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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Characterization and Optimization of Building Blocks for Specialized Computing Platforms

As noise limits the performance of quantum processors, the ability to characterize this noise and develop methods to overcome it is essential for the future of quantum computing. In this report, we develop a complete set of tools for improving quantum processor performance at the application level, including low-level physical models of quantum gates, a numerically efficient method of producing process matrices that span a wide range of model parameters, and full-channel quantum simulations. We then provide a few examples of how to use these tools to study the effects of noise on quantum circuits.

42 ENGINEERING↗
DOE OSTI2024

Machine Learning Classification Strategy to Improve Streamflow Estimates in Diverse River Basins in the Colorado River Basin

Streamflow in the Colorado River Basin (CRB) is significantly altered by human activities including land use/cover alterations, reservoir operation, irrigation, and water exports. Climate is also highly varied across the CRB which contains snowpack-dominated watersheds and arid, precipitation-dominated basins. Recently, machine learning methods have improved the generalizability and accuracy of streamflow models. Previous successes with LSTM modeling have primarily focused on unimpacted basins, and few studies have included human impacted systems in either regional or single-basin modeling. We demonstrate that the diverse hydrological behavior of river basins in the CRB are too difficult to model with a single, regional model. We propose a method to delineate catchments into categories based on the level of predictability, hydrological characteristics, and the level of human influence. Lastly, we model streamflow in each category with climate and anthropogenic proxy data sets and use feature importance methods to assess whether model performance improves with additional relevant data. Overall, land use cover data at a low temporal resolution was not sufficient to capture the irregular patterns of reservoir releases, demonstrating the importance of having high-resolution reservoir release data sets at a global scale. On the other hand, the classification approach reduced the complexity of the data and has the potential to improve streamflow forecasts in human-altered regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

EPRI Research Results: International Nuclear Power Plant Waste Classification - 17444

Different countries around the globe use varying schemes for the classification of radioactive waste. Many countries develop country specific waste classification schemes based on the International Atomic Energy Agency (IAEA) waste classification framework. The United States of America use the Class A, B, and C waste classification. Additionally, some countries use concentration limits to classify wastes while others use dose rate limits or a combination of concentration and dose rate limits. General comparisons have been made between the IAEA and the United States classification schemes, but a clear and well researched comparison of the international schemes was not evident in the available research data sets. In 2013 Electric Power Research Institute (EPRI) initiated the Comparison of Global Low and Intermediate Level Waste Management Methods project. The objective of the project was to understand how six countries managed their low and intermediate level wastes from generation to disposal. A major task of this project was to conduct a comparison of the international waste classification schemes. EPRI developed a set of reference waste volumes that are representative of nuclear power plant low-level radioactive waste in form and radioactivity concentrations (e.g. dry active waste, high activity resin, low activity resin, high activity filters and low activity filters). These waste volumes were then classified using the waste classification systems in place in several countries around the world. In 2016, EPRI presented a paper providing a status update on this research. This 2017 paper provides the final results of that research, show where comparisons and correlations can be made, and provide a discussion on how this information might inform international radioactive research and development and benchmarking of radioactive waste management strategies, operational experiences, best practices, and technology implementation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Charge transfer and atomic-level pressure in metallic glasses

This paper presents a systematic study on the charge transfer and ionicity in various metallic-glass forming systems, as well as its relationship with other atomic-level structure indicators, using the Bader analysis method and molecular dynamics simulation. It is shown that in a binary or multicomponent system, the chemical effects (when more than one elements present) appear to play a more important role in setting the absolute level of the atomic-level pressure, compared to the topological fluctuation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

UNCERTAINTIES IN ATOMIC DATA AND THEIR PROPAGATION THROUGH SPECTRAL MODELS. I

We present a method for computing uncertainties in spectral models, i.e., level populations, line emissivities, and emission line ratios, based upon the propagation of uncertainties originating from atomic data. We provide analytic expressions, in the form of linear sets of algebraic equations, for the coupled uncertainties among all levels. These equations can be solved efficiently for any set of physical conditions and uncertainties in the atomic data. We illustrate our method applied to spectral models of O III and Fe II and discuss the impact of the uncertainties on atomic systems under different physical conditions. As to intrinsic uncertainties in theoretical atomic data, we propose that these uncertainties can be estimated from the dispersion in the results from various independent calculations. This technique provides excellent results for the uncertainties in A-values of forbidden transitions in [Fe II].

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

TU-F-CAMPUS-I-05: Parameterization of the Noise Power Spectrum in X-Ray Computed Tomography

Purpose: The purpose of this work was to develop a method so that the noise power spectrum (NPS) can be approximated for arbitrary levels of mAs, from a single determination in CT. Methods: The NPS is factorized into 2 components, 1) a parameterized function representing the 1D normalized spatial frequency distribution and 2) a function to scale the magnitude of 1) for arbitrary values of mAs. The 1D NPS, normalized by image variance (NNPS), was determined for 2 FBP reconstruction kernels (smoothing and edge enhancing) for 400 mAs. The NNPS were fit to the parameterized function and a scaling function was established to approximate the image variance at arbitrary values of mAs. Using the root mean square error normalized by the maximum value (NRMSE), the NPS approximated with the factorization method was compared to the NPS determined at 5 different mAs levels. Results: The factorization resulted in a set of 7 coefficients that can be used to approximate the 1D NPS, for arbitrary levels of mAs, for the convolution kernels studied in this work. The approximated NPS (factorization) agreed well with the determined NPS for all mAs levels. The greatest NRMSE was 0.02 and was observed for the edge enhancing kernel. Conclusion: The proposed factorization method has been demonstrated as applicable for FBP reconstruction. It can be used to approximate the 1D NPS for arbitrary levels of mAs, from a single NPS determination. Furthermore, approximations of the 1D NPS can conveniently be distributed since the factorization method only used 7 coefficients in the approximation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Texture analysis improves level set segmentation of the anterior abdominal wall

Purpose: The treatment of ventral hernias (VH) has been a challenging problem for medical care. Repair of these hernias is fraught with failure; recurrence rates ranging from 24% to 43% have been reported, even with the use of biocompatible mesh. Currently, computed tomography (CT) is used to guide intervention through expert, but qualitative, clinical judgments, notably, quantitative metrics based on image-processing are not used. The authors propose that image segmentation methods to capture the three-dimensional structure of the abdominal wall and its abnormalities will provide a foundation on which to measure geometric properties of hernias and surrounding tissues and, therefore, to optimize intervention.Methods: In this study with 20 clinically acquired CT scans on postoperative patients, the authors demonstrated a novel approach to geometric classification of the abdominal. The authors’ approach uses a texture analysis based on Gabor filters to extract feature vectors and follows a fuzzy c-means clustering method to estimate voxelwise probability memberships for eight clusters. The memberships estimated from the texture analysis are helpful to identify anatomical structures with inhomogeneous intensities. The membership was used to guide the level set evolution, as well as to derive an initial start close to the abdominal wall.Results: Segmentation results on abdominal walls were both quantitatively and qualitatively validated with surface errors based on manually labeled ground truth. Using texture, mean surface errors for the outer surface of the abdominal wall were less than 2 mm, with 91% of the outer surface less than 5 mm away from the manual tracings; errors were significantly greater (2–5 mm) for methods that did not use the texture.Conclusions: The authors’ approach establishes a baseline for characterizing the abdominal wall for improving VH care. Inherent texture patterns in CT scans are helpful to the tissue classification, and texture analysis can improve the level set segmentation around the abdominal region.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Accurate and Efficient ab Initio Calculations for Supramolecular Complexes: Symmetry-Adapted Perturbation Theory with Many-Body Dispersion

Symmetry-adapted perturbation theory (SAPT) provides a chemically meaningful energy decomposition scheme for nonbonded interactions that is useful for interpretive purposes. Although formally a dimer theory, we have previously introduced an “extended” version (XSAPT) that incorporates many-body polarization via self-consistent charge embedding. Here, we extend the XSAPT methodology to include nonadditive dispersion, using a modified form of the many-body dispersion (MBD) method of Tkatchenko and co-workers. Dispersion interactions beyond the pairwise atom–atom approximation improve total interaction energies even in small systems, and for large π-stacked complexes these corrections can amount to several kilocalories per mole. The XSAPT+MBD method introduced here achieves errors of ≲1 kcal/mol (as compared to high-level ab initio benchmarks) for the L7 data set of large dispersion-bound complexes and ≲4 kcal/mol (as compared to experiment) for the S30L data set of host–guest complexes. This is superior to the best contemporary density functional methods for noncovalent interactions, at comparable or lower cost. XSAPT+MBD represents a promising method for application to supramolecular assemblies, including protein–ligand binding.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2012

Direct dynamics simulation of dioxetane formation and decomposition via the singlet ·O–O–CH2–CH2 · biradical: Non-RRKM dynamics

Electronic structure calculations and direct chemical dynamics simulations are used to study the formation and decomposition of dioxetane on its ground state singlet potential energy surface. The stationary points for 1O2 + C2H4, the singlet {center_dot}O-O-CH2-CH2{center_dot} biradical, the transition state (TS) connecting this biradical with dioxetane, and the two transition states and gauche {center_dot}O-CH2-CH2-O{center_dot} biradical connecting dioxetane with the formaldehyde product molecules are investigated at different levels of electronic structure theory including UB3LYP, UMP2, MRMP2, and CASSCF and a range of basis sets. The UB3LYP/6-31G* method was found to give representative energies for the reactive system and was used as a model for the simulations. UB3LYP/6-31G* direct dynamics trajectories were initiated at the TS connecting the {center_dot}O-O-CH2-CH2{center_dot} biradical and dioxetane by sampling the TS's vibrational energy levels, and rotational and reaction coordinate energies, with Boltzmann distributions at 300, 1000, and 1500 K. This corresponds to the transition state theory model for trajectories that pass the TS. The trajectories were directed randomly towards both the biradical and dioxetane. A small fraction of the trajectories directed towards the biradical recrossed the TS and formed dioxetane. The remainder formed 1O2 + C2H4 and of these {approx} 40% went directly from the TS to 1O2 + C2H4 without getting trapped and forming an intermediate in the {center_dot}O-O- CH2-CH2{center_dot} biradical potential energy minimum, a non-statistical result. The dioxetane molecules which are formed dissociate to two formaldehyde molecules with a rate constant two orders of magnitude smaller than that predicted by Rice-Ramsperger-Kassel-Marcus theory. The reaction dynamics from dioxetane to the formaldehyde molecules do not follow the intrinsic reaction coordinate or involve trapping in the gauche {center_dot}O-CH2-CH2-O{center_dot} biradical potential energy minimum. Important non-statistical dynamics are exhibited for this reactive system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

SU-D-12A-06: A Comprehensive Parameter Analysis for Low Dose Cone-Beam CT Reconstruction

Purpose: There is always a parameter in compressive sensing based iterative reconstruction (IR) methods low dose cone-beam CT (CBCT), which controls the weight of regularization relative to data fidelity. A clear understanding of the relationship between image quality and parameter values is important. The purpose of this study is to investigate this subject based on experimental data and a representative advanced IR algorithm using Tight-frame (TF) regularization. Methods: Three data sets of a Catphan phantom acquired at low, regular and high dose levels are used. For each tests, 90 projections covering a 200-degree scan range are used for reconstruction. Three different regions-of-interest (ROIs) of different contrasts are used to calculate contrast-to-noise ratios (CNR) for contrast evaluation. A single point structure is used to measure modulation transfer function (MTF) for spatial-resolution evaluation. Finally, we analyze CNRs and MTFs to study the relationship between image quality and parameter selections. Results: It was found that: 1) there is no universal optimal parameter. The optimal parameter value depends on specific task and dose level. 2) There is a clear trade-off between CNR and resolution. The parameter for the best CNR is always smaller than that for the best resolution. 3) Optimal parameters are also dose-specific. Data acquired under a high dose protocol require less regularization, yielding smaller optimal parameter values. 4) Comparing with conventional FDK images, TF-based CBCT images are better under a certain optimally selected parameters. The advantages are more obvious for low dose data. Conclusion: We have investigated the relationship between image quality and parameter values in the TF-based IR algorithm. Preliminary results indicate optimal parameters are specific to both the task types and dose levels, providing guidance for selecting parameters in advanced IR algorithms. This work is supported in part by NIH (1R01CA154747-01)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Using discrete Bayesian networks for diagnosing and isolating cross-level faults in HVAC systems

Fault detection and diagnosis (FDD) technologies are critical to ensure satisfactory building performance, such as reducing energy wastes and negative impacts on occupant comfort and productivity. Existing FDD technologies mainly focus on component-level FDD solutions, which could lead to mis-diagnosis of cross-level faults in heating, ventilating, and air-conditioning (HVAC) systems. Cross-level faults are those faults that occur in one component or subsystem, but cause operational abnormalities in other components or subsystems, and result in a building level performance degradation. How to effectively diagnose the root cause of a cross-level fault is the focus of this study. Here, this paper presents a novel discrete Bayesian Network (DisBN)-based method for diagnosing cross-level faults in an HVAC system commonly used in commercial buildings. A two-level DisBN structure model is developed in this study. The parameters used in the DisBN model are obtained either from expert knowledge or through machine-learning strategies from normal system operation data. Meanwhile, the probability parameters are discretized to incorporate the uncertainties associated with typical expert knowledge. Thus, the developed DisBN method addresses the challenges many other BN based FDD methods face, i.e., the lack of fault data for BN parameter training. The developed DisBN represents causal relationships between a fault and its cross-level system impacts (i.e., fault symptoms or fault indicators) by considering how fault impacts propagate across different levels in an HVAC system. A weather and schedule information-based Pattern Matching (WPM) method is employed to automatically create WPM baseline data sets for each incoming real time snapshot data from the building systems. Consequently, BN inference and real-time diagnostics are achieved by comparing incoming snapshot data and the WPM baseline data set. The proposed method is evaluated using experimental fault data collected in a campus building. Fault diagnosis results demonstrate that the WPM-DisBN method is effective at locating the root causes of cross-level faults in an HVAC system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Rigorous Ab Initio Quantum Embedding for Quantum Chemistry Using Green’s Function Theory: Screened Interaction, Nonlocal Self-Energy Relaxation, Orbital Basis, and Chemical Accuracy

We present a detailed discussion of the self-energy embedding theory (SEET), which is a quantum embedding scheme allowing us to describe a chosen subsystem very accurately while keeping the description of the environment at a lower level. We apply SEET to molecular examples where our chosen subsystem is made out of a set of strongly correlated orbitals while the weakly correlated orbitals constitute an environment. Consequently, a highly accurate method is used to calculate the self-energy for the system, while a lower-level method is employed to find the self-energy for the environment. Such a self-energy separation is very general, and to make the SEET procedure applicable to multiple systems, a detailed and practical procedure for the evaluation of the system and environment self-energy is necessary. We list all of the intricacies for one of the possible procedures while focusing our discussion on many practical implementation aspects such as the choice of best orbital basis, impurity solver, and many steps necessary to reach chemical accuracy. Finally, on a set of carefully chosen molecular examples, we demonstrate that SEET, which is a controlled, systematically improvable Green’s function method, can be as accurate as established wave function quantum chemistry methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

MO-DE-BRA-05: EUTEMPE-RX: Combining E-Learning and Face-To-Face Training to Build Expert Knowledge, Skills and Competences for Medical Physicists in Diagnostic and Interventional Radiology

Purpose: In 2013, the EURATOM authorities of the European Commission decided to support the Horizon2020 project submission ‘EUTEMPE-RX’ that aimed for a new set of course modules to train medical physicists in diagnostic and interventional radiology to expert level with small group deep learning. Each module would consist of 2 phases: an e-learning and a face-to-face phase, each phase requiring typically 40h of participant time. Methods: The European Federation (EFOMP) and 13 European partners, all of them selected for their excellent scientific and/or educational skills, led the 12 course modules. A quality manual ensured the quality of course content and organization. Educational workshops familiarized the teachers with e-learning techniques and methods for assessment. Content was set in accordance with the EC document RP174 that lists learning outcomes in terms of knowledge, skills and competences (KSCs) for different specialties and levels of medical physics. Surveys for stake holder satisfaction were prepared. Results: Today the course modules are being realized. The modules cover most of the KSCs in RP174 document. Teachers have challenged the participants with unique tasks: case studies in medical physics leadership, Monte Carlo simulation of a complete x-ray imaging chain, development of a task specific QA protocol, compilation of optimization plans, simulation tasks with anthropomorphic breast models, etc. Participants undertook practical sessions in modern hospitals and visited a synchrotron facility, a calibration lab, screening organizations, etc. Feedback form quality surveys was very positive and constructive. A sustainability plan has been worked out. Conclusion: The modules have enabled the participants to develop their KSCs and cope with challenges in medical physics. The sustainability plan will be implemented to continue the unique combined e-learning and face to face training at high level training in diagnostic and interventional radiology also beyond Europe. The EUTEMPE-RX project is funded by the Horizon2020 - EURATOM program of the European Commission.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Improved algorithm for processing grating-based phase contrast interferometry image sets

Grating-based X-ray and neutron interferometry tomography using phase-stepping methods generates large data sets. An improved algorithm is presented for solving for the parameters to calculate transmissions, differential phase contrast, and dark-field images. The method takes advantage of the vectorization inherent in high-level languages such as Mathematica and MATLAB and can solve a 16 × 1k × 1k data set in less than a second. In addition, the algorithm can function with partial data sets. This is demonstrated with processing of a 16-step grating data set with partial use of the original data chosen without any restriction. Also, we have calculated the reduced chi-square for the fit and notice the effect of grating support structural elements upon the differential phase contrast image and have explored expanded basis set representations to mitigate the impact.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

System, apparatus and methods to implement high-speed network analyzers

Systems, apparatus and methods for the implementation of high-speed network analyzers are provided. A set of high-level specifications is used to define the behavior of the network analyzer emitted by a compiler. An optimized inline workflow to process regular expressions is presented without sacrificing the semantic capabilities of the processing engine. An optimized packet dispatcher implements a subset of the functions implemented by the network analyzer, providing a fast and slow path workflow used to accelerate specific processing units. Such dispatcher facility can also be used as a cache of policies, wherein if a policy is found, then packet manipulations associated with the policy can be quickly performed. An optimized method of generating DFA specifications for network signatures is also presented. The method accepts several optimization criteria, such as min-max allocations or optimal allocations based on the probability of occurrence of each signature input bit.

42 ENGINEERING↗
DOE OSTI2016

SU-F-R-40: Robustness Test of Computed Tomography Textures of Lung Tissues to Varying Scanning Protocols Using a Realistic Phantom Environment

Purpose: The reliability of computed tomography (CT) textures is an important element of radiomics analysis. This study investigates the dependency of lung CT textures on different breathing phases and changes in CT image acquisition protocols in a realistic phantom setting. Methods: We investigated 11 CT texture features for radiation-induced lung disease from 3 categories (first-order, grey level co-ocurrence matrix (GLCM), and Law’s filter). A biomechanical swine lung phantom was scanned at two breathing phases (inhale/exhale) and two scanning protocols set for PET/CT and diagnostic CT scanning. Lung volumes acquired from the CT images were divided into 2-dimensional sub-regions with a grid spacing of 31 mm. The distribution of the evaluated texture features from these sub-regions were compared between the two scanning protocols and two breathing phases. The significance of each factor on feature values were tested at 95% significance level using analysis of covariance (ANCOVA) model with interaction terms included. Robustness of a feature to a scanning factor was defined as non-significant dependence on the factor. Results: Three GLCM textures (variance, sum entropy, difference entropy) were robust to breathing changes. Two GLCM (variance, sum entropy) and 3 Law’s filter textures (S5L5, E5L5, W5L5) were robust to scanner changes. Moreover, the two GLCM textures (variance, sum entropy) were consistent across all 4 scanning conditions. First-order features, especially Hounsfield unit intensity features, presented the most drastic variation up to 39%. Conclusion: Amongst the studied features, GLCM and Law’s filter texture features were more robust than first-order features. However, the majority of the features were modified by either breathing phase or scanner changes, suggesting a need for calibration when retrospectively comparing scans obtained at different conditions. Further investigation is necessary to identify the sensitivity of individual image acquisition parameters.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Technical Note: Measuring contrast- and noise-dependent spatial resolution of an iterative reconstruction method in CT using ensemble averaging

Purpose: The spatial resolution of iterative reconstruction (IR) in computed tomography (CT) is contrast- and noise-dependent because of the nonlinear regularization. Due to the severe noise contamination, it is challenging to perform precise spatial-resolution measurements at very low-contrast levels. The purpose of this study was to measure the spatial resolution of a commercially available IR method using ensemble-averaged images acquired from repeated scans. Methods: A low-contrast phantom containing three rods (7, 14, and 21 HU below background) was scanned on a 128-slice CT scanner at three dose levels (CTDI{sub vol} = 16, 8, and 4 mGy). Images were reconstructed using two filtered-backprojection (FBP) kernels (B40 and B20) and a commercial IR method (sinogram affirmed iterative reconstruction, SAFIRE, Siemens Healthcare) with two strength settings (I40-3 and I40-5). The same scan was repeated 100 times at each dose level. The modulation transfer function (MTF) was calculated based on the edge profile measured on the ensemble-averaged images. Results: The spatial resolution of the two FBP kernels, B40 and B20, remained relatively constant across contrast and dose levels. However, the spatial resolution of the two IR kernels degraded relative to FBP as contrast or dose level decreased. For a given dose level at 16 mGy, the MTF{sub 50%} value normalized to the B40 kernel decreased from 98.4% at 21 HU to 88.5% at 7 HU for I40-3 and from 97.6% to 82.1% for I40-5. At 21 HU, the relative MTF{sub 50%} value decreased from 98.4% at 16 mGy to 90.7% at 4 mGy for I40-3 and from 97.6% to 85.6% for I40-5. Conclusions: A simple technique using ensemble averaging from repeated CT scans can be used to measure the spatial resolution of IR techniques in CT at very low contrast levels. The evaluated IR method degraded the spatial resolution at low contrast and high noise levels.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Study of self-compliance behaviors and internal filament characteristics in intrinsic SiO{sub x}-based resistive switching memory

Self-compliance characteristics and reliability optimization are investigated in intrinsic unipolar silicon oxide (SiO{sub x})-based resistive switching (RS) memory using TiW/SiO{sub x}/TiW device structures. The program window (difference between SET voltage and RESET voltage) is dependent on external series resistance, demonstrating that the SET process is due to a voltage-triggered mechanism. The program window has been optimized for program/erase disturbance immunity and reliability for circuit-level applications. The SET and RESET transitions have also been characterized using a dynamic conductivity method, which distinguishes the self-compliance behavior due to an internal series resistance effect (filament) in SiO{sub x}-based RS memory. By using a conceptual “filament/resistive gap (GAP)” model of the conductive filament and a proton exchange model with appropriate assumptions, the internal filament resistance and GAP resistance can be estimated for high- and low-resistance states (HRS and LRS), and are found to be independent of external series resistance. Our experimental results not only provide insights into potential reliability issues but also help to clarify the switching mechanisms and device operating characteristics of SiO{sub x}-based RS memory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗