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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

BASS. XXXVI. Constraining the Local Supermassive Black Hole–Halo Connection with BASS DR2 AGNs

We investigate the connection between supermassive black holes (SMBHs) and their host dark matter halos in the local universe using the clustering statistics and luminosity function of active galactic nuclei (AGNs) from the Swift/BAT AGN Spectroscopic Survey (BASS DR2). By forward-modeling AGN activity into snapshot halo catalogs from N -body simulations, we test a scenario in which SMBH mass correlates with dark matter (sub)halo mass for fixed stellar mass. We compare this to a model absent of this correlation, where stellar mass alone determines the SMBH mass. We find that while both simple models are able to largely reproduce the abundance and overall clustering of AGNs, the model in which black hole mass is tightly correlated with halo mass is preferred by the data by 1.8 σ . When including an independent measurement on the black hole mass–halo mass correlation, this model is preferred by 4.6 σ . We show that the clustering trends with black hole mass can further break the degeneracies between the two scenarios and that our preferred model reproduces the measured clustering differences on one-halo scales between large and small black hole masses. These results indicate that the halo binding energy is fundamentally connected to the growth of SMBHs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Paradeisos: A perfect hashing algorithm for many-body eigenvalue problems

Here, we describe an essentially perfect hashing algorithm for calculating the position of an element in an ordered list, appropriate for the construction and manipulation of many-body Hamiltonian, sparse matrices. Each element of the list corresponds to an integer value whose binary representation reflects the occupation of single-particle basis states for each element in the many-body Hilbert space. The algorithm replaces conventional methods, such as binary search, for locating the elements of the ordered list, eliminating the need to store the integer representation for each element, without increasing the computational complexity. Combined with the “checkerboard” decomposition of the Hamiltonian matrix for distribution over parallel computing environments, this leads to a substantial savings in aggregate memory. While the algorithm can be applied broadly to many-body, correlated problems, we demonstrate its utility in reducing total memory consumption for a series of fermionic single-band Hubbard model calculations on small clusters with progressively larger Hilbert space dimension.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

The Development of Vocational Vehicle Drive Cycles and Segmentation

Under a collaborative interagency agreement between the U.S. Environmental Protection Agency and the U.S Department of Energy (DOE), the National Renewable Energy Laboratory (NREL) performed a series of in-depth analyses to characterize the on-road driving behavior including distributions of vehicle speed, idle time, accelerations and decelerations, and other driving metrics of medium- and heavy-duty vocational vehicles operating within the United States. As part of this effort, NREL researchers segmented U.S. medium- and heavy-duty vocational vehicle driving characteristics into three distinct operating groups or clusters using real world drive cycle data collected at 1 Hz and stored in NREL's Fleet DNA database. The Fleet DNA database contains millions of miles of historical real-world drive cycle data captured from medium- and heavy vehicles operating across the United States. The data encompass data from existing DOE activities as well as contributions from valued industry stakeholder participants. For this project, data captured from 913 unique vehicles comprising 16,250 days of operation were drawn from the Fleet DNA database and examined. The Fleet DNA data used as a source for this analysis has been collected from a total of 30 unique fleets/data providers operating across 22 unique geographic locations spread across the United States. This includes locations with topology ranging from the foothills of Denver, Colorado, to the flats of Miami, Florida. The range of fleets, geographic locations, and total number of vehicles analyzed ensures results that include the influence of these factors. While no analysis will be perfect without unlimited resources and data, it is the researchers understanding that the Fleet DNA database is the largest and most thorough publicly accessible vocational vehicle usage database currently in operation. This report includes an introduction to the Fleet DNA database and the data contained within, a presentation of the results of the statistical analysis performed by NREL, review of the logistic model developed to predict cluster membership, and a discussion and detailed summary of the development of the vocational drive cycle weights and representative transient drive cycles for testing and simulation. Additional discussion of known limitations and potential future work are also included in the report content.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Modeling temporal and hormonal regulation of plant transcriptional response to wounding

Plants respond to wounding stress by changing gene expression patterns and inducing the production of hormones including jasmonic acid. This wounding transcriptional response activates specialized metabolism pathways such as the glucosinolate pathways in Arabidopsis thaliana. While the regulatory factors and sequences controlling a subset of wound-response genes are known, it remains unclear how wound response is regulated globally. Here, we how these responses are regulated by incorporating putative cis-regulatory elements, known transcription factor binding sites, in vitro DNA affinity purification sequencing, and DNase I hypersensitive sites to predict genes with different wound-response patterns using machine learning. We observed that regulatory sites and regions of open chromatin differed between genes upregulated at early and late wounding time-points as well as between genes induced by jasmonic acid and those not induced. Expanding on what we currently know, we identified cis-elements that improved model predictions of expression clusters over known binding sites. Using a combination of genome editing, in vitro DNA-binding assays, and transient expression assays using native and mutated cis-regulatory elements, we experimentally validated four of the predicted elements, three of which were not previously known to function in wound-response regulation. Our study provides a global model predictive of wound response and identifies new regulatory sequences important for wounding without requiring prior knowledge of the transcriptional regulators.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

A two-phase substrate model for enzymatic hydrolysis of lignocellulose: application to batch and continuous reactors

Abstract Background Enzymatic hydrolysis continues to have a significant projected production cost for the biological conversion of biomass to fuels and chemicals, motivating research into improved enzyme and reactor technologies in order to reduce enzyme usage and equipment costs. However, technology development is stymied by a lack of accurate and computationally accessible enzymatic-hydrolysis reaction models. Enzymatic deconstruction of cellulosic materials is an exceedingly complex physico-chemical process. Models which elucidate specific mechanisms of deconstruction are often too computationally intensive to be accessible in process or multi-physics simulations, and empirical models are often too inflexible to be effectively applied outside of their batch contexts. In this paper, we employ a phenomenological modeling approach to represent rate slowdown due to substrate structure (implemented as two substrate phases) and feedback inhibition, and apply the model to a continuous reactor system. Results A phenomenological model was developed in order to predict glucose and solids concentrations in batch and continuous enzymatic-hydrolysis reactors from which liquor is continuously removed by ultrafiltration. A series of batch experiments were performed, varying initial conditions (solids, enzyme, and sugar concentrations), and best-fit model parameters were determined using constrained nonlinear least-squares methods. The model achieved a good fit for overall sugar yield and insoluble solids concentration, as well as for the reduced rate of sugar production over time. Additionally, without refitting model coefficients, good quantitative agreement was observed between results from continuous enzymatic-hydrolysis experiments and model predictions. Finally, the sensitivity of the model to its parameters is explored and discussed. Conclusions Although the phenomena represented by the model correspond to behaviors that emerge from clusters of mechanisms, and hence a set of model coefficients are unique to the substrate and the enzyme system, the model is efficient to solve and may be applied to novel reactor schema and implemented in computational fluid dynamics (CFD) simulations. Hence, this modeling approach finds the right balance between model complexity and computational efficiency. These capabilities have broad application to reactor design, scale-up, and process optimization.

09 BIOMASS FUELS↗
DOE OSTI2016

A giant Lyα nebula in the core of an x-ray cluster at z = 1.99: implications for early energy injection

We present the discovery of a giant ≳100 kpc Lyα nebula detected in the core of the X-ray emitting cluster CL J1449+0856 at z = 1.99 through Keck/LRIS narrow-band imaging. This detection extends the known relation between Lyα nebulae and overdense regions of the universe to the dense core of a 5–7 × 10{sup 13} M {sub ⊙} cluster. The most plausible candidates to power the nebula are two Chandra-detected AGN host cluster members, while cooling from the X-ray phase and cosmological cold flows are disfavored primarily because of the high Lyα to X-ray luminosity ratio (L{sub Lyα}/L{sub X}≈0.3, ≳10–1000 times higher than in local cool-core clusters) and by current modeling. Given the physical conditions of the Lyα-emitting gas and the possible interplay with the X-ray phase, we argue that the Lyα nebula would be short-lived (≲10 Myr) if not continuously replenished with cold gas at a rate of ≳1000 M {sub ⊙} yr{sup −1}. We investigate the possibility that cluster galaxies supply the required gas through outflows and we show that their total mass outflow rate matches the replenishment necessary to sustain the nebula. This scenario directly implies the extraction of energy from galaxies and its deposition in the surrounding intracluster medium (ICM), as required to explain the thermodynamic properties of local clusters. We estimate an energy injection of the order of ≈2 keV per particle in the ICM over a 2 Gyr interval. In our baseline calculation, AGNs provide up to 85% of the injected energy and two-thirds of the mass, while the rest is supplied by supernovae-driven winds.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1985

Calculation of flow about posts and powerhead model

A three dimensional analysis of the non-uniform flow around the liquid oxygen (LOX) posts in the Space Shuttle Main Engine (SSME) powerhead was performed to determine possible factors contributing to the failure of the posts. Also performed was three dimensional numerical fluid flow analysis of the high pressure fuel turbopump (HPFTP) exhaust system, consisting of the turnaround duct (TAD), two-duct hot gas manifold (HGM), and the Version B transfer ducts. The analysis was conducted in the following manner: (1) modeling the flow around a single and small clusters (2 to 10) of posts; (2) modeling the velocity field in the cross plane; and (3) modeling the entire flow region with a three dimensional network type model. Shear stress functions which will permit viscous analysis without requiring excessive numbers of computational grid points were developed. These wall functions, laminar and turbulent, have been compared to standard Blasius solutions and are directly applicable to the cylinder in cross flow class of problems to which the LOX post problem belongs.

Anderson, P. G.↗
NASA NTRS1986

Ultraviolet extinction toward five open clusters, and the accuracy of IUE extinction measurements

The UV extinction curves of 33 main-sequence B stars in five open clusters are presented and analyzed. An analytic fitting function is introduced which represents the observed curves and codifies the structure of the 2175 A extinction bump. A set of extinction parameters are also defined which describe the shape of the far-UV extinction. These data are first used to determine whether the extinction toward any of the clusters is uniform, i.e., whether it can be represented by a single curve for the cluster. This is accomplished by comparing the observed scatter of the far-UV extinction measurements toward a given cluster with that predicted by an error model. The extinction toward four of the five clusters is found to be uniform. The extinction data for those clusters with uniform extinction are then used to determine the observational uncertainties in other extinction parameters for which a priori error estimates cannot be made. With one exception, all of the parameters which describe the shapes of UV extinction curves differ significantly from cluster to cluster. The exception is the central position of the UV extinction bump, which has the same value for all of the cluster extinction curves. Applications and interpretation of the results are given elsewhere.

Massa, D.↗
NASA NTRS1990

Recognition and characterization of hierarchical interstellar structure. I - Correlation function

The problem of the quantitative description of multiscale structure in interstellar cloud complexes and gravitational collapse calculations is considered, emphasizing the recognition and characterization of hierarchical fragmentation structure. The response of the two-point correlation function to a variety of analytical models for density structure is discussed for simple clustering of pointlike clouds to more complex models involving clouds with a distribution of sizes and densities and hierarchical substructure. By expressing the density distribution as the superposition of individual clouds, it is shown that the correlation function generates two types of terms: those involving each cloud's density convolved with itself and those involving pairs of different clouds. Major distortion of the correlation function are introduced by the presence of any image features with size scales a significant fraction of the image size.

Houlahan, Padraig↗
DOE OSTI2016

Enabling parallel simulation of large-scale HPC network systems

Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks used in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Two-particle correlations in a dynamic cluster approximation with continuous momentum dependence: Superconductivity in the two-dimensional Hubbard model

The DCA + algorithm was recently introduced by Stear, Maier, and Schulthess [Phys. Rev. B 88, 115101 (2013), 10.1103/PhysRevB.88.115101] to extend the dynamic cluster approximation (DCA) with a continuous lattice self-energy in order to achieve better convergence with cluster size. In this work, we extend the DCA + algorithm to the calculation of two-particle correlation functions by introducing irreducible vertex functions with continuous momentum dependence consistent with the DCA + self-energy. This enables a significantly more controlled and reliable study of phase transitions than with the DCA. We test the new method by calculating the superconducting transition temperature $T_c$ in the attractive Hubbard model and show that it reproduces previous determinantal quantum Monte Carlo results. We then calculate $T_c$ in the doped repulsive Hubbard model, for which previous DCA calculations could only access the weak-coupling ($\textit{U}$ =4$\textit{t}$) regime for large clusters. Here, we show that the new algorithm provides access to much larger clusters and delivers asymptotically converged results for $T_c$ for both the weak ($\textit{U}$ =4$\textit{t}$) and intermediate ($\textit{U}$ =7$\textit{t}$) coupling regimes, and thereby enables the accurate determination of the exact infinite cluster size result.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1989

Tidal disruption of open clusters in their parent molecular clouds

A simple model of tidal encounters has been applied to the problem of an open cluster in a clumpy molecular cloud. The parameters of the clumps are taken from the Blitz, Stark, and Long (1988) catalog of clumps in the Rosette molecular cloud. Encounters are modeled as impulsive, rectilinear collisions between Plummer spheres, but the tidal approximation is not invoked. Mass and binding energy changes during an encounter are computed by considering the velocity impulses given to individual stars in a random realization of a Plummer sphere. Mean rates of mass and binding energy loss are then computed by integrating over many encounters. Self-similar evolutionary calculations using these rates indicate that the disruption process is most sensitive to the cluster radius and relatively insensitive to cluster mass. The calculations indicate that clusters which are born in a cloud similar to the Rosette with a cluster radius greater than about 2.5 pc will not survive long enough to leave the cloud. The majority of clusters, however, have smaller radii and will survive the passage through their parent cloud.

Long, Kevin↗
DOE OSTI2022

Uptake of N 2 O 5 by aqueous aerosol unveiled using chemically accurate many-body potentials

The reactive uptake of N 2 O 5 to aqueous aerosol is a major loss channel for nitrogen oxides in the troposphere. Despite its importance, a quantitative picture of the uptake mechanism is missing. Here we use molecular dynamics simulations with a data-driven many-body model of coupled-cluster accuracy to quantify thermodynamics and kinetics of solvation and adsorption of N 2 O 5 in water. The free energy profile highlights that N 2 O 5 is selectively adsorbed to the liquid–vapor interface and weakly solvated. Accommodation into bulk water occurs slowly, competing with evaporation upon adsorption from gas phase. Leveraging the quantitative accuracy of the model, we parameterize and solve a reaction–diffusion equation to determine hydrolysis rates consistent with experimental observations. We find a short reaction–diffusion length, indicating that the uptake is dominated by interfacial features. The parameters deduced here, including solubility, accommodation coefficient, and hydrolysis rate, afford a foundation for which to consider the reactive loss of N 2 O 5 in more complex solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Proton–Electron Conductivity in Thin Films of a Cobalt–Oxygen Evolving Catalyst

In this study, the conductivity of cobalt oxygen evolving catalysts (Co-OEC) thin film are examined for four variants differing in phosphate and borate anion compositions and pH. The effects of these parameters on the Co-OEC activity is explored by (a) examination of the intermediate range structural order within films through high energy X-ray scattering and pair distribution function analysis, and (b) direct measurement of film conductivity, which has been measured with an interdigitated array microelectrode. We find that the nature of the anion is a critical determinant of the size of cobaltate clusters comprising the Co-OEC thin films which in turn is a critical determinant of film conductivity. Improved conductivity of the Co-OEC films with the size of the metallate clusters is consistent with a model for electron conduction that arises from the hopping of hole equivalents delocalized over metallate clusters. Lastly, the hole hopping is fast relative to the ratedetermining step of OER, which may be become limited by proton transport within the films

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Probabilistic Model for Global EMIC Wave Activity Using Van Allen Probes Observations

Electromagnetic ion cyclotron (EMIC) waves play a key role in radiation belt dynamics through resonant interactions. However, their low occurrence probability, high variability, and spatial intermittency pose challenges for accurate modeling. In this study, we present a machine learning (ML)-based global EMIC wave model built on the entire data set from the Van Allen Probes mission. To capture the distinct statistical characteristics of wave occurrence and amplitude, the model is separated into two modules: an occurrence model trained using ML techniques, and a wave amplitude model sampled from observed probability distributions. The input parameters are limited to real-time or predictable variables to ensure practical applicability. Our model shows strong performance across the entire test set and demonstrates improved predictive capability over a baseline random occurrence model, particularly during quiet geomagnetic conditions. Evaluation during both quiet and active periods confirms the model's ability to represent the clustered and intermittent nature of EMIC wave activity. Furthermore, the model provides global estimates of wave power, enabling integration with radiation belt electron data and showing signatures consistent with wave-induced scattering. We found a good correlation between the global wave activity from the model and relativistic electron observation by Van Allen Probes, regardless of the availability of in situ wave observations. The modular structure of the model also allows for straightforward expansion for additional wave properties, such as wave frequency, which can be modeled independently. This flexible, event-sensitive approach offers a promising framework for data-driven radiation belt simulations and space weather applications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Measurement of high-dynamic range x-ray Thomson scattering spectra for the characterization of nano-plasmas at LCLS

Atomic clusters can serve as ideal model systems for exploring ultrafast (∼100 fs) laser-driven ionization dynamics of dense matter on the nanometer scale. Resonant absorption of optical laser pulses enables heating to temperatures on the order of 1 keV at near solid density conditions. To date, direct probing of transient states of such nano-plasmas was limited to coherent x-ray imaging. Here we present the first measurement of spectrally resolved incoherent x-ray scattering from clusters, enabling measurements of transient temperature, densities, and ionization. Single shot x-ray Thomson scattering signals were recorded at 120 Hz using a crystal spectrometer in combination with a single-photon counting and energy-dispersive pnCCD. A precise pump laser collimation scheme enabled recording near background-free scattering spectra from Ar clusters with an unprecedented dynamic range of more than 3 orders of magnitude. Such measurements are important for understanding collective effects in laser-matter interactions on femtosecond time scales, opening new routes for the development of schemes for their ultrafast control.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

32.8-nm X-ray laser produced in a krypton cluster jet

We have interpreted the well-known experimental quantum yield data for a 32.8-nm X-ray laser operating at the 3d{sup 9}4d (J = 0) – 3d{sup 9}4p (J = 1) transition of Kr{sup 8+} with the use of gaseous krypton or a krypton cluster jet. Proceeding from our model we propose a novel scheme for the 32.8-nm laser produced in a krypton cluster jet. The quantum yield is shown to saturate for a plasma length of ∼300 μm, a krypton ion density n{sub Kr} ∼ (4 – 9) × 10{sup 19} cm{sup -3}, and an electron temperature Te ∼ 5000 eV. In this case, the energy conversion coefficient amounts to ∼5 × 10{sup -3} of the pump pulse energy. We propose the experimental setup for producing a highefficiency subpicosecond X-ray laser in a krypton cluster jet. (lasers)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗