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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Copacabana: a probabilistic membership assignment method for galaxy clusters

Cosmological analyses using galaxy clusters in optical/near-infrared photometric surveys require robust characterization of their galaxy content. Precisely determining which galaxies belong to a cluster is crucial. In this paper, we present the COlor Probabilistic Assignment of Clusters And BAyesiaN Analysis (Copacabana) algorithm. Copacabana computes membership probabilities for all galaxies within an aperture centred on the cluster using photometric redshifts, colours, and projected radial probability density functions. We use simulations to validate Copacabana and we show that it achieves up to 89 per cent membership accuracy with a mild dependence on photometric redshift uncertainties and choice of aperture size. We find that the precision of the photometric redshifts has the largest impact on the determination of the membership probabilities followed by the choice of the cluster aperture size. We also quantify how much these uncertainties in the membership probabilities affect the stellar mass–cluster mass scaling relation, a relation that directly impacts cosmology. Using the sum of the stellar masses weighted by membership probabilities (⁠μ * ⁠) as the observable, we find that Copacabana can reach an accuracy of 0.06 dex in the measurement of the scaling relation at low redshift for a Legacy Survey of Space and Time type survey. These results indicate the potential of Copacabana and μ * to be used in cosmological analyses of optically selected clusters in the future.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Synchronization and Rebound Effects in Residential Loads

Increasing fuel prices and capacity investment deferral place an increasing demand for peak reduction from distribution level systems. Residential and commercial devices, such as HVAC systems and water heaters, are increasingly involved in load control programs, and their use may generate synchronization and rebound effects, such as artificial peaks caused by device optimization. While there have been concerns over device synchronization, few studies quantify the extent of this effect with numerical values. In this study, we attempt to investigate whether control efforts result in device synchronization or rebound effects. We focus on three clustering methods – Ward’s clustering, Euclidean K-means, and Density-based spatial clustering of applications with noise – to evaluate the extent of synchronization of a fleet of water heaters and HVAC systems in Atlanta, Georgia. Our findings show that synchronization and rebound effects are present in the neighborhood’s water heaters, but none were found in the HVAC systems. Further, high usage water heaters are more susceptible to synchronization and rebound effects.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1985

Applications of Fuzzy Set Theory to Satellite Soundings

The introduction of an appropriate fuzzy setting for satellite soundings and its application to clustering methods via unimodal fuzzy sets in the future is proposed. Methods of hard clustering analysis and fuzzy partitioned clustering were applied on simulated data with very encouraging results. The proposed clustering technique is discussed. The notion of a unimodal fuzzy set was chosen to represent the partition of a data set for two reasons: (1) it detects all the locations in the vector space where highly concentrated clusters of points exist; and (2) the notion is general enough to represent clusters that exhibit quite general distributions of points. The technique detects all of the existing unimodal fuzzy sets and realizes the maximum separation among them. It is economical in memory space and computational time requirements and also detects groups that are fairly generally distributed in the feature space.

Munteanu, M. J.↗
DOE OSTI2021

Incorporating historical data and past analyses for improved tensile property prediction of 9% Cr steel

Data-driven analytical clustering and visualization techniques were applied to the dataset of 9% Cr experimental alloy data generated through the eXtremeMAT project. Techniques and results were compared with the resulting clusters obtained through similar analytical techniques on previous and reduced versions of the dataset. The principal components were generated in order to reduce the dimensionality of the complex dataset and to visualize the underlying trends in the data. Partitioning around medoids was performed on the resulting principal components to determine relevant clusters. Domain knowledge labels were further applied to the principal components to compare the labels with the trends identified through the clustering methods. The resulting clusters show the addition of the new data into the dataset, and show where alignment between the domain knowledge labels and partitioning around medoids (PAM) clusters show where the labels are appropriate. The clusters can be used to compare the tensile properties of the alloys, and to reduce the variation in the dataset.

Alloy design, Mechanical Properties, data analysis↗
DOE OSTI2023

Coupled-cluster theory for strong entanglement in nuclei

Atomic nuclei can exhibit shape coexistence and multireference physics that enters in their ground states, and accurately capturing the ensuing correlations and entanglement is challenging. Here, we address this problem by applying single-reference coupled-cluster theory based on spherical and deformed reference states and the tailored coupled-cluster method. The latter combines configuration interactions to capture static correlations with coupled-cluster theory for dynamic correlations. We compute the atomic nuclei 12 C, 28 Si, and 56 Ni and find that the tailored coupled-cluster method and the single-reference approach based on a deformed Hartree-Fock state yield the most accurate results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1992

Ab initio multireference study of the BN molecule

The lowest 1Sigma(+) and 3Pi states of the BN molecule are studied using multireference configuration interaction (MRCI) and averaged coupled-pair functional (ACPF) methods and large atomic natural orbital (ANO) basis sets, as well as several coupled cluster methods. Our calculations strongly support a 3Pi ground state, but the a1Sigma(+) state lies only 381 +/- 100/cm higher. The a1Sigma(+) state wave function exhibits strong multireference character and, consequently, the predictions of the perturbationally-based single-reference CCSD(T) coupled cluster method are not as reliable in this case as the multireference results. The theoretical predictions for the spectroscopic constants of BN are in good agreement with experiment for the Chi3Pi state, but strongly suggest a misassignment of the fundamental vibrational frequency for the a1Sigma(+) state.

Martin, J. M. L.↗
DOE OSTI2022

Intertwined spin, charge, and pair correlations in the two-dimensional Hubbard model in the thermodynamic limit

Significance The high-temperature superconducting cuprates are governed by intertwined striped magnetic and charge orders, in addition to superconductivity. Remarkably similar behavior has also been seen in numerical calculations for the Hubbard model describing the copper–oxygen layers in these materials. Finite-cluster methods typically find that spin- and charge-stripe order dominates, while embedded quantum-cluster methods, which access the thermodynamic limit, often conclude that superconductivity does. Here, we report the observation of fluctuating spin and charge stripes in an embedded cluster calculation for the Hubbard model. This discovery demonstrates that striped states survive in the thermodynamic limit and allows us to study their influence on the model’s superconducting properties, where we find evidence for pair-density-wave correlations intertwined with the stripe correlations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Solid-state materials formed of molecular clusters and method of forming same

A solid-state material comprising a solid-state compound is provided. The solid-state compound has the formula: [Cluster1][Cluster2]n, where Cluster1 can be a metal chalcogenide molecular cluster, Cluster2 a carbon cluster, and n the number of Cluster2 clusters in the solid-state compound. A method of forming a solid-state material is also provided.

Nuckolls, Colin↗
DOE OSTI2021

Multi-channel Imager Algorithm (MIA): A novel cloud-top phase classification algorithm

The current Geostationary Operational Environmental Satellites (GOES-16 and 17) cloud-top phase classification algorithm is based primarily on empirical thresholds at multiple wavelengths that have varying absorption capabilities for water and ice. The performance of current GOES-16 cloud-top phase product largely depends on the accuracy of the selection of reflectance ratios. Here this study aims at presenting a novel cloud-top phase classification algorithm (the Multi-channel Imager Algorithm, MIA) that provides a more judicious selection of relationships between channels using a supervised K-mean clustering method on multi-channel Red-Green-Blue images. The K-mean clustering method works analogously to how human eyes separate different colors in a microphysical color rendering set of satellite images, which differentiates water, ice and unclassified thin clouds. For water phase, cloud-top temperature information is used to further distinguish supercooled water. To evaluate the performance of the MIA, an extensive comparison with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer, and current GOES-16 cloud-top phase products is conducted, using CALIOP as the benchmark. Compared to the current GOES-16 cloud-top phase product, MIA demonstrates a substantial improvement in phase classification, where hit rate increases from 69% to 76% over the Continental United States and 58% to 66% over the full disk domain.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

A possibilistic approach to clustering

Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering methods in that total commitment of a vector to a given class is not required at each image pattern recognition iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from the 'Fuzzy C-Means' (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Recently, we cast the clustering problem into the framework of possibility theory using an approach in which the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

Krishnapuram, Raghu↗
DOE OSTI2018

Time resolved surface photovoltage measurements using a big data capture approach to KPFM

Optoelectronic behavior in materials such as organic/inorganic hybrid perovskites depend on a complex interplay between fast (electronic) and slower (ionic) processes. These processes are thought to be influenced by structural inhomogeneities (e.g. interfaces and grain boundaries) bringing forward the necessity for development of techniques capable of correlating nanostructure and photo-transport behavior. While Kelvin probe force microscopy (KPFM) is ideally suited to map surface potentials on relevant length scales, it lacks sufficient temporal resolution to extract the meaningful system dynamics. Here, we develop a time resolved surface photovoltage (SPV) measurement based on full information capture of the photodetector stream during open loop KPFM operation. G-Mode, or G-KPFM allows quantification of SPV with microsecond temporal and nanoscale spatial resolution. Using this technique, we observe concurrent spatial and fast temporal variations in the SPV generated across a methylammonium lead bromide (MAPbBr3) thin film, a possible indicator relating microstructure with heterogenous photo-transport behavior. Here, we further demonstrate the advantage of adopting big data analytics including unsupervised clustering methods to quickly discern spatial variability in the information rich SPV dataset. Beyond G-KPFM, such clustering methods will be useful for interpretation of the multidimensional datasets arising from the growing number of time resolved KPFM approaches now available.

36 MATERIALS SCIENCE↗
NASA NTRS2005

Constrained spectral clustering under a local proximity structure assumption

This work focuses on incorporating pairwise constraints into a spectral clustering algorithm. A new constrained spectral clustering method is proposed, as well as an active constraint acquisition technique and a heuristic for parameter selection. We demonstrate that our constrained spectral clustering method, CSC, works well when the data exhibits what we term local proximity structure.

domain knowledge↗
DOE OSTI2018

Microscopic optical potentials for calcium isotopes

We construct nucleonic microscopic optical potentials by combining the Green's function approach with the coupled-cluster method for 40 Ca and 48 Ca. For the computation of the ground states of 40 Ca and 48 Ca, we use the coupled-cluster method in the singles-and-doubles approximation, while for the A = ±1 nuclei we use particle-attached and particle-removed equation-of-motion method truncated at two-particle–one-hole and one-particle–two-hole excitations, respectively. Our calculations are based on the chiral nucleon-nucleon and three-nucleon interaction NNLO sat , which reproduces the charge radii of 40 Ca and 48 Ca, and the chiral nucleon-nucleon interaction NNLO opt . In all cases considered here, we observe that the overall form of the neutron scattering cross section is reproduced for both interactions, but the imaginary part of the potential, which reflects the loss of flux in the elastic channel, is negligible. Furthermore, the latter points to neglected many-body correlations that would appear beyond the coupled-cluster truncation level considered in this work. We show that, by artificially increasing the parameter η in the Green's function, practical results can be further improved.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Ultrafast infrared transient absorption spectroscopy of gas-phase Ni(CO) 4 photodissociation at 261 nm

Here, we employ ultrafast mid-infrared transient absorption spectroscopy to probe the rapid loss of carbonyl ligands from gas-phase nickel tetracarbonyl following ultraviolet photoexcitation at 261 nm. Here, nickel tetracarbonyl undergoes prompt dissociation to produce nickel tricarbonyl in a singlet excited state; this electronically excited tricarbonyl loses another CO group over tens of picoseconds. Our results also suggest the presence of a parallel, concerted dissociation mechanism to produce nickel dicarbonyl in a triplet excited state, which likely dissociates to nickel monocarbonyl. Mechanisms for the formation of these photoproducts in multiple electronic excited states are theoretically predicted with one-dimensional cuts through the potential energy surfaces and computation of spin–orbit coupling constants using equation of motion coupled cluster methods (EOM-CC) and coupled cluster theory with single and double excitations (CCSD). Bond dissociation energies are calculated with CCSD, and anharmonic frequencies of ground and excited state species are computed using density functional theory (DFT) and time-dependent density functional theory (TD-DFT).

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

Transition properties from the Hermitian formulation of the coupled cluster polarization propagator

Theory of one-electron transition density matrices has been formulated within the time-independent coupled cluster method for the polarization propagator [R. Moszynski, P. S. Żuchowski, and B. Jeziorski, Coll. Czech. Chem. Commun. 70, 1109 (2005)]. Working expressions have been obtained and implemented with the coupled cluster method limited to single, double, and linear triple excitations (CC3). Selected dipole and quadrupole transition probabilities of the alkali earth atoms, computed with the new transition density matrices are compared to the experimental data. Good agreement between theory and experiment is found. The results obtained with the new approach are of the same quality as the results obtained with the linear response coupled cluster theory. The one-electron density matrices for the ground state in the CC3 approximation have also been implemented. The dipole moments for a few representative diatomic molecules have been computed with several variants of the new approach, and the results are discussed to choose the approximation with the best balance between the accuracy and computational efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

A cluster analysis method for identification of subpopulations of cells in flow cytometric list-mode arrays

A specialized program was developed for flow cytometric list-mode data using an heirarchical tree method for identifying and enumerating individual subpopulations, the method of principal components for a two-dimensional display of 6-parameter data array, and a standard sorting algorithm for characterizing subpopulations. The program was tested against a published data set subjected to cluster analysis and experimental data sets from controlled flow cytometry experiments using a Coulter Electronics EPICS V Cell Sorter. A version of the program in compiled BASIC is usable on a 16-bit microcomputer with the MS-DOS operating system. It is specialized for 6 parameters and up to 20,000 cells. Its two-dimensional display of Euclidean distances reveals clusters clearly, as does its 1-dimensional display. The identified subpopulations can, in suitable experiments, be related to functional subpopulations of cells.

Li, Z. K.↗
DOE OSTI2019

Methods for cluster cosmology and application to the SDSS in preparation for DES Year 1 release

ABSTRACT We implement the first blind analysis of cluster abundance data to derive cosmological constraints from the abundance and weak lensing signal of redMaPPer clusters in the Sloan Digital Sky Survey (SDSS). We simultaneously fit for cosmological parameters and the richness–mass relation of the clusters. For a flat Λ cold dark matter cosmological model with massive neutrinos, we find $S_8 \equiv \sigma _{8}(\Omega _\mathrm{ m}/0.3)^{0.5}=0.79^{+0.05}_{-0.04}$. This value is both consistent and competitive with that derived from cluster catalogues selected in different wavelengths. Our result is also consistent with the combined probes analyses by the Dark Energy Survey (DES), the Kilo-Degree Survey (KiDS), and with the cosmic microwave background (CMB) anisotropies as measured by Planck. We demonstrate that the cosmological posteriors are robust against variation of the richness–mass relation model and to systematics associated with the calibration of the selection function. In combination with baryon acoustic oscillation data and big bang nucleosynthesis data (Cooke et al.), we constrain the Hubble rate to be h = 0.66 ± 0.02, independent of the CMB. Future work aimed at improving our understanding of the scatter of the richness–mass relation has the potential to significantly improve the precision of our cosmological posteriors. The methods described in this work were developed for use in the forthcoming analysis of cluster abundances in the DES. Our SDSS analysis constitutes the first part of a staged-unblinding analysis of the full DES data set.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Modeling microstructural evolution in irradiated materials with cluster dynamics methods: A review

As both the design of material systems for nuclear energy applications and the number of reactor designs being proposed increase the need for material models predicting the evolution of microstructures as a function of chemistry, texture, grain size, precipitate content, etc., and irradiation conditions is steadily increasing. Here, this manuscript aims at presenting a review of the different cluster dynamics modeling schemes that have emerged worldwide over the past decade(s). Additionally, the manuscript also critically discusses limitations in existing approaches and identifies potential routes for future developments.

36 MATERIALS SCIENCE↗