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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Secondary structure of rat and human amylin across force fields

The aggregation of human amylin has been strongly implicated in the progression of Type II diabetes. This 37-residue peptide forms a variety of secondary structures, including random coils, α-helices, and β-hairpins. The balance between these structures depends on the chemical environment, making amylin an ideal candidate to examine inherent biases in force fields. Rat amylin differs from human amylin by only 6 residues; however, it does not form fibrils. Therefore it provides a useful complement to human amylin in studies of the key events along the aggregation pathway. In this work, the free energy of rat and human amylin was determined as a function of α-helix and β-hairpin content for the Gromos96 53a6, OPLS-AA/L, CHARMM22/CMAP, CHARMM22*, Amberff99sb*-ILDN, and Amberff03w force fields using advanced sampling techniques, specifically bias exchange metadynamics. This work represents a first systematic attempt to evaluate the conformations and the corresponding free energy of a large, clinically relevant disordered peptide in solution across force fields. The NMR chemical shifts of rIAPP were calculated for each of the force fields using their respective free energy maps, allowing us to quantitatively assess their predictions. We show that the predicted distribution of secondary structures is sensitive to the choice of force-field: Gromos53a6 is biased towards β-hairpins, while CHARMM22/CMAP predicts structures that are overly α-helical. OPLS-AA/L favors disordered structures. Amberff99sb*-ILDN, AmberFF03w and CHARMM22* provide the balance between secondary structures that is most consistent with available experimental data. In contrast to previous reports, our findings suggest that the equilibrium conformations of human and rat amylin are remarkably similar, but that subtle differences arise in transient alpha-helical and beta-strand containing structures that the human peptide can more readily adopt. We hypothesize that these transient states enable dynamic pathways that facilitate the formation of aggregates and, eventually, amyloid fibrils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

STELLAR POPULATION SYNTHESIS BASED MODELING OF THE MILKY WAY USING ASTEROSEISMOLOGY OF 13,000 KEPLER RED GIANTS

With current space-based missions it is now possible to obtain age-sensitive asteroseismic information for tens of thousands of red giants. This provides a promising opportunity to study the Galactic structure and evolution. We use asteroseismic data of red giants, observed by Kepler, to test the current theoretical framework of modeling the Galaxy based on population synthesis modeling and the use of asteroseismic scaling relations for giants. We use the open source code Galaxia to model the Milky Way and find the distribution of the masses predicted by Galaxia to be systematically offset with respect to the seismically inferred observed masses. The Galactic model overestimates the number of low-mass stars, and these stars are predominantly old and of low metallicity. Using corrections to the Δν scaling relation suggested by stellar models significantly reduces the disagreement between predicted and observed masses. For a few cases where non-seismic mass estimates are available, the corrections to Δν also improve the agreement between seismic and non-seismic mass estimates. The disagreement between predictions of the Galactic model and the observations is most pronounced for stars with [Fe/H]<−0.5 and [Fe/H]>0 or for T{sub eff}>4700 K. Altering the star formation rate in order to suppress stars older than 10 Gyr improves the agreement for mass but leads to inconsistent color distributions. We also tested the predictions of the TRILEGAL Galactic model. However, unlike Galaxia, it had difficulties in reproducing the photometric properties of the Kepler Input Catalog because it overestimates the number of blue stars. We conclude that either the scaling relations and/or the Galactic models need to be revised to reconcile predictions of theory with asteroseismic observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Nucleon Structure from Lattice QCD Calculations

Parton distribution and correlation functions describe the relation between a hadron and the quarks and gluons (or collectively, the partons) within it, and carry rich information on hadron’s partonic structure that cannot be calculated by QCD perturbation theory. In this talk, I will review what lattice QCD can and cannot do for calculating the parton distribution and correlation functions, and the new ideas and efforts around the world to explore nucleon structure from lattice QCD calculations by combining the strength of both lattice QCD and perturbative QCD in such a way that is complementary to our on-going effort to extract these fundamental functions from experimental data.

Qiu, Jian-Wei↗
DOE OSTI2018

Time-of-flight neutron total scattering with applied electric fields: Ex situ and in situ studies of ferroelectric materials

Characterizing the structural response of functional materials (e.g., piezoelectrics and ferroelectrics) to electric fields is key for the creation of structure-property relationships. Here in this paper, we present a new sample environment and data reduction routines which allow the measurement of time-of-flight neutron total scattering during the in situ or ex situ application of high voltage (<10 kV) to a sample. Instead of utilizing the entire detector space of the diffractometer, only selected regions of detector pixels with scattering at the desired angle to the sample electric field are interrogated, which allows the generation of orientation-dependent reciprocal space patterns and real-space pair distribution functions (PDFs). We demonstrate the method using the relaxor ferroelectric Na 1/2 Bi 1/2 TiO 3 and observe lattice expansion parallel and contraction perpendicular to the electric field for both in situ or ex situ experiments, revealing the irreversible nature of the local scale structural changes to this composition. Additionally, changes in the distributions of nearest neighbor metal-oxygen bond lengths are observed, which have been difficult to observe in previously measured analogous orientation-dependent X-ray PDFs. Lastly, considerations related to sample positioning and background subtraction are discussed, and future research directions are suggested.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Level structure of {sup 164}Dy from the (n, n′γ) reaction

By employing a beam of reactor fast neutrons, gamma-ray spectra and angular distributions of gamma rays with respect to the neutron-beam axis were measured in the reaction {sup 164}Dy(n, n′γ). The scheme of levels and gamma transitions in {sup 164}Dy was composed on the basis of data published earlier and new levels, rotational bands, gamma transitions, and multipole-mixing parameters. It is concluded that the scheme of J = 0–4 levels is complete up to the excitation energy of 1.95 MeV. The commonly accepted rule in constructing K{sub n}{sup π} = 0{sub 2}{sup +} and 1{sub 1}{sup +} rotational bands is found to be violated. The nature of the 2{sup +} level at the energy of 1796.68 keV is discussed.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

G-Mapper: Learning a Cover in the Mapper Construction

The Mapper algorithm is a visualization technique in topological data analysis (TDA) that outputs a graph reflecting the structure of a given dataset. However, the Mapper algorithm requires tuning several parameters in order to generate a “nice” Mapper graph. This paper focuses on selecting the cover parameter. We present an algorithm that optimizes the cover of a Mapper graph by splitting a cover repeatedly according to a statistical test for normality. Our algorithm is based on G-means clustering, which searches for the optimal number of clusters in 𝑘-means by iteratively applying the Anderson–Darling test. Our splitting procedure employs a Gaussian mixture model to carefully choose the cover according to the distribution of the given data. In conclusion, experiments for synthetic and real-world datasets demonstrate that our algorithm generates covers so that the Mapper graphs retain the essence of the datasets, while also running significantly faster than a previous iterative method.

G-means clustering↗
DOE OSTI2017

Transverse Densities of Octet Baryons from Chiral Effective Field Theory

Transverse densities describe the distribution of charge and current at fixed light-front time and provide a frame-independent spatial representation of hadrons as relativistic systems. In this paper, we calculate the transverse densities of the octet baryons at peripheral distances b=O(M π -1 ) in an approach that combines chiral effective field theory (χχEFT) and dispersion analysis. The densities are represented as dispersive integrals of the imaginary parts of the baryon electromagnetic form factors in the timelike region (spectral functions). The spectral functions on the two-pion cut at t>4M$2\atop{π}$ are computed using relativistic χEFT with octet and decuplet baryons in the extended on-mass-shell renormalization scheme. The calculations are extended into the ρ-meson mass region using a dispersive method that incorporates the timelike pion form-factor data. The approach allows us to construct densities at distances b>1 fm with controlled uncertainties. Finally, our results provide insight into the peripheral structure of nucleons and hyperons and can be compared with empirical densities and lattice-QCD calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

The Influence of Environment on Post-Detonation Chemistry and Debris Formation (Abbreviated Final Report: 20-SI-006)

Predicting, responding to, or interpreting the chemical record preserved in debris derived from nuclear events can be challenging due to chemical fractionation. Chemical fractionation is where different species of the evolving radionuclide inventory segregate and/or are lost from the system over the timescales of debris formation. Both historic data and recent research suggest that the interaction and character of the local environment may exert controls on chemical fractionation by influencing the cooling and evolution of the associated fireball as well as the composition of the vapor term and resultant speciation. Prior to this work, an integrated platform permitting dynamic and concurrent consideration of physical and chemical evolution of early time post-detonation event environments did not exist. Our work merged historic data and experimental approaches to support development of a computational framework able to simulate fundamental processes (e.g., entrainment of local environment, oxidation chemistry, and cooling time scales) that may perturb the radionuclide inventory captured in post-detonation debris. Work with historic debris confirmed that entrained environmental material affect debris composition, structure, and radionuclide incorporation. Complementary work utilizing a readily controllable and tunable benchtop setup (a plasma flow reactor) simulated the late cooling of a nuclear fireball (e.g., T < 6000 K) and bounded the sensitivity of actinide speciation and particle size distribution to variations in oxygen concentration and cooling rates. Concurrent laser ablation and laser heating experiments were used to investigate the chemistry and physics of processes occurring in vaporized and/or rapidly heated actinides and other elements in the presence of oxygen. A more computationally efficient microphysical model was developed for predicting and evolving size distributions of particles forming from mixed vapor terms and simulating particle formation processes under a variety of extreme conditions. Continued study of historic nuclear event film confirmed that shockwave data and physics codes agree to within the uncertainty of the data. Good agreement was achieved for thermal emission from an airburst, however the paucity of low-temperature molecular opacity data for mixtures of air, bomb debris, entrained dirt, and water vapor complicate agreement for more elaborate scenarios. A multiphysics code (ALE3D) was modified to bring the necessary physics and chemistry, including these new data and insights, onto a single platform. Code development included improved initialization of large physical systems, modernization of chemistry capabilities, and modifications to enable inclusion of particle transport.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2018

Model of Solar Wind in the Heliosphere at Low and High Latitudes

The spatial distributions of the magnetic field, plasma density, and current at distances of (20–400)R{sub S} from the Sun (where R{sub S} is the solar radius) are investigated within a stationary axisymmetric MHD model of the solar wind (SW) at all latitudes in the inertial frame of reference with the origin at the center of the Sun. The model takes into account differential (with respect to the heliolatitude) rotation of the Sun and full corotation of plasma inside a boundary sphere of radius 20RS, which breaks down beyond this sphere. Self-consistent distributions of the plasma density, current, and magnetic field in the SW are obtained by numerically solving a set of time-independent MHD equations in spherical coordinates. It is demonstrated that the calculated results do not contradict observational data and describe a gradual transition from the fast SW at high heliolatitudes to the slow SW at low heliolatitudes, as well as the steepening of the profiles of the main SW characteristics with increasing distance from the Sun. The obtained dependences extend understanding of the SW structure at low and high latitudes and agree with the well-known Parker model in the limit of a small Ampère force.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Gravitational waves and galaxies cross-correlations: a forecast on GW biases for future detectors

ABSTRACT Gravitational waves (GWs) have rapidly become important cosmological probes since their first detection in 2015. As the number of detected events continues to rise, upcoming instruments like Einstein Telescope (ET) and Cosmic Explorer (CE) will observe millions of compact binary mergers. These detections, coupled with galaxy surveys by instruments such as the Dark Spectroscopic Energy Instrument (DESI), Euclid, and the Vera Rubin Observatory, will provide unique information on the large-scale structure of the universe by cross-correlating GWs with the distribution of galaxies hosting them. In this paper, we focus on how cross-correlations constrain the clustering bias of GWs emitted by the coalescence of binary black holes (BBHs). This parameter links BBHs to the underlying dark matter distribution, hence informing us how they populate galaxies. Using a multitracer approach, we forecast the precision of these measurements under different survey combinations. Our results indicate that current GW detectors will have limited precision, with measurement errors as high as $\displaystyle \sim 50~{{\ \rm per\ cent}}$. However, third-generation detectors like ET, when cross-correlated with Legacy Survey of Space and Time (LSST) data, can improve clustering bias measurements to within 2.5 per cent. Furthermore, we demonstrate that these cross-correlations can enable a per cent-level measurement of the magnification lensing effect on GWs. Despite this, there is a degeneracy between magnification and evolution biases, which hinders the precision of both. This degeneracy is most effectively addressed by assuming knowledge of one bias or targeting an optimal redshift range of $\displaystyle 1 \lt z \lt 2.5$. Our analysis opens new avenues for studying the distribution of BBHs and testing the nature of gravity through large-scale structure.

Zazzera, Stefano (ORCID:0000000158979221)↗
DOE OSTI2019

Microstructural, Magnetic, Magnetocaloric, and Electrical Properties of Ni{sub 0.4}Mg{sub 0.3}Cu{sub 0.3}Fe{sub 2}O{sub 4} Ferrite Prepared Using Sol–Gel Method

Detailed investigations of the microstructural, magnetic, magnetocaloric, and electrical properties of Ni{sub 0.4}Mg{sub 0.3}Cu{sub 0.3}Fe{sub 2}O{sub 4} ferrite synthesized by sol-gel method have been investigated. XRD pattern indicates that sample has cubic spinel structure with Fd 3-bar m symmetry. The cation distribution of the sample has been determined by Rietveld refinement. Temperature dependence of magnetization shows that sample exhibits a second-order PM to FM phase transition at the Curie temperature T{sub C} = 690 K. From the M(μ{sub 0}H,T) data, we found that the maximum entropy change |ΔS{sub M}{sup max}| reaches value of about 1.56 J kg{sup − 1} K{sup − 1} and relative cooling power (RCP) of 136 J kg{sup − 1} at μ{sub 0}H = 5 T. From electrical conductivity curves, the estimated value of the activation energy is equal to 0.349 eV. The Nequist diagram at different temperatures reveals that the grain boundary contribution is responsible to the conduction process for the studied sample.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

A hybrid architecture for volt-var control in active distribution grids

Modern active distribution grids are characterized by the increasing penetration of distributed energy resources (DERs). The proper coordination and scheduling of a large numbers of these small-scale and spatially distributed DERs is necessary, and warrants the use of novel distributed approaches. In this paper, we propose a hybrid volt-var control architecture for the distribution grid, which leverages existing centralized and local approaches to planning, decision making, and control, and augments it with distributed optimization and distributed control for DER management. First, we propose a convex model to describe the power physics of distribution grids of meshed topology and unbalanced structure, based on current injection and McCormick Envelopes. Second, we employ the distributed proximal atomic coordination (PAC) algorithm to coordinate DERs to provide voltage support. We implement volt-var optimization by optimally coordinating DERs including PV smart inverters and demand response. We present results using the IEEE-34 bus network, using real data from a distribution feeder in Hawaii, to model load and PV generation. Different levels of DER penetration and objective functions are simulated. Finally, our results show the need for the coordination of DERs to improve voltage profiles, even in networks with existing voltage control devices. Further, we show the need for flexible reactive power capabilities to achieve desired grid performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Investigation of 3D printed lightweight hybrid composites via theoretical modeling and machine learning

Hybrid composites combine two or more different fillers to achieve multifunctional or advanced material properties, such as lightweight and enhanced mechanical properties. The properties of the composites significantly depend on their microstructures, which can be tailored via advanced 3D printing processes. Understanding the process-structure-property relationships is critical to enable the design and engineering of novel hybrid composites for applications in aerospace, automotive, and protective coatings. Here, for this work, we develop 3D printable and lightweight hybrid composites and leverage the conventional design of experiments, a theoretical hybrid model, and an image-driven machine learning (ML) method to investigate their mechanical behaviors. The hybrid composites are formulated with elastomer matrix, microfillers, and thin-shell particles, enabling a significant degree of design freedom of microstructures with densities and mechanical properties varying up to 70% and 91%, respectively. Our statistical analysis indicates that the 3D printing path direction and the microfibers fraction are dominating process parameters with contribution percentages of 45.3% and 57.7% on the specific stiffness and strength, respectively. A hybrid mechanics model is developed based on a simple Weibull distribution function and classical single-filler models to effectively capture the variations in mechanical properties, however, it overestimates the values due to its statistical constraints and idealization of experimental uncertainty. The image-driven ML model leverages the microscale images directly without losing the structural details, shows more accurate predictions with experimental data, and has 48.6% lower root mean square error than the theoretical model.

3D printing↗
DOE OSTI2025

Kernel methods for evolution of generalized parton distributions

Generalized parton distributions (GPDs) characterize the 3-dimensional structure of hadrons, combining information about their internal quark and gluon longitudinal momentum distributions and transverse position within the hadron. The dependence of GPDs on the factorization scale Q 2 allows one to connect hard exclusive processes involving GPDs at disparate energy and momentum scales, which is needed in global analyses of experimental data. Here, in this work, we explore how finite element methods can be used to construct fast and differentiable Q 2 evolution codes for GPDs in momentum space, which can be used in a machine learning framework. We show numerical benchmarks of the methods' accuracy, including a comparison to an existing evolution code from PARTONS/APFEL++, and provide a repository where the code can be accessed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Extended hierarchical solvent perturbations from curved surfaces of mesoporous silica particles in a deep eutectic solvent

Here, many applications of deep eutectic solvents (DES) rely on exploitation of their unique yet complex liquid structures. Due to the ionic nature of the DES components, their diffuse structures are perturbed in the presence of a charged surface. We hypothesize that it is possible to perturb the bulk DES structure far (> 100 nm) from a curved, charged surface with mesoscopic dimensions. We performed in situ, synchrotron-based ultra-small angle X-ray scattering (USAXS) experiments to study the solvent distribution near the surface of charged mesoporous silica particles (MPS) (≈ 0.5 µm in diameter) suspended in both water and a common type of DES (1:2 choline Cl-:ethylene glycol). A careful USAXS analysis reveals that the perturbation of electron density distribution within the DES extends ≈ 1 μm beyond the particle surface, and that this perturbation can be manipulated by the addition of salt ions (AgCl). The concentration of the pore-filling fluid is greatly reduced in the DES. Notably, we extracted the real-space structures of these fluctuations from the USAXS data using a simulated annealing approach that does not require a priori knowledge about the scattering form factor, and can be generalized to a wide range of complex small-angle scattering problems.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Estimating the joint distribution of rate parameters across multiple reactions in the absence of experimental data

Here, a procedure for determining the joint uncertainty of Arrhenius parameters across multiple combustion reactions of interest is demonstrated. This approach is capable of constructing the joint distribution of the Arrhenius parameters arising from the uncertain measurements performed in specific target experiments without having direct access to the underlying experimental data. The method involves constructing an ensemble of hypothetical data sets with summary statistics consistent with the available information reported by the experimentalists, followed by a fitting procedure that learns the structure of the joint parameter density across reactions using this consistent hypothetical data as evidence. The procedure is formalized in a Bayesian statistical framework, employing maximum-entropy and approximate Bayesian computation methods and utilizing efficient Markov chain Monte Carlo techniques to explore data and parameter spaces in a nested algorithm. We demonstrate the application of the method in the context of experiments designed to measure the rates of selected chain reactions in the H 2 -O 2 system and highlight the utility of this approach for revealing the critical correlations between the parameters within a single reaction and across reactions, as well as for maximizing consistency when utilizing rate parameter information in predictive combustion modeling of systems of interest.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Comparison of the Optical Connectivity Method to X-Ray spray measurements in the near field of a diesel injector

For diesel sprays, the primary breakup processes are only rarely understood due to the high optical density and the resulting difficulties to measure them with extremely high spatial and sufficient temporal resolution. The Optical Connectivity Method (OCM) has been proposed in the last years to allow the determination of the breakup length of the connected liquid core, thus giving a measurement quantity of the primary breakup. In this research, an improved optical setup of the OCM is applied to a three-hole test injector nozzle where several measurement techniques are compared currently under well-defined conditions up to 100 MPa injection pressure. In this work, the direct comparison with X-Ray measurements done at the Advanced Photon Source of the Argonne National Laboratory will be described. This allows an evaluation of the OCM technique and a comparison of the different measurement quantities in the first 500 μm range of the spray. The structure of the spray is measured by X-Ray phase contrast imaging and the fuel mass distribution is measured by X-Ray absorption imaging. A detailed comparison of the two X-Ray techniques and the OCM technique has been possible for the first time. It is found that the measurement data of the spray near field are very congruent with all three methods. Due to this comparison, the measurement of the non-perturbed length, which describes the distance from the nozzle orifice up to the point where the formation of surface disturbances is starting, by the OCM is validated for the first time. Within this non-perturbed length of the spray, the OCM signal is weak before it starts to illuminate from the scattering of the perturbed surface. Hence, the OCM technique can deliver two characteristic length scales, the non-perturbed length and the breakup length , characterizing the primary spray breakup.

33 ADVANCED PROPULSION SYSTEMS↗