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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

DEFINING THE PLAYERS IN HIGHER-ORDER NETWORKS: PREDICTIVE MODELING FOR REVERSE ENGINEERING FUNCTIONAL INFLUENCE NETWORKS

A difficult problem that is currently growing rapidly due to the sharp increase in the amount of high-throughput data available for many systems is that of determining useful and informative causative influence networks. These networks can be used to predict behavior given observation of a small number of components, predict behavior at a future time point, or identify components that are critical to the functioning of the system under particular conditions. In these endeavors incorporating observations of systems from a wide variety of viewpoints can be particularly beneficial, but has often been undertaken with the objective of inferring networks that are generally applicable. The focus of the current work is to integrate both general observations and measurements taken for a particular pathology, that of ischemic stroke, to provide improved ability to produce useful predictions of systems behavior. A number of hybrid approaches have recently been proposed for network generation in which the Gene Ontology is used to filter or enrich network links inferred from gene expression data through reverse engineering methods. These approaches have been shown to improve the biological plausibility of the inferred relationships determined, but still treat knowledge-based and machine-learning inferences as incommensurable inputs. In this paper, we explore how further improvements may be achieved through a full integration of network inference insights achieved through application of the Gene Ontology and reverse engineering methods with specific reference to the construction of dynamic models of transcriptional regulatory networks. We show that integrating two approaches to network construction, one based on reverse-engineering from conditional transcriptional data, one based on reverse-engineering from in situ hybridization data, and another based on functional associations derived from Gene Ontology, using probabilities can improve results of clustering as evaluated by a predictive model of transcriptional expression levels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Higgs bosons in a minimal R-parity conserving left-right supersymmetric model

We revisit the Higgs sector of the left-right supersymmetric model. We study the scalar potential in a version of the model in which the minimum is the charge-conserving vacuum state, without R-parity violation or additional nonrenormalizable terms in the Lagrangian. We analyze the dependence of the potential and of the Higgs mass spectrum on the various parameters of the model, pinpointing the most sensitive ones. We also show that the model can predict light neutral flavor-conserving Higgs bosons, while the flavor-violating ones are heavy and within the limits from K{sup 0}-K{sup 0}, D{sup 0}-D{sup 0}, and B{sub d,s}{sup 0}-B{sub d,s}{sup 0} mixings. We study variants of the model in which at least one doubly charged Higgs boson is light and show that the parameter space for such Higgs masses and mixings is very restrictive, thus making the model more predictive.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Counterintuitive electron localisation from density-functional theory with polarisable solvent models

Exploration of the solvated electron phenomena using density-functional theory (DFT) generally results in prediction of a localised electron within an induced solvent cavity. However, it is well known that DFT favours highly delocalised charges, rendering the localisation of a solvated electron unexpected. We explore the origins of this counterintuitive behaviour using a model Kevan-structure system. When a polarisable-continuum solvent model is included, it forces electron localisation by introducing a strong energetic bias that favours integer charges. This results in the formation of a large energetic barrier for charge-hopping and can cause the self-consistent field to become trapped in local minima thus converging to stable solutions that are higher in energy than the ground electronic state. Finally, since the bias towards integer charges is caused by the polarisable continuum, these findings will also apply to other classical polarisation corrections, as in combined quantum mechanics and molecular mechanics (QM/MM) methods. The implications for systems beyond the solvated electron, including cationic DNA bases, are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1988

Comparison of measured C-band scattering coefficients with model predictions as a function of leaf area index and Biomass

The backscattering coefficients for black spruce and aspen at an incidence angle of 50 deg obtained using a helicopter mounted C-band scatterometer are related to leaf area index (LAI) and biomass for several dates while leaves are present. These data are compared with estimates obtained from the Fung disk model for aspen. Implications for spacecraft SAR (e.g., SIR-C) systems and their ability to determine biophysical characteristics of forest canopies are discussed. The precision of SAR data is insufficient to provide consistent tests of the relationship of LAI to the scattering coefficient for single polarizations alone. Backscatter models only provide a simulation of part of the canopy, and more attention needs to be placed on collecting field data which support tests of the microwave scattering models.

Pitts, D. E.↗
DOE OSTI2011

Plasma analogy and non-Abelian statistics for Ising-type quantum Hall states

We study the non-Abelian statistics of quasiparticles in the Ising-type quantum Hall states which are likely candidates to explain the observed Hall conductivity plateaus in the second Landau level, most notably the one at filling fraction {nu}=5/2. We complete the program started in V. Gurarie and C. Nayak, [Nucl. Phys. B 506, 685 (1997)]. and show that the degenerate four-quasihole and six-quasihole wave functions of the Moore-Read Pfaffian state are orthogonal with equal constant norms in the basis given by conformal blocks in a c=1+(1/2) conformal field theory. As a consequence, this proves that the non-Abelian statistics of the excitations in this state are given by the explicit analytic continuation of these wave functions. Our proof is based on a plasma analogy derived from the Coulomb gas construction of Ising model correlation functions involving both order and (at most two) disorder operators. We show how this computation also determines the non-Abelian statistics of collections of more than six quasiholes and give an explicit expression for the corresponding conformal block-derived wave functions for an arbitrary number of quasiholes. Our method also applies to the anti-Pfaffian wave function and to Bonderson-Slingerland hierarchy states constructed over the Moore-Read and anti-Pfaffian states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Assessing the Performance of Exchange‐Correlation Density Functionals in Describing the Iron‐Catalyzed Ammonia Synthesis System

Density functional theory (DFT) has been widely employed for elucidating mechanistic aspects of heterogeneous catalysis. However, the accuracy of DFT calculations relies heavily on selecting an exchange-correlation (XC) functional that correctly describes the electronic structure of materials involved in the reactions. This study assesses the accuracy of several XC density functionals for modeling the iron-catalyzed ammonia synthesis system. In the assessment of functional accuracy, experimental references are compared to DFT-calculated values for the formation energy of gas-phase ammonia and nitrogen, bulk Fe/Fe-nitride (γ′-Fe 4 N) lattice constants and cohesive/formation energies, and nitrogen and ammonia binding energies on Fe(100), Fe(111), Fe(110), and γ′-Fe 4 N(111). It is observed that the experimental value for each of these descriptors is accurately modeled by at least one functional. RPBE alone provides reliable estimates for both the lattice constant and cohesive energy of Fe and γ′-Fe 4 N. Temperature-programmed desorption experiments led to estimates for N and NH 3 adsorption across several Fe-based facets that are best captured by RPBE. These results highlight the importance of choosing an appropriate XC functional that accurately describes experimental systems and offer insights into effectively modeling the interactions between nitrogen and ammonia on Fe-based surfaces.

adsorption↗
NASA NTRS1975

Stochastic simulation of vertically nonhomogeneous gusts

The small-scale horizontal gust structure of detailed wind profiles along the vertical in the first 20 km of the atmosphere is a vertically nonhomogeneous process. A linear stochastic model was developed based on the process covariance function. This model was formulated through the use of a scaling hypothesis which transforms the nonhomogeneous gust process into a nondimensional gust process which is homogeneous in a nondimensional gust height coordinate. The velocity scaling parameter for the gust process is the gust standard deviation, and the length scale used to nondimensionalize the altitude is the vertical space lag associated with the first zero of the gust covariance function. State space theory was used to derive a digital filter from the model, which can be readily used to simulate gusts for space vehicle design applications.

Fichtl, G. H.↗
DOE OSTI2022

Atoms and interatomic bonding synergism inherent in molecular electronic wave functions

The chemical model of matter consists of atoms held together by bonds. The success of this model implies that the physical interactions of the electrons and nuclei in molecules combine into compound interactions that create the bonding. In the quantum mechanical description, the modified atoms in molecules and the bonding synergism are contained in the molecular electronic wave function. So far, only part of this information has been recovered from the wave function. Notably, the atoms have remained unidentified in the wave function. One reason is that conventional energy decomposition analyses formulate separate model wave functions, independent of the actual wave function, to represent “prepared atoms” and preconceived interactions and, then, intuitively catenate the parts. In the present work, the embedded modified atoms and the inherent physical synergisms between them are determined by a unified derivation entirely from the actual molecular valence space wave function. By means of a series of intrinsic orbital and configurational transformations of the wave function, the energy of formation of a molecule is additively resolved in terms of intra-atomic energy changes, interference energies, and quasi-classical, non-classical, and charge-transfer Coulombic interactions. Here, the analysis furnishes an algorithm for the quantitative resolution of the energy of formation, which enables analyses elucidating reaction energies.

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

Density Functional Tight-Binding Models for Band Structures of Transition-Metal Alloys and Surfaces across the d -Block

First-principles electronic structure simulations are an invaluable tool for understanding chemical bonding and reactions. While machine-learning models such as interatomic potentials significantly accelerate the exploration of potential energy surfaces, electronic structure information is generally lost. Particularly in the field of heterogeneous catalysis, simulated electron band structures provide fundamental insights into catalytic reactivity. This ab initio knowledge is preserved in semiempirical methods such as density functional tight binding (DFTB), which extend the accessible computational length and time scales beyond first-principles approaches. In this paper here we present Shell-Optimized Atomic Confinement (SOAC) DFTB electronic-part-only parametrizations for bulk and surface band structures of all d-block transition metals that enable efficient predictions of electronic descriptors for large structures or high-throughput studies on complex systems outside the computational reach of density functional theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

A xenograft model reveals that PU.1 functions as a tumor suppressor for multiple myeloma in vivo

We previously demonstrated that PU.1 expression is down-regulated in the majority of myeloma cell lines and primary myeloma cells from patients. We introduced the tet-off system into the human myeloma cell lines U266 and KMS12PE that conditionally express PU.1 and demonstrated that PU.1 induces cell cycle arrest and apoptosis in myeloma cells in vitro. Here, we established a mouse xenograft model of myeloma using these cell lines to analyze the effects of PU.1 on the phenotype of myeloma cells in vivo. When doxycycline was added to the drinking water of mice engrafted with these myeloma cells, all mice had continuous growth of subcutaneous tumors and could not survived more than 65 days. In contrast, mice that were not exposed to doxycycline did not develop subcutaneous tumors and survived for at least 100 days. We next generated mice engrafted with subcutaneous tumors 5–10 mm in diameter that were induced by exposure to doxycycline. Half of the mice stopped taking doxycycline-containing water, whereas the other half kept taking the water. Although the tumors in the mice taking doxycycline continued to grow, tumor growth in the mice not taking doxycycline was significantly suppressed. The myeloma cells in the tumors of the mice not taking doxycycline expressed PU.1 and TRAIL and many of such cells were apoptotic. Moreover, the expression of a cell proliferation marker Ki67 was significantly decreased in tumors from the mice not taking doxycycline, compared with that of tumors from the mice continuously taking doxycycline. The present data strongly suggest that PU.1 functions as a tumor suppressor of myeloma cells in vivo. - Highlights: • PU.1 suppresses xenograft myeloma cell growth and prolongs survival periods of mice. • PU.1 induces TRAIL expression and apoptosis in myeloma cells in vivo. • PU.1 suppresses Ki67 expression in myeloma cells in vivo. • Up-regulation of PU.1 is a promising strategy for generating anti-myeloma agents.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Informing Robust Functional Relationship Benchmarks: An Evaluation of the Temperature Sensitivity of Ecosystem Respiration Across the Arctic-Boreal Region

During land model development, simulated carbon dynamics are often benchmarked against observational data sets to evaluate model performance. Functional relationship benchmarks are the relationship between a driving variable (e.g., temperature) and a response variable (e.g., ecosystem respiration) and are a promising tool for assessing model performance by evaluating modeled sensitivities to changing environmental conditions. However, observed functional relationships can be influenced by choices made during data collection and throughout the benchmarking process, impacting the inferred skill of land models. To avoid misrepresenting a model's true performance, it is necessary to systematically evaluate best practices when constructing functional relationship benchmarks. We developed a set of guidelines for constructing functional relationship benchmarks, considering the choice of data set, number of daily observations, temporal extent, and temporal resolution across Alaska and Canada over a 20-year period from 2001 to 2020. The temperature sensitivity of ecosystem respiration from observations, evaluated through an apparent Q 10 , is highly variable both spatially and as a result of the data processing approach applied in the benchmark formation. When benchmarking 13 models from the Warming Permafrost Model Intercomparison Project (WrPMIP), the range in inferred model skill is substantially impacted by the choices applied in constructing functional relationship benchmarks. The inferred performance of a given model is most sensitive to the number of daily observations and temporal extent, followed by choice of benchmark data set and temporal averaging. Results from this analysis can guide the development of consistent and robust functional relationships for future model evaluation studies.

Poe, Jeralyn [Northern Arizona University, Flagsta↗
DOE OSTI2015

SIFTER search: a web server for accurate phylogeny-based protein function prediction

We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Towards a NEAMS-based high-fidelity model of the MARVEL reactor

This report outlines the progress of Idaho National Laboratory in developing a high-fidelity and high-resolution model of the Microreactor Applications Research Validation and Evaluation reactor. The model was developed under the Nuclear Energy Advanced Modeling and Simulation microreactor application driver at Idaho National Laboratory. The overarching objective of this activity is the development of a high-fidelity multiphysics MARVEL model using NEAMS tools, and to verify and validate NEAMS tools against MARVEL reference simulation and experimental data, respectively. This is a unique opportunity to conduct multiphysics analysis on a soon-to-be-deployed microreactor. This multiphysics model developed under the NEAMS-funded INL microreactor application driver leverages three single-physics models coupled via the MOOSE’s MultiApp and Transfer systems. The latter systems enable in-memory data transfer between MOOSE-based and MOOSE-wrapped applications. The first single-physics model, that functions as main application, leverages Griffin to model the neutron transport in the core through the discontinuous finite element (DFEM) discrete ordinates solver (SN). Several optimization flags that were developed by the Griffin developer team were beta-tested to enhance the solver’s performance. These include the combined use of using_average_xs and update_averaged_xs_on that enable to avoid expensive on-the-fly cross sections evaluations at each linear iterations in favor of evaluations of the macroscopic cross sections at each Picard iteration. The second single-physics model uses BISON to handle solid heat transfer and asymptotic hydrogen redistribution analysis in the fuel. While the model returns consistent results for the temperature and hydrogen distribution in the fuel, a mismatch was noticed in the calculated temperature in the reflector due to the value of the gap conductance used in our model. Ongoing investigations are being performed to assess the origin of this discrepancy. Finally, the System Analysis Module (SAM) was used to model the flow of the sodium-potassium eutectic in the primary loop. A first verification was also performed showing good agreement in terms of mass flow rate and inlet temperature. All mesh files were generated using the MOOSE Reactor module, removing the need for external meshing tools. Notably, this workscope represents one of the initial applications of the MOOSE Reactor module for modeling highly irregular geometries. The use of the reactor module significantly streamlined the mesh generation process. The full multiphysics mode, that combines all the single physics models, was leveraged to conduct initial steady-state multiphysics simulations to compute power, and temperature distribution in the reactor. Initial testing was performed for transient simulations as well. In this case, the new checkpoint restart capability for eigenvalue calculations was tested showing the capability for streamlined restart of transient calculations. Future work will focus on improving the fidelity of the model by performing comprehensive code-to-code comparisons. For instance, the full-core Griffin neutronics model will be benchmarked against MCNP reference results, that were provided by the MARVEL design team. Additionally, the SAM T/H model will be verified against reference RELAP-5 results for selected accident scenarios. Besides code-to-code verification exercises, the model fidelity will be improved by replacing the single-channel SAM model with a more complex SAM-Pronghorn coupled model, in which the sub-channel capability is deployed to obtain radial temperature resolution in the coolant. This model will be developed in synergy with the NEAMS thermal hydraulics team.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

The E3SM version 1 single-column model

Abstract. The single-column model (SCM) functionality of the Energy Exascale Earth System Model version 1 (E3SMv1) is described in this paper. The E3SM SCM was adopted from the SCM used in the Community Atmosphere Model (CAM) but has evolved significantly since then. We describe changes made to the aerosol specification in the SCM, idealizations, and developments made so that the SCM uses the same dynamical core as the full general circulation model (GCM) component. Based on these changes, we describe and demonstrate the seamless capability to “replay” a GCM column using the SCM. We give an overview of the E3SM case library and briefly describe which cases may serve as useful proxies for replicating and investigate some long-standing biases in the full GCM runs while demonstrating that the E3SM SCM is an efficient tool for both model development and evaluation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Meteor velocity distribution and an optimum monitoring mathematical model

At present, there are a great number of radio meteor, ionosphere and rocket observation data for the altitude range of 80 to 100 km which indicate the existence of large scale circulation systems in the mesopause to low thermosphere range which change regularly with season and latitude. But the existing observation network and observation programs are not optimal for revealing the main factors forming the circulation mode at these altitudes. A generalized optimum monitoring mathematical model is offered for consideration. The model input data are distribution density, response function, individual measurement root mean square uncertainty and detection effectiveness function. The model makes it possible to obtain the observation distribution density, the minimal possible dispersion and optimized system effectiveness.

Volkov, N. G.↗
NASA NTRS1988

Extremely luminous far-infrared colliding galaxies - Computation of colliding-galaxy luminosity function

A computational model used to determine the luminosity function for gaseous galaxies in collision is described. It is based on the assumption of high-velocity encounters of two thin, gas-rich disks having identical radii and thickness, able to approach each other from arbitrary directions, with arbitrary orientations and with arbitrary degree of overlap. The distribution of expected luminosities generated in the dissipation of translational energy is then found to closely fit the observed distribution of luminosities of extremely luminous IRAS galaxies. Bursts of star formation resulting from such collisions would not have the correct luminosity function.

Harwit, Martin↗
NASA NTRS1988

A test of synthetic accretion disk spectra using ultraviolet flux distributions of novalike variables

Ultraviolet (UV) fluxes and other data for a sample of nine novalike cataclysmic variables are assembled from the literature. The UV fluxes and colors are compared to spectra of steady state model accretion disks, constructed using either Planck functions or model stellar atmosphere spectra as elementary radiators. Deficiencies are found with both sets of models. The restriction to steady state radial temperature profiles is relaxed for the 'stellar atmosphere' disks, but these generalized models still fail to account simultaneously for the absolute UV flux and the UV color of the observed spectra. The conclusion is that stellar atmosphere models do not reflect the physics of disks. More appropriate models probably can and definitely should be made.

Wade, Richard A.↗
NASA NTRS1988

Electron-impact excitation of atomic oxygen

A close-coupling approximation is employed to theoretically investigate the excitation of the 3s3S0 and 3p3P states of atomic oxygen for electron impact energies ranging from 13.87-100 eV. The target states included in the expansion of the total wave function are modeled by accurate configuration-interaction wave functions. The results are consistent with recent experimental findings for the dipole-allowed 3P-3s3S0 transition.

Tayal, S. S.↗