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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Approximate Hessian for accelerating ab initio structure relaxation by force fitting

We present a method to approximate the Hessian matrix of the Born-Oppenheimer energy landscape by using a simple force field model whose parameters are fitted to on-the-flight ab initio results. The inversed Hessian matrix is used as the preconditioner of conjugate gradient algorithms to speed up the atomic structure relaxation, resulting in a speedup factor of 2 to 5 on systems of bulk, slab, sheets, and atomic clusters. Because the force field model employed is simple and general, the parameter fitting is straightforward; the method is applicable to a variety of complicated systems for minimum structure relaxation. In the metal cluster new structure search, the new method yields better structures than the one obtained before with conventional algorithms.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Robust Intratumor Partitioning to Identify High-Risk Subregions in Lung Cancer: A Pilot Study

Purpose: To develop an intratumor partitioning framework for identifying high-risk subregions from {sup 18}F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) imaging and to test whether tumor burden associated with the high-risk subregions is prognostic of outcomes in lung cancer. Methods and Materials: In this institutional review board–approved retrospective study, we analyzed the pretreatment FDG-PET and CT scans of 44 lung cancer patients treated with radiation therapy. A novel, intratumor partitioning method was developed, based on a 2-stage clustering process: first at the patient level, each tumor was over-segmented into many superpixels by k-means clustering of integrated PET and CT images; next, tumor subregions were identified by merging previously defined superpixels via population-level hierarchical clustering. The volume associated with each of the subregions was evaluated using Kaplan-Meier analysis regarding its prognostic capability in predicting overall survival (OS) and out-of-field progression (OFP). Results: Three spatially distinct subregions were identified within each tumor that were highly robust to uncertainty in PET/CT co-registration. Among these, the volume of the most metabolically active and metabolically heterogeneous solid component of the tumor was predictive of OS and OFP on the entire cohort, with a concordance index or CI of 0.66-0.67. When restricting the analysis to patients with stage III disease (n=32), the same subregion achieved an even higher CI of 0.75 (hazard ratio 3.93, log-rank P=.002) for predicting OS, and a CI of 0.76 (hazard ratio 4.84, log-rank P=.002) for predicting OFP. In comparison, conventional imaging markers, including tumor volume, maximum standardized uptake value, and metabolic tumor volume using threshold of 50% standardized uptake value maximum, were not predictive of OS or OFP, with CI mostly below 0.60 (log-rank P>.05). Conclusion: We propose a robust intratumor partitioning method to identify clinically relevant, high-risk subregions in lung cancer. We envision that this approach will be applicable to identifying useful imaging biomarkers in many cancer types.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Architecture and method for a burst buffer using flash technology

A parallel supercomputing cluster includes compute nodes interconnected in a mesh of data links for executing an MPI job, and solid-state storage nodes each linked to a respective group of the compute nodes for receiving checkpoint data from the respective compute nodes, and magnetic disk storage linked to each of the solid-state storage nodes for asynchronous migration of the checkpoint data from the solid-state storage nodes to the magnetic disk storage. Each solid-state storage node presents a file system interface to the MPI job, and multiple MPI processes of the MPI job write the checkpoint data to a shared file in the solid-state storage in a strided fashion, and the solid-state storage node asynchronously migrates the checkpoint data from the shared file in the solid-state storage to the magnetic disk storage and writes the checkpoint data to the magnetic disk storage in a sequential fashion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

State Preparation of Antisymmetrized Geminal Power on a Quantum Computer without Number Projection

The antisymmetrized geminal power (AGP) is equivalent to the number projected Bardeen–Cooper–Schrieffer (PBCS) wave function. It is also an elementary symmetric polynomial (ESP) state. We generalize previous research on deterministically implementing the Dicke state to a state preparation algorithm for an ESP state, or equivalently AGP, on a quantum computer. Our method is deterministic and has polynomial cost, and it does not rely on number symmetry breaking and restoration. We also show that our circuit is equivalent to a disentangled unitary paired coupled cluster operator and a layer of unitary Jastrow operator acting on a single Slater determinant. Here, the method presented herein highlights the ability of disentangled unitary coupled cluster to capture nontrivial entanglement properties that are hardly accessible with traditional Hartree–Fock based electronic structure methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Coupled-cluster based approach for core-level states in condensed phase: Theory and application to different protonated forms of aqueous glycine

A theoretical approach for calculating core-level states in condensed phase is presented. The approach is based on equation-of-motion coupled-cluster theory (EOMCC) and effective fragment potential (EFP) method. By introducing an approximate treatment of double excitations in the EOM-CCSD (EOM-CC with single and double substitutions) ansatz, we address poor convergence issues that are encountered for the core-level states and significantly reduce computational costs. While the approximations introduce relatively large errors in the absolute values of transition energies, the errors are systematic. Consequently, chemical shifts, changes in ionization energies relative to reference systems, are reproduced reasonably well. By using different protonation forms of solvated glycine as a benchmark system, we show that our protocol is capable of reproducing the experimental chemical shifts with a quantitative accuracy. The results demonstrate that chemical shifts are very sensitive to the solvent interactions and that explicit treatment of solvent, such as EFP, is essential for achieving quantitative accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Capturing many-body correlation effects with quantum and classical computing

Theoretical descriptions of excited states of molecular systems in high-energy regimes are crucial for supporting and driving many experimental efforts at light source facilities. However, capturing their complicated correlation effects requires formalisms that provide a hierarchical infrastructure of approximations. These approximations lead to an increased overhead in classical computing methods and, therefore, decisions regarding the ranking of approximations and the quality of results must be made on purely numerical grounds. The emergence of quantum computing methods has the potential to change this situation. Here, in this study, we demonstrate the efficiency of the quantum phase estimator (QPE) in identifying core-level states relevant to x-ray photoelectron spectroscopy. We compare and validate the QPE predictions with exact diagonalization and real-time equation-of-motion coupled-cluster formulations, which are some of the most accurate methods for states dominated by collective correlation effects.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

The distances to open clusters from main-sequence fitting. V. Extension of color calibration and test using cool and metal-rich stars in NGC 6791

We extend our effort to calibrate stellar isochrones in the Johnson–Cousins (BVI{sub C}) and the 2MASS (JHK{sub s}) filter systems based on observations of well-studied open clusters. Using cool main-sequence (MS) stars in Praesepe, we define empirical corrections to the Lejeune et al. color–effective temperature (T{sub eff}) relations down to T{sub eff}∼3600 K, complementing our previous work based on the Hyades and the Pleiades. We apply empirically corrected isochrones to existing optical and near-infrared photometry of cool (T{sub eff}≲5500 K) and metal-rich ([Fe/H]= +0.37) MS stars in NGC 6791. The current methodology relies on an assumption that color–T{sub eff} corrections are independent of metallicity, but we find that estimates of color excess and distance from color–magnitude diagrams with different color indices converge on each other at the precisely known metallicity of the cluster. Along with a satisfactory agreement with eclipsing binary data in the cluster, we view the improved internal consistency as a validation of our calibrated isochrones at super-solar metallicities. For very cool stars (T{sub eff}≲4800 K), however, we find that B − V colors of our models are systematically redder than the cluster photometry by ∼0.02 mag. We use color–T{sub eff} transformations from the infrared flux method and alternative photometry to examine a potential color-scale error in the input cluster photometry. After excluding B − V photometry of these cool MS stars, we derive E(B − V)=0.105±0.014, [M/H] = +0.42±0.07, (m − M){sub 0}=13.04±0.08, and the age of 9.5 ± 0.3 Gyr for NGC 6791.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1987

The application of time series models to cloud field morphology analysis

A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

Chin, Roland T.↗
DOE OSTI2016

SU-G-TeP3-14: Three-Dimensional Cluster Model in Inhomogeneous Dose Distribution

Purpose: We aim to investigate 3D cluster formation in inhomogeneous dose distribution to search for new models predicting radiation tissue damage and further leading to new optimization paradigm for radiotherapy planning. Methods: The aggregation of higher dose in the organ at risk (OAR) than a preset threshold was chosen as the cluster whose connectivity dictates the cluster structure. Upon the selection of the dose threshold, the fractional density defined as the fraction of voxels in the organ eligible to be part of the cluster was determined according to the dose volume histogram (DVH). A Monte Carlo method was implemented to establish a case pertinent to the corresponding DVH. Ones and zeros were randomly assigned to each OAR voxel with the sampling probability equal to the fractional density. Ten thousand samples were randomly generated to ensure a sufficient number of cluster sets. A recursive cluster searching algorithm was developed to analyze the cluster with various connectivity choices like 1-, 2-, and 3-connectivity. The mean size of the largest cluster (MSLC) from the Monte Carlo samples was taken to be a function of the fractional density. Various OARs from clinical plans were included in the study. Results: Intensive Monte Carlo study demonstrates the inverse relationship between the MSLC and the cluster connectivity as anticipated and the cluster size does not change with fractional density linearly regardless of the connectivity types. An initially-slow-increase to exponential growth transition of the MSLC from low to high density was observed. The cluster sizes were found to vary within a large range and are relatively independent of the OARs. Conclusion: The Monte Carlo study revealed that the cluster size could serve as a suitable index of the tissue damage (percolation cluster) and the clinical outcome of the same DVH might be potentially different.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

Quantum cluster equilibrium model of N-methylformamide–water binary mixtures

The established quantum cluster equilibrium (QCE) approach is refined and applied to N-methylformamide (NMF) and its aqueous solution. The QCE method is split into two iterative cycles: one which converges to the liquid phase solution of the QCE equations and another which yields the gas phase. By comparing Gibbs energies, the thermodynamically stable phase at a given temperature and pressure is then chosen. The new methodology avoids metastable solutions and allows a different treatment of the mean-field interactions within the gas and liquid phases. These changes are of crucial importance for the treatment of binary mixtures. For the first time in a QCE study, the cis-trans-isomerism of a species (NMF) is explicitly considered. Cluster geometries and frequencies are calculated using density functional theory (DFT) and complementary coupled cluster single point energies are used to benchmark the DFT results. Independent of the selected quantum-chemical method, a large set of clusters is required for an accurate thermodynamic description of the binary mixture. The liquid phase of neat NMF is found to be dominated by the cyclic trans-NMF pentamer, which can be interpreted as a linear trimer that is stabilized by explicit solvation of two further NMF molecules. This cluster reflects the known hydrogen bond network preferences of neat NMF.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Bootstrap AMG for spectral clustering

Graph Laplacian is a popular tool for analyzing graphs, particularly in graph partitioning and clustering. Given a notion of similarity (via an adjacency matrix), graph clustering refers to identifying different groups such that vertices in the same group are more similar compared to vertices across different groups. Data clustering can be reformulated in terms of a graph clustering problem when the given set of data is represented as a graph, also known as similarity graph. In this context, eigenvectors of the graph Laplacian are often used to obtain a new geometric representation of the original data set that generally enhances cluster properties and improves cluster detection. Here, we apply a bootstrap algebraic multigrid (AMG) method that constructs a set of vectors associated with the graph Laplacian. These vectors, referred to as algebraically smooth ones, span a low-dimensional Euclidean space, which we use to represent the data, enabling cluster detection both in synthetic and in realistic well-clustered graphs. We show that, in the case of a good quality bootstrap AMG, the computed smooth vectors employed in the construction of the final AMG operator, which by construction is spectrally equivalent to the originally given graph Laplacian, accurately approximate the space in the lower portion of the spectrum of the preconditioned operator. Thus, our approach can be viewed as a spectral clustering technique associated with the generalized spectral problem (Laplace operator versus the final AMG operator), and hence, it can be seen as an extension of the classical spectral clustering that employs a standard eigenvalue problem.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Computation and parallel implementation for early vision

The problem of early vision is to transform one or more retinal illuminance images-pixel arrays-to image representations built out of such primitive visual features such as edges, regions, disparities, and clusters. These transformed representations form the input to later vision stages that perform higher level vision tasks including matching and recognition. Researchers developed algorithms for: (1) edge finding in the scale space formulation; (2) correlation methods for computing matches between pairs of images; and (3) clustering of data by neural networks. These algorithms are formulated for parallel implementation of SIMD machines, such as the Massively Parallel Processor, a 128 x 128 array processor with 1024 bits of local memory per processor. For some cases, researchers can show speedups of three orders of magnitude over serial implementations.

Gualtieri, J. Anthony↗
DOE OSTI2026

Bond Dissociation Energies of the Actinide Halides AnX, An = Ac–Lr and X = F–I, Utilizing Relativistic Composite Coupled Cluster Approaches

Bond dissociation energies (BDEs) have been calculated for the set of actinide halides AnX with An=Ac, Pa, and Np-Lr and X=F-I. Two composite thermochemistry methods based on the Feller-Peterson-Dixon (FPD) approach have been utilized, one involving spinor-based relativistic CCSD(T) calculations where spin-orbit (SO) was included at the orbital level and another using scalar relativistic CCSD(T) with a posteriori SO contributions based on 2-component multireference configuration interaction calculations. The method that was chosen for a given actinide halide was based on which representation yielded the best single determinant reference determinant for the coupled cluster calculation. The spinor-based method was chosen for all cases except for AmX, CmX, and BkX. Both composite approaches included contributions accounting for basis set truncation, outer-core correlation, the Gaunt interaction, and QED. The scalar FPD results, as well as the spinor-based calculations for AcF, also included higher order electron correlation up through CCSDT(Q). In addition to BDEs, CCSD(T) equilibrium bond lengths, harmonic frequencies, and vibrational anharmonicity constants are reported for all species. Last, the FPD BDEs for the fluorides were used to confirm the trend across the actinide series previously predicted by Gibson using bonding models based atomic promotion energies that provide a single 6d electron for bonding. In particular the local minimum in the BDEs at AmF is confirmed in the present calculations. Furthermore, the BDEs for LrX are predicted to be slightly larger than those of AcX, making them the largest in the actinide halide series.

Actinides↗
DOE OSTI2015

A full-configuration-interaction nuclear orbital approach and application for small doped He clusters

An efficient full-configuration-interaction 'nuclear orbital' treatment was developed as a benchmark quantum-chemistry-like method to calculate, ground and excited, fermionic 'solvent' wave-functions and applied to {sup 3}He{sub N} clusters with atomic or molecular impurities [J. Chem. Phys. (Communication) 125, 221101 (2006)]. The main difficulty in handling doped {sup 3}He{sub N} clusters lies in the Fermi-Dirac nuclear statistics, the wide amplitudes of the He-dopant and He-He motions, and the hard-core He-He interaction at short distances. This paper overviews the theoretical approach and its recent applications to energetic, structural and spectroscopic aspects of different dopant-{sup 3}He{sub N} clusters. Preliminary results by using the latest version of the FCI-NO computational implementation, to bosonic Cl{sub 2}(X)-({sup 4}He){sub N} clusters, are also shown.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

ON THE DISCREPANCY BETWEEN THEORETICAL AND X-RAY CONCENTRATION-MASS RELATIONS FOR GALAXY CLUSTERS

In the past 15 years, the concentration-mass relation has been investigated diffusely in theoretical studies. On the other hand, only recently has this relation been derived from X-ray observations. When that happened, the results caused a certain level of concern: the X-ray normalizations and slopes were found significantly dissimilar from those predicted by theory. We analyzed 52 galaxy clusters and groups, simulated with different descriptions of the physical processes that affect the baryonic component, with the purpose of determining whether these discrepancies are real or induced by biases in the computation of the concentration parameter or in the determination of the selection function of the cluster sample for which the analysis is carried out. In particular, we investigate how the simulated concentration-mass relation depends (1) on the radial range used to derive the concentration; (2) on the presence of baryons in the simulations, and on the effect of star formation and feedback from supernovae and active galactic nuclei (AGNs). Finally, we evaluate (3) how the results differ when adopting an X-ray approach for the analysis and (4) how the selection function based on X-ray luminosity can impact the results. All effects studied go in the direction of alleviating the discrepancy between observations and simulations, although with different significance: while the choice of the radial range to fit the profiles and the inclusion of the baryonic component play only a minor role, the X-ray approach to reconstruct the mass profiles and the selection of the cluster sample have a strong impact on the resulting concentration-mass relation. Extending the fit to the most central regions or reducing the fitting radius from the virial boundary to the typical X-ray external radius causes an increase of the normalization in radiative simulations by 5%-10%. In the second case, we measure a slope that is up to twice steeper than that derived by using the typical theoretical radial range. Radiative simulations including only supernova feedback produce 30% higher concentrations than the dark matter case. Such a difference is largely reduced when including the effect of AGN feedback. The concentration-mass relation derived from the X-ray synthetic catalog is significantly steeper due to the combination of several different effects, such as environment, dynamical state and dynamical history of the clusters, bias in mass and temperature measurements, and their dependence on the radius and on the mass of the system. Finally, selecting clusters according to their X-ray luminosity produces a net increase in both normalization and slope of the relation, since at fixed mass, the most luminous clusters are also the most concentrated.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

Spectroscopy of the young cluster Blanco 1

We present spectroscopic observations of some 115 stars of the cluster Blanco 1, extending from the Ca II(H,K) region to the Ca II(I-R) triplet, supporting an age similar to that of the young cluster alpha Persei. The H-alpha absorption equivalent with vs (B - V) diagram forms a well-defined locus, with decreasing absorption equivalent width for decreasing effective temperature, akin to solar neighborhood dwarfs. A large spread in the Ca II surface flux, as a function of (B - V), also indicates the presence of a high degree of surface inhomogeneity, synonymous with high magnetic activity in young stars. A drop-off in the Ca II flux at (B - V) = 1.0 is also similar to the solar neighborhood stars, and shows that the primary chromospheric cooling changes from the Ca II and Mg II lines to the Balmer lines. The mean chromospheric temperature for stars at 4800 K lies between 8000 K and 10,000 K, based on theoretical models, which is somewhat higher than the older solar neighborhood dwarfs. The high mean Ca II surface flux of the sample is also consistent with that of other young clusters. We were able to measure the equivalent width of the Li(6708) line, whose strength as a function of (B - V) indicates an age similar to the young cluster alpha Persei. The lithium abundance decreases with decreasing effective temperature, consistent with the premise of lithium depletion in stars with larger convection zones. Using published photometry and a recent Zero Age Main Sequence (ZAMS) fitting method, we also re-define the distance to the cluster to be 246 pc.

Panagi, P. M.↗
DOE OSTI2020

The influence of lattice defects, recombination, and clustering on thermal transport in single crystal thorium dioxide

Thermal transport is a key controlling property for thorium dioxide in many applications where defect-generating radiation fields are present. An understanding of the effect of nanoscale lattice defects on thermal transport in this material is currently unavailable due to a lack of high-quality, single crystal material from which unit processes may be investigated. In this work, a series of thorium dioxide single crystals are exposed to 2 MeV proton irradiation at room temperature and 600°C to create microscale regions with varying densities and types of point and extended defects. Defected regions are investigated using spatial domain thermoreflectance to quantify the change in thermal conductivity as a function of ion fluence as well as transmission electron microscopy and Raman spectroscopy to interrogate the structure of the generated defects. Together, this com- bination of methods provides important initial insight into defect formation, recombination, and clustering in thorium dioxide and the effect of those defects on thermal transport. These methods also provide a promising pathway for the quantification of the smallest-scale defects which cannot be captured using traditional microscopy techniques and play and outsized role in degrading thermal performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗