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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Sequential geophysical and flow inversion to characterize fracture networks in subsurface systems

Subsurface applications, including geothermal, geological carbon sequestration, and oil and gas, typically involve maximizing either the extraction of energy or the storage of fluids. Fractures form the main pathways for flow in these systems, and locating these fractures is critical for predicting flow. However, fracture characterization is a highly uncertain process, and data from multiple sources, such as flow and geophysical are needed to reduce this uncertainty. We present a nonintrusive, sequential inversion framework for integrating data from geophysical and flow sources to constrain fracture networks in the subsurface. In this framework, we first estimate bounds on the statistics for the fracture orientations using microseismic data. These bounds are estimated through a combination of a focal mechanism (physics-based approach) and clustering analysis (statistical approach) of seismic data. Then, the fracture lengths are constrained using flow data. In conclusion, the efficacy of this inversion is demonstrated through a representative example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Paramagnon dispersion and damping in doped Na x Ca 2 – x CuO 2 Cl 2

Here, using resonant inelastic x-ray scattering, we measure the paramagnon dispersion and damping of undoped, antiferromagnetic Ca 2 CuO 2 Cl 2 as well as doped, superconducting Na x Ca 2–x CuO 2 Cl 2 . Our estimation of the spin-exchange parameter and width of the paramagnon peak at the zone boundary X=(0.5, 0) confirms that no simple relation can be drawn between these parameters and the critical temperature T c . Consistently with other cuprate compounds, we show that upon doping there is a slight softening at (0.25,0) but not at the zone boundary X. In combination with these measurements we perform calculations of the dynamical spin structure factor of the one-band Hubbard model using cluster dynamical mean-field theory. The calculations are in excellent agreement with the experiment in the undoped case, both in terms of energy position and width. While the increase in width is also captured upon doping, the dynamical spin structure factor shows a sizable softening at X, which provides insightful information on the length-scale of the spin fluctuations in doped cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

The temperature and size distribution of large water clusters from a non-equilibrium model

A hybrid Lagrangian-Eulerian approach is used to examine the properties of water clusters formed in neon-water vapor mixtures expanding through microscale conical nozzles. Experimental size distributions were reliably determined by the sodium doping technique in a molecular beam machine. The comparison of computed size distributions and experimental data shows satisfactory agreement, especially for (H{sub 2}O){sub n} clusters with n larger than 50. Thus validated simulations provide size selected cluster temperature profiles in and outside the nozzle. This information is used for an in-depth analysis of the crystallization and water cluster aggregation dynamics of recently reported supersonic jet expansion experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The Installation of Direct Water-Cooling Systems to Reduce Cooling Energy Requirements for High-Performance Computing Centers

A large cluster of High-Performance Computing (HPC) equipment at the Lawrence Livermore National Laboratory in California was retrofitted with an Asetek cooling system. The Asetek system is a hybrid scheme with water-cooled cold plates on high-heat-producing components in the information technology (IT) equipment, and with the remainder of the heat being removed by conventional air-cooling systems. In order to determine energy savings of the Asetek system, data were gathered and analyzed two ways: using top-down statistical models, and bottom-up engineering models. The cluster, “Cabernet”, rejected its heat into a facilities cooling water loop which in turn rejected the heat into the same chilled water system serving the computer-room air handlers (CRAHs) that provided the air-based cooling for the room. Because the “before” and “after” cases both reject their heat into the chilled water system, the only savings is due to reduction in CRAH fan power. The top-down analysis showed a 4% overall energy savings for the data center (power usage effectiveness (PUE) —the ratio of total data center energy to IT energy— dropped from 1.60 to 1.53, lower is better); the bottom-up analysis showed a 3% overall energy savings (PUE from 1.70 to 1.66) and an 11% savings for the Cabernet system by itself (partial PUE of 1.51). Greater savings, on the order of 15-20%, would be possible if the chilled water system was not used for rejecting the heat from the Asetek system. About 37% of the heat from the Cab system was rejected to the cooling water, lower than at other installations.

Earni, Shankar↗
DOE OSTI2025

Reduced-basis method for few-body bound-state emulation

Recent advances in both theoretical and computational methods have enabled large-scale, precision calculations of the properties of atomic nuclei. With the growing complexity of modern nuclear theory, however, also comes the need for novel methods to perform systematic studies and quantify the uncertainties of models when confronted with experimental data. Here, this study presents an application of such an approach, the reduced basis method, to substantially lower computational costs by constructing a significantly smaller Hamiltonian subspace informed by previous solutions. Our method shows comparable efficiency and accuracy to other dimensionality reduction techniques on an artificial three-body bound system while providing a richer representation of physical information in its projection and training subspace. This methodological advancement can be applied in other contexts and has the potential to greatly improve our ability to systematically explore theoretical models and thus enhance our understanding of the fundamental properties of nuclear systems.

cluster models↗
DOE OSTI2014

Characterization of the Praesepe star cluster by photometry and proper motions with 2MASS, PPMXL, and Pan-STARRS

Membership identification is the first step in determining the properties of a star cluster. Low-mass members in particular could be used to trace the dynamical history, such as mass segregation, stellar evaporation, or tidal stripping, of a star cluster in its Galactic environment. We identified member candidates of the intermediate-age Praesepe cluster (M44) with stellar masses ∼0.11-2.4 M {sub ☉}, using Panoramic Survey Telescope And Rapid Response System and Two Micron All Sky Survey photometry, and PPMXL proper motions. Within a sky area of 3° radius, 1040 candidates are identified, of which 96 are new inclusions. Using the same set of selection criteria on field stars, an estimated false positive rate of 16% was determined, suggesting that 872 of the candidates are true members. This most complete and reliable membership list allows us to favor the BT-Settl model over other stellar models. The cluster shows a distinct binary track above the main sequence, with a binary frequency of 20%-40%, and a high occurrence rate of similar mass pairs. The mass function is consistent with that of the disk population but shows a deficit of members below 0.3 solar masses. A clear mass segregation is evidenced, with the lowest-mass members in our sample being evaporated from this disintegrating cluster.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Trends in Siting of Metals in Heterometallic Nd–Yb Metal–Organic Frameworks and Molecular Crystals

Several studies suggest that metal ordering within metal–organic frameworks (MOFs) is important for understanding how MOFs behave in relevant applications; however, these siting trends can be difficult to determine experimentally. To garner insight into the energetic driving forces that may lead to nonrandom ordering within heterometallic MOFs, we employ density functional theory (DFT) calculations on several bimetallic metal–organic crystals composed of Nd and Yb metal atoms. We also investigate the metal siting trends for a newly synthesized MOF. Our DFT-based energy of mixing results suggest that Nd will likely occupy sites with greater access to electronegative atoms and that local homometallic domains within a mixed-metal Nd–Yb system are favored. We also explore the use of less computationally extensive methods such as classical force fields and cluster expansion models to understand their feasibility for large system sizes. Here, this study highlights the impact of metal ordering on the energetic stability of heterometallic MOFs and crystal structures.

energy of mixing↗
DOE OSTI2020

Emergence of quasiparticles in a doped Mott insulator

How a Mott insulator develops into a weakly coupled metal upon doping is a central question to understanding various emergent correlated phenomena. To analyze this evolution and its connection to the high- T c cuprates, we study the single-particle spectrum for the doped Hubbard model using cluster perturbation theory on superclusters. Starting from extremely low doping, we identify a heavily renormalized quasiparticle dispersion that immediately develops across the Fermi level, and a weakening polaronic side band at higher binding energy. The quasiparticle spectral weight roughly grows at twice the rate of doping in the low doping regime, but this rate is halved at optimal doping. In the heavily doped regime, we find both strong electron-hole asymmetry and a persistent presence of Mott spectral features. Finally, we discuss the applicability of the single-band Hubbard model to describe the evolution of nodal spectra measured by angle-resolved photoemission spectroscopy (ARPES) on the single-layer cuprate La 2– x Sr x CuO 4 (0 ≤ x ≤ 0.15). This work benchmarks the predictive power of the Hubbard model for electronic properties of high- T c cuprates.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

THE EXTENDED VIRGO CLUSTER CATALOG

We present a new catalog of galaxies in the wider region of the Virgo cluster, based on the Sloan Digital Sky Survey (SDSS) Data Release 7. The Extended Virgo Cluster Catalog (EVCC) covers an area of 725 deg{sup 2} or 60.1 Mpc{sup 2}. It is 5.2 times larger than the footprint of the classical Virgo Cluster Catalog (VCC) and reaches out to 3.5 times the virial radius of the Virgo cluster. We selected 1324 spectroscopically targeted galaxies with radial velocities less than 3000 km s{sup –1}. In addition, 265 galaxies that have been overlooked in the SDSS spectroscopic survey but have available redshifts in the NASA Extragalactic Database are also included. Our selection process secured a total of 1589 galaxies, 676 of which are not included in the VCC. The certain and possible cluster members are defined by means of redshift comparison with a cluster infall model. We employed two independent and complementary galaxy classification schemes: the traditional morphological classification based on the visual inspection of optical images and a characterization of galaxies from their spectroscopic features. SDSS u, g, r, i, and z passband photometry of all EVCC galaxies was performed using Source Extractor. We compare the EVCC galaxies with the VCC in terms of morphology, spatial distribution, and luminosity function. The EVCC defines a comprehensive galaxy sample covering a wider range in galaxy density that is significantly different from the inner region of the Virgo cluster. It will be the foundation for forthcoming galaxy evolution studies in the extended Virgo cluster region, complementing ongoing and planned Virgo cluster surveys at various wavelengths.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Molecular-Level Insights into Oxygen Reduction Catalysis by Graphite-Conjugated Active Sites

With a combination of experimental and computational investigations, we design a consistent mechanistic model for the oxygen reduction reaction (ORR) at molecularly well-defined graphite-conjugated catalyst ( GCC ) active sites featuring aryl-pyridinium moieties ( N+-GCC ). ORR catalysis at glassy carbon surfaces modified with N+-GCC fragments displays near-first-order dependence in O 2 partial pressure and near-zero-order dependence on electrolyte pH. Tafel analysis suggests an equilibrium one-electron transfer process followed by a rate-limiting chemical step at modest overpotentials that transitions to a rate-limiting electron transfer sequence at higher overpotentials. Finite-cluster computational modeling of the N+-GCC active site reveals preferential O 2 adsorption at electrophilic carbons alpha to the pyridinium moiety. Together, the experimental and computational data indicate that ORR proceeds via a proton-decoupled O 2 activation sequence involving either concerted or stepwise electron transfer and adsorption of O 2 , which is then followed by a series of electron/proton transfer steps to generate water and turn over the catalytic cycle. The introduced mechanistic model serves as a roadmap for the bottom-up synthesis of highly active N-doped carbon ORR catalysts.

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

Do Better Quality Embedding Potentials Accelerate the Convergence of QM/MM Models? The Case of Solvated Acid Clusters

This study examines whether the use of more accurate embedding potentials improves the convergence of quantum mechanics/molecular mechanics (QM/MM) models with respect to the size of the QM region. In conjunction with density functional theory calculations using the ωB97X-D functional, various embedding potentials including the TIP3P water model, the effective fragment potential (EFP), and semi-empirical methods (PM6, PM7, and DFTB) were used to simulate the deprotonation energies of solvated acid clusters. The calculations were performed on solvated neutral (HA) and cationic (HB+) acids clusters containing 160 and 480 water molecules using configurations sampled from molecular dynamics simulations. Consistently, the ωB97X-D/EFP model performed the best when using a minimal QM region size. The performance for the other potentials appears to be highly sensitive to the charge character of the acid/base pair. Neutral acids display the expected trend that semi-empirical methods generally perform better than TIP3P; however, an opposite trend was observed for the cationic acids. Additionally, electronic embedding provided an improvement over mechanical embedding for the cationic systems, but not the neutral acids. For the best performing ωB97X-D/EFP model, a QM region containing about 6% of the total number of solvent molecules is needed to approach within 10 kJ mol−1 of the pure QM result if the QM region was chosen based on the distance from the reaction centre.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Report on fundamental modeling of irradiation-induced swelling and creep in FeCrAl alloys

In order to improve the accident tolerance of light water reactor (LWR) fuel, alternative cladding materials have been proposed to replace zirconium (Zr)-based alloys. Of these materials, there is a particular focus on iron-chromium-aluminum (FeCrAl) alloys due to much slower oxidation kinetics in high-temperature steam than Zr-alloys. This should decrease the energy release due to oxidation and allow the cladding to remain integral longer in the presence of high temperature steam, making accident mitigation more likely. As a continuation of the development for these alloys, the material response must be demonstrated to provide suitable radiation stability, in order to ensure that there will not be significant dimensional changes (e.g., swelling), as well as quantifying the radiation hardening and radiation creep behavior. In this report, we describe the use of cluster dynamics modeling to evaluate the defect physics and damage accumulation behavior of FeCrAl alloys subjected to neutron irradiation, with a particular focus on irradiation-induced swelling and defect fluxes to dislocations that are required to model irradiation creep behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Spatial effects on hybrid electric vehicle adoption

This paper examines spatial effects on hybrid-electric vehicle (HEV) adoption. This is in contrast to most existing analyses, which concentrate on analyzing socioeconomic factors and demographics. This paper uses a general spatial model to estimate the strength of ‘neighbor effects’ on HEV adoption—namely that each consumer’s HEV-adoption decision can be influenced by the HEV-adoption decisions of geographic neighbors. We use detailed census tract-level demographic data from the 2010 United States Census and the 2012 American Community Survey and vehicle registration data collected by the Ohio Bureau of Motor Vehicles. We find that HEV adoption exhibits significant spatial effects. We further conduct a time-series analysis and show that historical HEV adoption has a spatial effect on future adoption. Lastly, these results suggest that HEVs may appear in more dense clusters than models that do not consider spatial effects predict.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Evaluating Energy Efficiency Opportunities from Connected and Automated Vehicle Deployments Coupled with Shared Mobility in California

Connected and Automated Vehicles (CAVs) can be considered to be a disruptive transportation technology, with the potential to significantly improve overall transportation system efficiency; however, CAVs may increase induce vehicle miles traveled (VMT) and bring on greater energy consumption. Further, shared mobility is another disruptive transportation event that is reshaping our travel patterns. The primary goal of this project was to extensively collect data from vehicles and associated infrastructure equipped with CAV technologies from both real-world experiments and simulation studies mainly deployed in California, and develop a comprehensive framework for evaluating energy efficiency opportunities from large-scale (e.g., statewide) introduction of CAVs and a wide deployment of shared mobility systems in a variety of scenarios. To quantify the combined impact of CAV and shared mobility on travel behavior, traffic performance, and energy efficiency, a unique mesoscopic simulation-based model was developed for mobility and energy efficiency evaluation considering these disruptive transportation technologies. As a complement to existing studies on nationwide evaluation of CAVs’ energy impacts, this project was focused on data collection efforts and CAV applications under congested traffic environments that are frequently experienced on a massive scale across the major metropolitan areas in California. Extensive real-world data collection supplemented with simulation studies were conducted to cover a variety of CAV and shared mobility scenarios, particularly on scenarios less-explored in the existing research. Another key component of this project was to consider the interaction between different CAV technologies and shared mobility models, and the compound effect on energy efficiency. A comprehensive modeling suite was developed to quantify the impact of new mobility technologies on travel behavior and traffic performance. The developed modeling framework includes an energy intensity module, mode choice module and activity generation module that are integrated into an agent-based BEAM simulation platform to perform impact analysis based on a variety of scenarios. In addition, the RouteE model has been upgraded to incorporate the impact of CAVs on traffic flow, VMT and energy intensity, using micro-simulation data collected from both freeways and urban arterials. A novel fundamental influencing factor (FIF) mode choice model was developed to link CAV and shared mobility components with travel behaviors, and adapted into the BEAM-centered model framework. A statewide energy inventory was constructed under various CAV technology deployment scenarios by incorporating datasets and models for predicting vehicle market share and vehicle usage, which are tightly associated with the penetration of shared mobility systems. Based applying this modeling suite to a calibrated network in Riverside California, it was found that cooperative automated driving in general will improve mobility, but automated vehicles, even when deployed in a shared autonomous fleet, will likely bring an increase of VMT (up to 36%) due to mode shifts and deadheading. Ride-hailing vehicles typically have better energy efficiency and a higher share of electric vehicles, which helps offset the negative impact from VMT increases when estimating the system-level energy consumption. In general, simulation results show a 6% increase in energy consumption for the scenarios with an increasing shift to ride-hailing modes. The statewide analysis based on the National Household Travel Survey (NHTS) sample data is consistent with the findings from the Riverside network and validate the developed clustering-prediction modeling methodology. The outcomes from this project will help close the knowledge gap on recognizing the potential performance and energy impacts of a broad deployment of CAV and shared mobility technologies across a wide range of roadway infrastructure with varying levels of congestion. Results from this project: 1) will support policymakers in steering CAV development and deployment towards an energy favorable direction; 2) reduce uncertainties in estimating energy saving opportunities from new mobility technologies and services; 3) increase the confidence of CAV technology investors both on the infrastructure side (i.e., transportation agencies) and on the vehicle side (i.e., OEMs); and 4) expedite the deployment of energy-efficient CAV and shared mobility applications.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Systematic study of the validity of the eikonal model including uncertainties

Nuclear reactions at intermediate beam energies are often interpreted using the eikonal model. In the analysis of complex reaction probes, where few-body reaction methods are needed, the eikonal method may be used as an efficient way for describing the fragment-target reaction process. In this work, we perform a systematic study to test the validity of the eikonal approximation for nucleon-nucleus reactions. We also quantify uncertainties due to the nucleon optical potential on reaction observables. We inspect the validity of the eikonal model and its semiclassical correction by comparing it to exact solutions (obtained from solving the optical-model equation with a finite-differences method) for a wide range of reactions. We also study the effect of relativistic corrections, both kinematic and dynamic, by effectively incorporating the relativistic effects at intermediate energies. The uncertainties from a Bayesian global optical potential (KDUQ) are propagated to the observables of interest. Our study includes neutron and proton reactions on 27 Al , 40 Ca , 90 Zr , and 208 Pb , for a wide range of energies 𝐸 lab = 0–400 MeV. We calculate neutron-total cross sections (elastic and reactions) as well as proton-absorption cross sections as a function of beam energy, using the eikonal model, the eikonal model with a semiclassical correction, and the exact solution. Here, we also compute angular distributions for the methods above. Our results show that for the proton-absorption cross section, the eikonal model can be used down to around 60 MeV and the semiclassical correction extends its use to 30 MeV. However, the validity of the eikonal model for the neutron-total cross section only goes down to ≈120 MeV, a range extended to ≈ 50 MeV when using the semiclassical correction. We find the semiclassical correction to the eikonal model to be less effective in describing the angular distributions. The 1⁢𝜎 uncertainty intervals on the observables we studied is less than 5% for most of the energies considered, but increases rapidly for higher energies, namely energies outside the range of KDUQ (𝐸 lab > 200MeV).

Cluster models↗
DOE OSTI2022

Ab Initio Prediction of the 4 $\mathrm{H}$e($d, γ$) 6 $\mathrm{L}$i Big Bang Radiative Capture

We report the rate at which helium ( 4 He ) and deuterium (d) fuse together to produce lithium-6 ( 6 Li) and a γ ray, 4 $\mathrm{H}$e($d, γ$) 6 $\mathrm{L}$i, is a critical puzzle piece in resolving the discrepancy between big bang predictions and astronomical observations for the primordial abundance of 6 Li . The accurate determination of this radiative capture rate requires the quantitative and predictive description of the fusion probability across the big bang energy window (30 keV ≲ E ≲ 400 keV), where measurements are hindered by low counting rates. We present first-principle (or, ab initio) predictions of the 4 $\mathrm{H}$e($d, γ$) 6 $\mathrm{L}$i astrophysical S factor using validated nucleon-nucleon and three-nucleon interactions derived within the framework of chiral effective field theory. By employing the ab initio no-core shell model with continuum to describe 4 He-d scattering dynamics and bound 6 Li product on an equal footing, we accurately and consistently determine the contributions of the main electromagnetic transitions driving the radiative capture process. Our results reveal an enhancement of the capture probability below 100 keV owing to previously neglected magnetic dipole (M1) transitions and reduce by an average factor of 7 the uncertainty of the thermonuclear capture rate between 0.002 and 2 GK.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

LICK INDICES AND SPECTRAL ENERGY DISTRIBUTION ANALYSIS BASED ON AN M31 STAR CLUSTER SAMPLE: COMPARISONS OF METHODS AND MODELS

Application of fitting techniques to obtain physical parameters—such as ages, metallicities, and α-element to iron ratios—of stellar populations is an important approach to understanding the nature of both galaxies and globular clusters (GCs). In fact, fitting methods based on different underlying models may yield different results and with varying precision. In this paper, we have selected 22 confirmed M31 GCs for which we do not have access to previously known spectroscopic metallicities. Most are located at approximately one degree (in projection) from the galactic center. We performed spectroscopic observations with the 6.5 m MMT telescope, equipped with its Red Channel Spectrograph. Lick/IDS absorption-line indices, radial velocities, ages, and metallicities were derived based on the EZ-Ages stellar population parameter calculator. We also applied full spectral fitting with the ULySS code to constrain the parameters of our sample star clusters. In addition, we performed χ{sub min}{sup 2} fitting of the clusters’ Lick/IDS indices with different models, including the Bruzual and Charlot models (adopting Chabrier or Salpeter stellar initial mass functions and 1994 or 2000 Padova stellar evolutionary tracks), the galev, and the Thomas et al. models. For comparison, we collected their UVBRIJK photometry from the Revised Bologna Catalogue (v.5) to obtain and fit the GCs’ spectral energy distributions (SEDs). Finally, we performed fits using a combination of Lick/IDS indices and SEDs. The latter results are more reliable and the associated error bars become significantly smaller than those resulting from either our Lick/IDS indices-only or our SED-only fits.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1990

Is the Coma cluster binary dominated?

It is investigated whether the model of an expanding cluster dominated by a massive binary galaxy, first suggested by Valtonen and Byrd (1979), is consistent with optical data on the surface density and velocity dispersion of the Coma cluster. The evolution of this model is simulated for a wide variety of initial conditions. It is found that galaxy counts in the model can be made to agree with observation, but that the observed velocity dispersion profile cannot be reproduced. A number of other arguments suggest that the central galaxies in Coma cannot be as massive as required by the model. This model is not a viable representation of the Coma cluster.

The, Lih Sin↗