tests. γ reaction history detectors measured flux as a function of time. After data analysis we report α as a function of time. Flux uncertainty and time uncertainty propagation into α uncertainty are discussed in detail. Discretization of the formulas is discussed.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Ferroelectric switching pathways and domain structure of SrBi 2 ⁢(Ta,Nb) 2 ⁢O 9 from first principles

Several families of layered perovskite oxide ferroelectrics exhibit a coupling between polarization and structural order parameters, such as octahedral rotation distortions. This coupling provides opportunities for novel electric field-based manipulation of material properties, and it also stabilizes complex domain patterns and domain-wall vortices. Among layered perovskites with such coupled orders, the Aurivillius-phase oxides SrBi 2 ⁢B 2 ⁢O 9 (B = Ta,Nb) are well-known for their excellent room-temperature ferroelectric performance. This work combines group theoretic analysis with density functional theory calculations to examine the ferroelectric switching processes of SrBi2⁢B2⁢O9. Low-energy two-step ferroelectric switching paths are identified, with polarization reversal facilitated by structural order-parameter rotations. Analysis of the domain structure reveals how the relative energetics of the coupled order parameters translates into a network of several distinct domain-wall types linked by domain-wall vortex structures. Comparisons are made between the ferroelectric switching and domain structure of SrBi 2 ⁢B 2 ⁢O 9 and those of the layered n = 2 Ruddlesden-Popper hybrid improper ferroelectrics. The results provide insight into how ferroelectric properties may be optimized by engineering the complex crystal structures of Aurivillius-phase oxides.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

TH-EF-207A-04: A Dynamic Contrast Enhanced Cone Beam CT Technique for Evaluation of Renal Functions

Purpose: To develop a simple but robust method for the early detection and evaluation of renal functions using dynamic contrast enhanced cone beam CT technique. Methods: Experiments were performed on an integrated imaging and radiation research platform developed by our lab. Animals (n=3) were anesthetized with 20uL Ketamine/Xylazine cocktail, and then received 200uL injection of iodinated contrast agent Iopamidol via tail vein. Cone beam CT was acquired following contrast injection once per minute and up to 25 minutes. The cone beam CT was reconstructed with a dimension of 300×300×800 voxels of 130×130×130um voxel resolution. The middle kidney slices in the transvers and coronal planes were selected for image analysis. A double exponential function was used to fit the contrast enhanced signal intensity versus the time after contrast injection. Both pixel-based and region of interest (ROI)-based curve fitting were performed. Four parameters obtained from the curve fitting, namely the amplitude and flow constant for both contrast wash in and wash out phases, were investigated for further analysis. Results: Robust curve fitting was demonstrated for both pixel based (with R{sup 2}>0.8 for >85% pixels within the kidney contour) and ROI based (R{sup 2}>0.9 for all regions) analysis. Three different functional regions: renal pelvis, medulla and cortex, were clearly differentiated in the functional parameter map in the pixel based analysis. ROI based analysis showed the half-life T1/2 for contrast wash in and wash out phases were 0.98±0.15 and 17.04±7.16, 0.63±0.07 and 17.88±4.51, and 1.48±0.40 and 10.79±3.88 minutes for the renal pelvis, medulla and cortex, respectively. Conclusion: A robust method based on dynamic contrast enhanced cone beam CT and double exponential curve fitting has been developed to analyze the renal functions for different functional regions. Future study will be performed to investigate the sensitivity of this technique in the detection of radiation induced kidney dysfunction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

The globus compute dataset: An open function-as-a-service dataset from the edge to the cloud

Here we present a unique function-as-a-service (FaaS) dataset capturing the use of the Globus Compute (previously funcX) platform. Globus Compute implements a federated model via which users may deploy endpoints on arbitrary remote computers, from the edge to high performance computing (HPC) cluster, and they may then invoke Python functions on those endpoints via a reliable cloud -hosted service. The dataset covers 31 weeks and includes 2121472 task submissions from 252 users executed on 580 remote computing endpoints. It includes 277386 registered functions. We describe the dataset and various observations, some that are similar to other FaaS datasets, for example, that 74% of tasks run for less than 1 s, and some that are unique to Globus Compute, for example, that endpoints are used in different ways and that the majority of functions are related to scientific computing and machine learning. To the best of our knowledge, this dataset represents the first federated FaaS dataset that includes user workloads, distributed computing endpoints, and analysis of registered function bodies. We expect the dataset to be useful for researching FaaS architectures, workload modeling, container warming, and other distributed computing architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Towards a self-consistent analysis of the anisotropic galaxy two- and three-point correlation functions on large scales: application to mock galaxy catalogues

We establish a practical method for the joint analysis of anisotropic galaxy two- and three-point correlation functions (2PCF and 3PCF, respectively) on the basis of the decomposition formalism of the 3PCF using tripolar spherical harmonics. We perform such an analysis with MultiDark-Patchy mock catalogues to demonstrate and understand the benefit of the anisotropic 3PCF. We focus on scales above $80\, h^{-1}\, {\rm Mpc}$, and use information from the shape and the baryon acoustic oscillation (BAO) signals of the 2PCF and 3PCF. We also apply density field reconstruction to increase the signal-to-noise ratio of BAO in the 2PCF measurement, but not in the 3PCF measurement. In particular, we study in detail the constraints on the angular diameter distance and the Hubble parameter. We build a model of the bispectrum or 3PCF that includes the non-linear damping of the BAO signal in redshift space. We carefully account for various uncertainties in our analysis including theoretical models of the 3PCF, window function corrections, biases in estimated parameters from the fiducial values, the number of mock realizations to estimate the covariance matrix, and bin size. The joint analysis of the 2PCF and 3PCF monopole and quadrupole components shows a $30{{\ \rm per\ cent}}$ and $20{{\ \rm per\ cent}}$ improvement in Hubble parameter constraints before and after reconstruction of the 2PCF measurements, respectively, compared to the 2PCF analysis alone. Furthermore, this study clearly shows that the anisotropic 3PCF increases cosmological information from galaxy surveys and encourages further development of the modelling of the 3PCF on smaller scales than we consider.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Emission properties of body-centered cubic elemental metal photocathodes

A first principles analysis of photoemission is developed to explain the lower than expected rms transverse electron momentum measured using the solenoid scan technique for the body-centered cubic Group Vb (V, Nb, and Ta) and Group VIb (Cr, Mo, and W) metallic photocathodes. The density functional theory based analysis elucidates the fundamental role that the electronic band structure (and its dispersion) plays in determining the emission properties of solid-state photocathodes and includes evaluation of work function anisotropy using a thin-slab method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Deuterium-tritium neutron yield measurements with the 4.5 m neutron-time-of-flight detectors at NIF

The first several campaigns of laser fusion experiments at the National Ignition Facility (NIF) included a family of high-sensitivity scintillator/photodetector neutron-time-of-flight (nTOF) detectors for measuring deuterium-deuterium (DD) and DT neutron yields. The detectors provided consistent neutron yield (Y{sub n}) measurements from below 10{sup 9} (DD) to nearly 10{sup 15} (DT). The detectors initially demonstrated detector-to-detector Y{sub n} precisions better than 5%, but lacked in situ absolute calibrations. Recent experiments at NIF now have provided in situ DT yield calibration data that establish the absolute sensitivity of the 4.5 m differential tissue harmonic imaging (DTHI) detector with an accuracy of {+-}10% and precision of {+-}1%. The 4.5 m nTOF calibration measurements also have helped to establish improved detector impulse response functions and data analysis methods, which have contributed to improving the accuracy of the Y{sub n} measurements. These advances have also helped to extend the usefulness of nTOF measurements of ion temperature and downscattered neutron ratio (neutron yield 10-12 MeV divided by yield 13-15 MeV) with other nTOF detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Dynamic nuclear renography kinetic analysis: Four-compartment model for assessing kidney function

Dynamic nuclear renography method produces TACs of kidneys and bladder. Multiple TACs data can be further analyzed to obtain the overview of urinary system's condition. Tracer kinetic analysis was performed using four-compartment models. The system's model consist of four irreversible compartment with four transport constants (k1, k2, k3 and k4). The mathematical expressions of tracer's distributions is fitted to experimental data (TACs) resulting in model constants. This transport constants represent the urinary system behavior, and later can be used for analyzing system's condition. Different intervals of kinetics parameter are clearly shown by abnormal system with respect to the normal one. Furthermore, the system with delayed uptake has 82% lower uptake parameters (k1 and k2) than normal one. Meanwhile, the system with prolonged clearance time has its kinetics parameters k3 or k4 lower than the others. This model is promising for quantitatively describe urinary system's function especially if supplied with more data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Modeling and simulation functional needs for molten salt reactor licensing

The modeling and simulation functional needs to license and design molten salt reactor concepts were assessed and an evaluation methodology was developed using a licensing-focused approach considering the modeling and simulation components that contribute to a molten salt reactor safety analysis report. These functional needs were prioritized by identifying the relationships between functional needs and using a quantitative weighting method to identify the most critical components to build a licensing case. This novel weighting method provided a list of functional needs prioritized relative to key advanced reactor licensing outcomes. In addition, functional need inputs were ranked to reveal those that feed the most modeling and simulation components. The findings from this prioritization effort were used to inform the modeling and simulation goals of the US Department of Energy Office of Nuclear Energy (DOE-NE) Molten Salt Reactor campaign.Modeling and simulation needs were grouped into three main categories: (1) source term definition, material accountancy, and radiological consequences, (2) safety analysis, and (3) steady-state neutronics and thermal hydraulics. Here, five near-term goals were identified among these focus areas that add value: (1) deploying a systems and safeguards analysis computational tool, (2) defining source terms for molten salt reactor analysis and interfacing with the US Nuclear Regulatory Commission on accident progression analysis, (3) developing point designs for liquid-fueled thermal-spectrum and fast-spectrum molten salt reactors, (4) building safety analysis specifications and reference solutions for Molten Salt Reactor Experiment transients, and (5) interfacing with the thermophysical and thermodynamic salt chemistry databases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Machine-Learning Analysis of Moisture Carryover in Boiling Water Reactors

Moisture carryover (MCO) is modeled in the General Electric Type-4 boiling water reactor (BWR) using machine-learning methods and data from operating plants. Understanding MCO and the conditions that give rise to an elevated value is important since excessive MCO can damage critical turbine components, can result in elevated dose levels to on-site personnel, and can interfere with late-cycle power management. The analysis of MCO takes into account simplifying reactor symmetries and important geometric dependencies. The plant data are taken from several reactors and were collected over multiple years and multiple fuel cycles. A brief description of the origin of MCO in U.S. BWR plants is given. A machine-learning model is constructed from the data using applicable algorithms and data-reduction techniques. Matching model complexity with available data is one of the more challenging machine-learning tasks. Too many features and too little data will lead to overfitting. The data for each fuel cycle included over 6876 original features, 9 for each fuel bundle. Two approaches are used to reduce the data set into a manageable number of features. The first was an engineering analysis that resulted in the selection of steam quality Q and steam liquid phase velocity V L as the main features driving MCO. Using a Q and a V L for each fuel bundle gives 1528 Q and a V L feature describing the reactor behavior. An analysis of different functional forms of these two variables led to the actual inputs to the neural network model. The second approach involved the use of statistical techniques such as Pearson’s correlation and k-means analysis. The identified groupings of bundles behaved similarly. Treating each grouping as a single feature further reduced the input variable set to a manageable number. Here, a model selection criterion is proposed, and results are presented along with a discussion of related issues.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Tuning the Properties of Lignin‐Derived Deep Eutectic Solvents for Biomass Processing

Lignin-derived deep eutectic solvents (DESs) have been investigated as sustainable green media for biomass processing. However, the properties and processability of DESs have not been fully understood with the chemical structures of their constituents for biomass fractionation. Here, in this article, the properties of the phenolic DESs are discussed with different numbers of functional groups, such as –OCH 3 and –CHO in their hydrogen bond donor (HBD) structures. The formation of DES is significantly related to the hydrogen bond between its constituents, identified by nuclear magnetic resonance (NMR) analysis and density functional theory calculation (DFT). Lower viscosity and net basicity of DES are achieved with fewer –OCH 3 on HBD structures, resulting in enhanced processability and fractionation efficiency. The thermal stability of the DES is also influenced by the –OCH 3 and –CHO of HBD, as indicated by its onset temperature. The recyclability of the phenolic DES is confirmed by the fractionation performance of the recycled DES. Understanding the structural impacts of DES constituents on the properties and performance is crucial for designing solvents in biorefinery applications.

Ryu, Jiae [State University of New York (SUNY), Sy↗
DOE OSTI2016

Energy Management Policies in Distributed Residential Energy Systems

In this paper, we study energy management problems in communities with several neighborhood-level Residential Energy Systems (RESs). We consider control problems from both community level and residential level to handle external changes such as restriction on peak demand and restriction on the total demand from the electricity grid. We propose three policies to handle the problems at community level. Based on the collected data from RESs such as predicted energy load, the community controller analyzes the policies, distribute the results to the RES, and each RES can then control and schedule its own energy load based on different coordination functions. We utilize a framework to integrate both policy analysis and coordination of functions. With the use of our approach, we show that the policies are useful to resolve the challenges of energy management under external changes.

Duan, Sisi↗
DOE OSTI2011

Relationship Between Radiation Treatment Time and Overall Survival After Induction Chemotherapy for Locally Advanced Head-and-Neck Carcinoma: A Subset Analysis of TAX 324

Purpose: To analyze the relationship between overall survival (OS) and radiation treatment time (RTT) and overall treatment time (OTT) in a well-described sequential therapy paradigm for locally advanced head-and-neck carcinoma (LAHNC). Methods and Materials: TAX 324 is a Phase III study comparing TPF (docetaxel, cisplatin, and fluorouracil) with PF (cisplatin and fluorouracil) induction chemotherapy (IC) in LAHNC patients; both arms were followed by carboplatin-based chemoradiotherapy (CRT). Prospective radiotherapy quality assurance was performed. This analysis includes all patients who received three cycles of IC and a radiation dose of {>=} 70 Gy. Radiotherapy treatment time was analyzed as binary ({<=} 8 weeks vs. longer) and continuous (number of days beyond 8 weeks) functions. The primary analysis assessed the relationship between RTT, OTT, and OS, and the secondary analysis explored the association between treatment times and locoregional recurrence (LRR). Results: A total of 333 (of 501) TAX 324 patients met the criteria for inclusion in this analysis. There were no significant differences between the treatment arms in baseline or treatment characteristics. On multivariable analysis, PF IC, World Health Organization performance status of 1, non-oropharynx site, T3/4 stage, N3 status, and prolonged RTT (hazard ratio 1.63, p = 0.006) were associated with significantly inferior survival. Performance status, T3/4 disease, and prolonged RTT (odds ratio 1.68, p = 0.047) were independently and negatively related to LRR on multivariable analysis, whereas PF was not. Overall treatment time was not independently associated with either OS or LRR. Conclusions: In this secondary analysis of the TAX 324 trial, TPF IC remains superior to PF IC after controlling for radiotherapy delivery time. Even with optimal IC and concurrent chemotherapy, a non-prolonged RTT is a crucial determinant of treatment success. Appropriate delivery of radiotherapy after IC remains essential for optimizing OS in LAHNC.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Extracting dependencies between network assets using deep learning

A network analysis tool receives network flow information and uses deep learning—machine learning that models high-level abstractions in the network flow information—to identify dependencies between network assets. Based on the identified dependencies, the network analysis tool can discover functional relationships between network assets. For example, a network analysis tool receives network flow information, identifies dependencies between multiple network assets based on evaluation of the network flow information, and outputs results of the identification of the dependencies. When evaluating the network flow information, the network analysis tool can pre-process the network flow information to produce input vectors, use deep learning to extract patterns in the input vectors, and then determine dependencies based on the extracted patterns. The network analysis tool can repeat this process so as to update an assessment of the dependencies between network assets on a near real-time basis.

Carroll, Thomas E.↗
DOE OSTI2016

Progress In Developing Laser Based Post Irradiation Examination Infrastructure

To be able to understand the performance of reactor fuels and materials, irradiated materials must be characterized effectively and efficiently in a high rad environment. The characterization work must be performed remotely and in an environment hostile to instrumentation. Laser based characterization techniques provide the ability to be remote and robust in a hot-cell environment. Laser based instrumentation also can provide high spatial resolution suitable for scanning and imaging large areas. The INL is currently developing three laser based Post Irradiation Examination (PIE) stations for the Hot Fuel Examination Facility at the INL. These laser based systems will characterize irradiated materials and fuels. The characterization systems are the following: Laser Shock Laser based ultrasonic C-scan system Gas Assay, Sample, and Recharge system (GASR, up-grade to an existing system). The laser shock technique will characterize material properties and failure loads/mechanisms in various materials such as LWR fuel, plate fuel, and next generation fuel forms, for PIE in high radiation areas. The laser shock-technique induces large amplitude shock waves to mechanically characterize interfaces such as the fuel-clad bond. The shock wave travels as a compression wave through the material to the free (unconfined) back surface and reflects back through the material under test as a rarefaction (tensile) wave. This rarefaction wave is the physical mechanism that produces internal de-lamination failure. As part of the laser shock system, a laser-based ultrasonic C-scan system will be used to detect and characterize debonding caused by the laser shock technique. The laser ultrasonic system will be fully capable of performing classical non-destructive evaluation testing and imaging functions such as microstructure characterization, flaw detection and dimensional metrology in complex components. The purpose of the GASR is to measure the pressure/volume of the plenum of an irradiated fuel element and obtain fission gas samples for analysis. The study of pressure and volume in the plenum of an irradiated fuel element and the analysis of fission gases released from the fuel is important to understanding the performance of reactor fuels and materials. This system may also be used to measure the pressure/volume of other components (such as control blades) and obtain gas samples from these components for analysis. The main function of the laser in this application is to puncture the fuel element to allow the fission gas to escape and if necessary to weld the spot close. The GASR station will have the inherent capability to perform cutting welding and joining functions within a hot-cell.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

The ecosystem approach in ecological impact assessment: Lessons learned from windfarm developments on peatlands in Scotland

Highlights: • Recent wind energy projects in Scotland mostly fail to consider ecosystem-level impacts on peatland. • Projects on peatland illustrate the usefulness of an ecosystem approach to Environmental Impact Assessment. • Defining more meaningful functional management units can improve Environmental Impact Assessment outcomes. • VAn ecosystem approach could also improve ecosystem services assessments. - Abstract: The Ecosystem Approach introduced in 1994 through the Convention on Biological Diversity, together with related Ecosystem-based Management and Landscape Approaches, are frequently called upon to improve ecological impact assessment. Current practice typically does not have such a systems focus and we explore the potential for explicitly adopting an Ecosystem Approach in the Environmental Impact Assessment process using wind energy development on peatland, in Scotland, as a case study. Based on a review of 21 windfarm projects (>50 MW) approved by the Scottish Government we provide an overview of current practice and identify and discuss how the 12 principles of the Ecosystem Approach can help identify options for more appropriate impact assessment. These include defining functional units of analysis that reflect the spatial and temporal linkages of peatland elements through hydrological connections, rather than a focus on individual vegetation types and simple distance buffers. Our conclusions are not limited to peatland and are relevant wherever meaningful functional management units can be defined, including in marine environments. Our results also show that environmental statements for wind energy development in Scotland largely ignore ecosystem services and the people that benefit from them. As for threatened species and other biodiversity features, an Ecosystem Approach is a prerequisite to the meaningful inclusion of ecosystem services in impact assessment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Structural analysis of ITER magnet feeders

This paper summarizes the results of the static structural analyses, which were conducted in support of the ITER magnet feeder design with the aim of validating certain components against the structural design criteria. While almost every feeder has unique features, they all share many common constructional elements and the same functional specifications. The analysis approach to assess the load conditions and stresses that have driven the design is equivalent for all feeders, except for particularities that needed to be modeled in each case. The mechanical analysis of the feeders follows the sub-modeling approach: the results of the global mechanical model of a feeder assembly are used as input for the detailed models of the feeder' sub-assemblies or single components. Examples of such approach, including the load conditions, stress assessment criteria and solutions for the most critical components, are discussed. It has been concluded that the feeder system is safe in the referential operation scenarios. (authors)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗