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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Fusion of Surface Ceilometer Data and Satellite Cloud Retrievals in 2D Mesh Interpolating Model with Clustering

For accurate cloud ceiling information, a data fusion approach is proposed that utilizes satellite data to extend surface station information to much wider areas. Cloud base height (CBH) retrieved from satellite observations provides for much larger spatial coverage and higher resolution. The direct comparison of GOES-16 CBH with surface station ceiling yields a local bias that has to be corrected for in the initial GOES-16 cloud base information. This sparsely sampled bias correction presents an irregular 2D mesh of control points, which is then interpolated by constructing a continuous smooth field using polyharmonic splines. The influence of remote stations is restricted by grouping the control points into clusters depending on an effective distance. This cluster-based approach allows for constructing separate spline surfaces corresponding to physically different clouds. The obtained continuous bias correction function is then applied to the entire GOES-16 pixel level CBH except for areas far away from surface stations in data sparse regions such as offshore. The described method is currently being tested using daytime-only observations over the central and eastern United States. Overall, this approach has potential to provide more accurate, high spatial resolution cloud ceiling information for the aviation community.

Khlopenkov, Konstantin↗
DOE OSTI2018

Heat of Melting of Small Clusters in the Model of the Potential with the Effective Well Depth

Within the framework of the cluster model using the Mie pair power-law interaction potential with the effective depth of the potential well, whose depth is determined by the number of particles in the cluster, an equation for the calculation of the heat of melting of cluster systems is obtained. The resulting mathematical expression does not contain empirical constants and shows that the ratio of the heat of melting of a cluster to the heat of melting of a macroscopic sample is a universal function of the number of particles in the cluster and mathematically described by the square of the hyperbolic tangent.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Cluster structure of light nuclei

We review recent studies of the cluster structure of light nuclei within the framework of the algebraic cluster model (ACM) for nuclei composed of k α-particles and within the framework of the cluster shell model (CSM) for nuclei composed of k α-particles plus x additional nucleons. The calculations, based on symmetry considerations and thus for the most part given in analytic form, are compared with experiments in light cluster nuclei. The comparison shows evidence for Z 2 , D 3h and T d symmetry in the even–even nuclei 8 Be (k = 2), 12 C (k = 3) and 16 O (k = 4), respectively, and for the associated double groups Z' 2 and D' 3h in the odd nuclei 9 Be, 9 B (k = 2, x = 1) and 13 C (k = 3, x = 1), respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1991

A model for the evaporation of clusters of drops embedded in jet vortices. I - Steady injection of identical clusters

A model is developed for describing the interaction of vortex-drop clusters in a flowing gaseous jet, convecting downstream from an injection location. Results are presented for a stationary case representing the situation when identical clusters are continuously injected and the injection rate is constant. The results indicate that, in a rich mixture high-drop-number density regime, the mass evaporated from the drops controls the velocity of the cluster-in-vortex as it propagates downstream.

Bellan, J.↗
NASA NTRS1993

Software forecasting as it is really done: A study of JPL software engineers

This paper presents a summary of the results to date of a Jet Propulsion Laboratory internally funded research task to study the costing process and parameters used by internally recognized software cost estimating experts. Protocol Analysis and Markov process modeling were used to capture software engineer's forecasting mental models. While there is significant variation between the mental models that were studied, it was nevertheless possible to identify a core set of cost forecasting activities, and it was also found that the mental models cluster around three forecasting techniques. Further partitioning of the mental models revealed clustering of activities, that is very suggestive of a forecasting lifecycle. The different forecasting methods identified were based on the use of multiple-decomposition steps or multiple forecasting steps. The multiple forecasting steps involved either forecasting software size or an additional effort forecast. Virtually no subject used risk reduction steps in combination. The results of the analysis include: the identification of a core set of well defined costing activities, a proposed software forecasting life cycle, and the identification of several basic software forecasting mental models. The paper concludes with a discussion of the implications of the results for current individual and institutional practices.

Griesel, Martha Ann↗
DOE OSTI2015

Identifying the Interactions That Allow Separation of O 2 from N 2 on the Open Iron Sites of Fe 2 (dobdc)

The presence of open metal sites along with a high porosity makes the Fe 2 (dobdc) metal–organic framework, also called Fe-MOF-74, particularly well suited for separating gaseous mixtures. For instance, since Fe 2 (dobdc) adsorbs O 2 more strongly than N 2 , it can, in principle, be used to separate O 2 from air [Bloch et al., J. Am. Chem. Soc. 2011, 133, 14814]. Here, in the present work, we investigate the reversible differential adsorption of N 2 and O 2 on Fe 2 (dobdc) with Kohn-Sham density functional theory applied to an 88-atom cluster model of the MOF. The cluster is chosen such that it is large enough to allow an accurate description of the most important contributions to the binding enthalpies and small enough to perform high-level quantum mechanical calculations. For the quantum mechanical calculations, we use well-validated exchange–correlation functionals to study the ground-state structures of the Fe–N 2 and Fe–O 2 interacting systems. The calculations agree with experiment in that O 2 binds more strongly than N 2 , and they reveal that the ground-state structure of the Fe–O 2 subsystem has the dioxygen unit in a triplet spin state ferromagnetically coupled to the high-spin state (quintet state) of the iron center. Charge Model 5 (CM5) calculations have been performed to determine the partial atomic charges on the adsorbate molecules and the iron atom, and they show that charge transfer from the open iron(II) site is more important in the case of O 2 than in the case of N 2 . Furthermore, bond orders, vibrational frequencies, and orbital energies were calculated to rationalize the stronger binding of O 2 compared to N 2 on Fe 2 (dobdc).

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

Monte Carlo Explicitly Correlated Second-Order Many-Body Green’s Function Calculations of Semiconductor Band Gaps

A systematically converging series of ab initio, post-density-functional, size-consistent, electron-correlated approximations is desired for predictive computing of felectronic band structures of insulating, semiconducting, and metallic solids. A series that meets all of these desiderata (except the applicability to metals) is ab initio many-body Green's function theory based on Gaussian-type-orbital (GTO) basis sets. Here, its leading-order approximation, the second-order Green's function (GF2) method in the diagonal and frequency-independent approximations with the aug-cc-pVDZ basis set, is applied to the fundamental band gaps of three semiconductors (diamond, silicon, and silicon carbide in the zincblende structure) using cluster models. Corrections are made to the basis-set-incompleteness errors by the explicit-correlation (F12) ansatz (GF2-F12) for the valence band edges. The crystals are modeled as surface-passivated clusters of increasing sizes, whose wave functions are expanded by up to 2709 GTO basis functions. Immense computational costs of these calculations are overcome by the highly scalable stochastic algorithm of the Monte Carlo GF2-F12 method, whose operation cost per state increases only as a cubic power of system size, which has a tiny memory footprint and easily achieves near-perfect parallel efficiency on thousands of CPUs or on hundreds of GPUs. The correlated, F12-corrected highest-occupied and lowest-unoccupied molecular-orbital energy (HOMO-LUMO) gap is 5.78 ± 0.07 eV for C 87 H 76 as compared with the experimental value of the fundamental (indirect) band gap of bulk diamond at 5.48 eV. The correlated, F12-corrected HOMO-LUMO gaps for Si 75 H 76 and Si 32 C 43 H 76 are 2.56 ± 0.15 eV and 3.50 ± 0.12 eV, respectively, which are expected to decrease further with increasing cluster sizes. As a result, the experimental fundamental (indirect) band gaps of bulk silicon and silicon carbide are 1.17 eV and 2.42 eV, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

A Transferable Force Field for Predicting Adsorption and Diffusion of Water in Cationic Zeolites with Coupled Cluster Accuracy

We present a transferable force field for water in proton-exchanged, alkali (Li, Na, K, Rb, and Cs) metal-exchanged, and alkaline-earth (Mg, Ca, Sr, and Ba) metal-exchanged zeolites. The fitting methodology is based on adsorbate–adsorbent interaction energies obtained from periodic density functional theory calculations and corrected using the coupled-cluster method applied to small model clusters. To ensure an accurate prediction of both adsorption and diffusion properties of water, sets of configurations that sample both adsorption sites and intracrystalline hopping transition states were used in the fitting. The quality of the force field is assessed for a wide range of zeolites with different topologies and chemical compositions, demonstrating good agreement between theoretical predictions and experimental measurements of water adsorption and diffusion.

Adsorption↗
NASA NTRS2016

Linking Remotely Sensed Aerosol Types to Their Chemical Composition

Aerosol types measured during the Ship-Aircraft Bio-Optical Research (SABOR) experiment are related to GEOS-Chem model chemical composition. The application for this procedure to link model chemical components to aerosol type is desirable for understanding aerosol evolution over time. The Mahalanobis distance (DM) statistic is used to cluster model groupings of five chemical components (organic carbon, black carbon, sea salt, dust and sulfate) in a way analogous to the methods used by Burton et al. [2012] and Russell et al. [2014]. First, model-to-measurement evaluation is performed by collocating vertically resolved aerosol extinction from SABOR High Spectral Resolution LiDAR (HSRL) to the GEOS-Chem nested high-resolution data. Comparisons of modeled-to-measured aerosol extinction are shown to be within 35% +/- 14%. Second, the model chemical components are calculation into five variables to calculate the DM and cluster means and covariances for each HSRL-retrieved aerosol type. The layer variables from the model are aerosol optical depth (AOD) ratios of (i) sea salt and (ii) dust to total AOD, mass ratios of (iii) total carbon (i.e. sum of organic and black carbon) to the sum of total carbon and sulfate (iv) organic carbon to black carbon, and (v) the natural log of the aerosol-to-molecular extinction ratio. Third, the layer variables and at most five out of twenty SABOR flights are used to form the pre-specified clusters for calculating DM and to assign an aerosol type. After determining the pre-specified clusters, model aerosol types are produced for the entire vertically resolved GEOS-Chem nested domain over the United States and the model chemical component distributions relating to each type are recorded. Resulting aerosol types are Dust/Dusty Mix, Maritime, Smoke, Urban and Fresh Smoke (separated into 'dark' and 'light' by a threshold of the organic to black carbon ratio). Model-calculated DM not belonging to a specific type (i.e. not meeting a threshold probability) is termed an outlier and those DM values that can belong to multiple types (i.e. showing weak probability of belonging to a specific cluster) are termed as Overlap. MODIS active fires are overlaid on the model domain to qualitatively evaluate the model-predicted Smoke aerosol types.

Aerosol Types↗
DOE OSTI2018

Spinon Fermi Surface in a Cluster Mott Insulator Model on a Triangular Lattice and Possible Application to 1 T –TaS 2

1T-TaS 2 is a cluster Mott insulator on the triangular lattice with 13 Ta atoms forming a star of David cluster as the unit cell. We derive a two-dimensional XXZ spin-1/2 model with a four-spin ring exchange term to describe the effective low energy physics of a monolayer 1T-TaS 2 , where the effective spin-1/2 degrees of freedom arises from the Kramers degenerate spin-orbital states on each star of David. Here, a large scale density matrix renormalization group simulation is further performed on this effective model and we find a gapless spin liquid phase with a spinon Fermi surface at a moderate to large strength region of the four-spin ring exchange term. All peaks in the static spin structure factor are found to be located on the “2k F ” surface of a half-filled spinon on the triangular lattice. Experiments to detect the spinon Fermi surface phase in 1T-TaS 2 are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2015

A Symmetric Time-Varying Cluster Rate of Descent Model

A model of the time-varying rate of descent of the Orion vehicle was developed based on the observed correlation between canopy projected area and drag coefficient. This initial version of the model assumes cluster symmetry and only varies the vertical component of velocity. The cluster fly-out angle is modeled as a series of sine waves based on flight test data. The projected area of each canopy is synchronized with the primary fly-out angle mode. The sudden loss of projected area during canopy collisions is modeled at minimum fly-out angles, leading to brief increases in rate of descent. The cluster geometry is converted to drag coefficient using empirically derived constants. A more complete model is under development, which computes the aerodynamic response of each canopy to its local incidence angle.

Ray, Eric S.↗
DOE OSTI2017

Galaxy Cluster Pressure Profiles as Determined by Sunyaev Zel’dovich Effect Observations with MUSTANG and Bolocam. II. Joint Analysis of 14 Clusters

We present pressure profiles of galaxy clusters determined from high-resolution Sunyaev–Zel’dovich (SZ) effect observations of 14 clusters, which span the redshift range of 0.25<z<0.89. The procedure simultaneously fits spherical cluster models to MUSTANG and Bolocam data. In this analysis, we adopt the generalized NFW parameterization of pressure profiles to produce our models. Our constraints on ensemble-average pressure profile parameters, in this study γ, C {sub 500}, and P {sub 0}, are consistent with those in previous studies, but for individual clusters we find discrepancies with the X-ray derived pressure profiles from the ACCEPT2 database. We investigate potential sources of these discrepancies, especially cluster geometry, electron temperature of the intracluster medium, and substructure. We find that the ensemble mean profile for all clusters in our sample is described by the parameters [γ,C{sub 500},P{sub 0}]=[0.3{sub −0.1}{sup +0.1},1.3{sub −0.1}{sup +0.1},8.6{sub −2.4}{sup +2.4}], cool core clusters are described by [γ,C{sub 500},P{sub 0}] =[0.6{sub −0.1}{sup +0.1},0.9{sub −0.1}{sup +0.1},3.6{sub −1.5}{sup +1.5}], and disturbed clusters are described by [γ,C{sub 500},P{sub 0}]=[0.0{sub −0.0}{sup +0.1},1.5{sub −0.2}{sup +0.1},13.8{sub −1.6}{sup +1.6}]. Of the 14 clusters, 4 have clear substructure in our SZ observations, while an additional 2 clusters exhibit potential substructure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Star cluster formation in cosmological simulations. I. Properties of young clusters

We present a new implementation of star formation in cosmological simulations by considering star clusters as a unit of star formation. Cluster particles grow in mass over several million years at the rate determined by local gas properties, with high time resolution. The particle growth is terminated by its own energy and momentum feedback on the interstellar medium. We test this implementation for Milky Way-sized galaxies at high redshift by comparing the properties of model clusters with observations of young star clusters. We find that the cluster initial mass function is best described by a Schechter function rather than a single power law. In agreement with observations, at low masses the logarithmic slope is $\alpha \approx 1.8\mbox{–}2$, while the cutoff at high mass scales with the star formation rate (SFR). A related trend is a positive correlation between the surface density of the SFR and fraction of stars contained in massive clusters. Both trends indicate that the formation of massive star clusters is preferred during bursts of star formation. These bursts are often associated with major-merger events. We also find that the median timescale for cluster formation ranges from 0.5 to 4 Myr and decreases systematically with increasing star formation efficiency. Local variations in the gas density and cluster accretion rate naturally lead to the scatter of the overall formation efficiency by an order of magnitude, even when the instantaneous efficiency is kept constant. As a result, comparison of the formation timescale with the observed age spread of young star clusters provides an additional important constraint on the modeling of star formation and feedback schemes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Density functional investigation of intermolecular effects on {sup 13}C NMR chemical-shielding tensors modeled with molecular clusters

A quantum-chemical method for modeling solid-state nuclear magnetic resonance chemical-shift tensors by calculations on large symmetry-adapted clusters of molecules is demonstrated. Four hundred sixty five principal components of the {sup 13}C chemical-shielding tensors of 24 organic materials are analyzed. The comparison of calculations on isolated molecules with molecules in clusters demonstrates that intermolecular effects can be successfully modeled using a cluster that represents a local portion of the lattice structure, without the need to use periodic-boundary conditions (PBCs). The accuracy of calculations which model the solid state using a cluster rivals the accuracy of calculations which model the solid state using PBCs, provided the cluster preserves the symmetry properties of the crystalline space group. The size and symmetry conditions that the model cluster must satisfy to obtain significant agreement with experimental chemical-shift values are discussed. The symmetry constraints described in the paper provide a systematic approach for incorporating intermolecular effects into chemical-shielding calculations performed at a level of theory that is more advanced than the generalized gradient approximation. Specifically, NMR parameters are calculated using the hybrid exchange-correlation functional B3PW91, which is not available in periodic codes. Calculations on structures of four molecules refined with density plane waves yield chemical-shielding values that are essentially in agreement with calculations on clusters where only the hydrogen sites are optimized and are used to provide insight into the inherent sensitivity of chemical shielding to lattice structure, including the role of rovibrational effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2003

Effects of carbonyl bond, metal cluster dissociation, and evaporation rates on predictions of nanotube production in high-pressure carbon monoxide

The high-pressure carbon monoxide (HiPco) process for producing single-wall carbon nanotubes (SWNTs) uses iron pentacarbonyl as the source of iron for catalyzing the Boudouard reaction. Attempts using nickel tetracarbonyl led to no production of SWNTs. This paper discusses simulations at a constant condition of 1300 K and 30 atm in which the chemical rate equations are solved for different reaction schemes. A lumped cluster model is developed to limit the number of species in the models, yet it includes fairly large clusters. Reaction rate coefficients in these schemes are based on bond energies of iron and nickel species and on estimates of chemical rates for formation of SWNTs. SWNT growth is measured by the conformation of CO2. It is shown that the production of CO2 is significantly greater for FeCO because of its lower bond energy as compared with that of NiCO. It is also shown that the dissociation and evaporation rates of atoms from small metal clusters have a significant effect on CO2 production. A high rate of evaporation leads to a smaller number of metal clusters available to catalyze the Boudouard reaction. This suggests that if CO reacts with metal clusters and removes atoms from them by forming MeCO, this has the effect of enhancing the evaporation rate and reducing SWNT production. The study also investigates some other reactions in the model that have a less dramatic influence.

Models, Chemical↗
NASA NTRS2002

Effects of Carbonyl Bond and Metal Cluster Dissociation and Evaporation Rates on Predictions of Nanotube Production in HiPco

The high-pressure carbon monoxide (HiPco) process for producing single-wall carbon nanotubes (SWNT) uses iron pentacarbonyl as the source of iron for catalyzing the Boudouard reaction. Attempts using nickel tetracarbonyl led to no production of SWNTs. This paper discusses simulations at a constant condition of 1300 K and 30 atm in which the chemical rate equations are solved for different reaction schemes. A lumped cluster model is developed to limit the number of species in the models, yet it includes fairly large clusters. Reaction rate coefficients in these schemes are based on bond energies of iron and nickel species and on estimates of chemical rates for formation of SWNTs. SWNT growth is measured by the co-formation of CO2. It is shown that the production of CO2 is significantly greater for FeCO due to its lower bond energy as compared with that ofNiCO. It is also shown that the dissociation and evaporation rates of atoms from small metal clusters have a significant effect on CO2 production. A high rate of evaporation leads to a smaller number of metal clusters available to catalyze the Boudouard reaction. This suggests that if CO reacts with metal clusters and removes atoms from them by forming MeCO, this has the effect of enhancing the evaporation rate and reducing SWNT production. The study also investigates some other reactions in the model that have a less dramatic influence.

Scott, Carl D.↗
NASA NTRS1991

The formation of primordial binaries in globular clusters by star-disk interactions

The formation of primordial binaries in globular clusters is examined using simple numerical models. Clusters of protostars collapse until their velocity dispersion rises sufficiently to reverse the infall and the cluster reaches equilibrium. During the collapse, interactions between stars and protostellar disks lead to stellar capture. It is found that binary fraction of a few percent typically result. Binary formation is terminated when the velocity dispersion rises to a point at which most encounters result in disk destruction rather than capture. As a result, much gas is returned to the cluster ISM, limiting the star formation efficiency to a value significantly below 100 percent.

Murray, Stephen D.↗
NASA NTRS2016

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

uncertainty↗