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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Weak Production of Strange and Charmed Ground-State Baryons in Nuclei

We present results for the quasielastic weak production of Λ and Σ hyperons induced by ν¯ scattering off nuclei in the kinematical region of interest for accelerator neutrino experiments. We employ realistic hole spectral functions and we describe the propagation of the hyperons in the nuclear medium by means of a Monte Carlo cascade. The latter strongly modifies the kinematics and the relative production rates of the hyperons, leading to a nonvanishing Σ+ cross section, to a sizable enhancement of the Λ production and to a drastic reduction of the Σ0 and Σ− distributions. We also compute the quasielastic weak Λc production cross section, paying special attention to estimate the uncertainties induced by the model dependence of the vacuum n→Λc weak matrix element. In this regard, the recent BESIII measurements of the branching ratios of Λc→Λl+νl (l=e,μ) are used to benchmark the available theoretical predictions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Fabrication and characterization of multifunctional Fe/TiO2 composite coatings

Highlights: • Electrodeposition of Fe/TiO{sub 2} composite coatings using methanesulfonate electrolytes. • TiO{sub 2} sol is synthesized by means of precipitation technique. • Electrodeposition kinetics obeys the improved Guglielmi's model. • Incorporation of TiO{sub 2} into Fe matrix results in an increase in microhardness. • Enhanced electrocatalytic and photocatalytic activity of Fe/TiO{sub 2} composites. - Abstract: Composite Fe/TiO{sub 2} coatings were electrodeposited using environmentally friendly colloidal methanesulfonate electrolytes. A sol of titania nano-particles was synthesized by means of precipitation technique. The electrodeposition parameters and the properties of composite coatings were compared with those typical of analogous composite electrodeposits produced from the plating bath containing suspended commercially available nano-powder Degussa P25. The electrodeposition process obeys the modified Guglielmi's model. The incorporation of TiO{sub 2} dispersed phase into iron matrix results in an appreciable increase in the microhardness due to dispersion strengthening. The microhardness of deposits obtained from electrolyte with the addition of nano-sized titania sol exceeds that which is observed for coatings produced from the bath containing aggregated Degussa P25 TiO{sub 2} particles. The introduction of dioxide titanium particles into Fe matrix yields photocatalytic properties towards the reaction of organic dye degradation and improves electrocatalytic performance towards hydrogen and oxygen evolution reactions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

In-beam γ-ray spectroscopy of 37–42 P

The level schemes of the neutron-rich 37-42 P isotopes are investigated via in-beam gamma-ray spectroscopy following the fragmentation of a 45 Cl projectile beam at intermediate beam energies. Information on gamma-gamma coincidence relationships complemented by comparisons to shell-model calculations in the sd-pf model space were used to construct excitation level schemes for these neutron-rich nuclei. For the odd-mass 37,39 P isotopes, a level scheme is presented that appears essentially complete at low energies and exhausts the states predicted by the SDPF-MU shell-model Hamiltonian. In conclusion, simple Nilsson configurations are proposed for the low-lying excited states of 38,39,40,41 P from an analysis of the E2 transition matrix elements and moments calculated within the shell model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Optimization of micropillar sequences for fluid flow sculpting

Inertial fluid flow deformation around pillars in a microchannel is a new method for controlling fluid flow. Sequences of pillars have been shown to produce a rich phase space with a wide variety of flow transformations. Previous work has successfully demonstrated manual design of pillar sequences to achieve desired transformations of the flow cross section, with experimental validation. However, such a method is not ideal for seeking out complex sculpted shapes as the search space quickly becomes too large for efficient manual discovery. We explore fast, automated optimization methods to solve this problem. We formulate the inertial flow physics in microchannels with different micropillar configurations as a set of state transition matrix operations. These state transition matrices are constructed from experimentally validated streamtraces for a fixed channel length per pillar. This facilitates modeling the effect of a sequence of micropillars as nested matrix-matrix products, which have very efficient numerical implementations. With this new forward model, arbitrary micropillar sequences can be rapidly simulated with various inlet configurations, allowing optimization routines quick access to a large search space. We integrate this framework with the genetic algorithm and showcase its applicability by designing micropillar sequences for various useful transformations. We computationally discover micropillar sequences for complex transformations that are substantially shorter than manually designed sequences. We also determine sequences for novel transformations that were difficult to manually design. Finally, we experimentally validate these computational designs by fabricating devices and comparing predictions with the results from confocal microscopy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Learning physics-based reduced-order models from data using nonlinear manifolds

Here we present a novel method for learning reduced-order models of dynamical systems using nonlinear manifolds. First, we learn the manifold by identifying nonlinear structure in the data through a general representation learning problem. The proposed approach is driven by embeddings of low-order polynomial form. A projection onto the nonlinear manifold reveals the algebraic structure of the reduced-space system that governs the problem of interest. The matrix operators of the reduced-order model are then inferred from the data using operator inference. Numerical experiments on a number of nonlinear problems demonstrate the generalizability of the methodology and the increase in accuracy that can be obtained over reduced-order modeling methods that employ a linear subspace approximation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Post-Fracturing Experiment Simulation of Hydraulic Fracture Propagation in a Deep Mine Using a Fully Coupled 3D Network-Flow and Quasi-static Discrete Element Model

Aimed at supporting the hydraulic fracturing experiments in a vertical borehole in the Poorman phyllite at approximately 1500 m depth at the Sanford Underground Research Facility (SURF), we perform post-hydraulic fracturing experiment simulations and compare the simulated borehole pressure changes and flow rates with actual measurements using a newly developed fully coupled three-dimensional (3D) network flow and quasi-static discrete element model (DEM). The quasi-static DEM model, which is constructed by Delaunay tessellation of the rock volume, considers rock fabric heterogeneities by using the “disordered” DEM mesh and adding random perturbations to the stiffness and tensile/shear strengths of individual DEM elements and the elastic beam between them. A conjugate 3D flow network based on DEM lattice is constructed to calculate the fluid flow in both the fracture and porous matrix. One distinctive advantage of the DEM model is that fracturing is naturally described by the breakage of elastic beams between DEM elements. It is also extremely convenient to introduce mechanical anisotropy into the model by simply assigning orientation-dependent tensile/shear strengths to the elastic beams.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

DRIPS: A framework for dimension reduction and interpolation in parameter space

Reduced-order models are often used to describe the behavior of complex systems, whose simulation with a full model is too expensive, or to extract salient features from the full model’s output. We introduce a new model-reduction framework DRIPS (dimension reduction and interpolation in parameter space) that combines the offline local model reduction with the online parameter interpolation of reduced-order bases (ROBs). The offline step of this framework relies on dynamic mode decomposition (DMD) to build a low-rank linear surrogate model, equipped with a local ROB, for quantities of interest derived from the training data generated by repeatedly solving the (nonlinear) high-fidelity model for multiple parameter points. The online step consists of the construction of a parametric reduced-order model for each target/test point in the parameter space, with the interpolation of ROBs done on a Grassman manifold and the interpolation of reduced-order operators done on a matrix manifold. The DMD component enables DRIPS to model (typically low-dimensional) quantities of interest directly, without having to access the (typically high-dimensional and possibly nonlinear) operators in a high-fidelity model that governs the dynamics of the underlying high-dimensional state variables, as required in projection-based reduced-order modeling. A series of numerical experiments suggests that DRIPS yields a model reduction, which is computationally more efficient than the commonly used projection-based proper orthogonal decomposition; it does so without requiring a prior knowledge of the governing equation for quantities of interest. Furthermore, for the nonlinear systems considered, DRIPS is more accurate than Gaussian-process interpolation (Kriging).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Factorized three-body S-matrix restrained by the Yang–Baxter equation and quantum entanglements

This paper investigates the physical effects of the Yang–Baxter equation (YBE) to quantum entanglements through the 3-body S-matrix in entangling parameter space. The explicit form of 3-body S-matrix Ř{sub 123}(θ,φ) based on the 2-body S-matrices is given due to the factorization condition of YBE. The corresponding chain Hamiltonian has been obtained and diagonalized, also the Berry phase for 3-body system is given. It turns out that by choosing different spectral parameters the Ř(θ,φ)-matrix gives GHZ and W states respectively. The extended 1-D Kitaev toy model has been derived. Examples of the role of the model in entanglement transfer are discussed. - Highlights: • We give the relation between 3-body S-matrix and 3-qubit entanglement. • The relation between 3-qubit and 2-qubit entanglements is investigated via YBE. • 1D Kitaev toy model is derived by the Type-II solution of YBE. • The condition of YBE kills the “Zero boundary mode” in our chain model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Neutron Number Probability Distributions in a Subcritical System Using the Forward Master Equation

The subject of this paper is the determination of the equilibrium probability distribution function (PDF) of the neutron population within a subcritical multiplying system in the presence of an intrinsic random source as a result of spontaneous fission (SF). Such systems are strongly stochastic and low order moments such as the mean and variance of the neutron number are not sufficient to characterize the true state of the neutron population. We base our work on the forward Master equation in a lumped model formulation for P{sub n} (t), n = 0, 1, 2,..., the probability of there existing η neutrons at time t and obtain solutions for the steady state distributions. The key parameters in this model, neutron lifetime and fission probability, are rigorously obtained by numerically solving the k-eigenvalue problem in a one-dimensional spherical system and using standard definitions of lumped parameters in terms of production and loss rates in finite systems. Previous work has examined single-chain PDFs (a single fission and the resulting progeny) for neutrons, uncoupled neutron-photon single-chain PDFs, both using a lumped backward Master equation formulation, as well as neutron PDFs in supercritical systems. In this paper, we analyze strictly subcritical systems, for which we compare analytically derived solutions with numerical computations for different multiplicity distribution models. For subcritical systems where the neutron population remains finite at steady state, we show that the forward Master equation can be very efficiently solved numerically to obtain the equilibrium distributions. Finally, this work is motivated by potential application to passive interrogation for detection of diverted nuclear materials as well to criticality safety. The equilibrium neutron number probability distribution in subcritical systems has been numerically investigated for several models of the induced and spontaneous fission multiplicity distribution. A well known approximate but closed form solution, namely the quadratic model, was shown to be unacceptably accurate for subcritical media. The matrix inversion and the recursion methods agree well and were benchmarked with the binary fission model, but the recursion formulation proves far more computationally efficient. A qualitative change in the shape of the neutron PDF is observed for increasing source strength, as expected, and a transition from a stochastic to a deterministic system is expected for a sufficiently strong source. We are currently extending this approach to obtain the equilibrium joint distribution of neutrons within the system and those that have leaked, to explicitly represent the neutron PDF as observed by an external detector. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Emergent Chiral Spin Liquid: Fractional Quantum Hall Effect in a Kagome Heisenberg Model

The fractional quantum Hall effect (FQHE) realized in two-dimensional electron systems under a magnetic field is one of the most remarkable discoveries in condensed matter physics. Interestingly, it has been proposed that FQHE can also emerge in time-reversal invariant spin systems, known as the chiral spin liquid (CSL) characterized by the topological order and the emerging of the fractionalized quasiparticles. A CSL can naturally lead to the exotic superconductivity originating from the condense of anyonic quasiparticles. Although CSL was highly sought after for more than twenty years, it had never been found in a spin isotropic Heisenberg model or related materials. By developing a density-matrix renormalization group based method for adiabatically inserting flux, we discover a FQHE in a spin-$ \frac{1}{2}$ isotropic kagome Heisenberg model. We identify this FQHE state as the long-sought CSL with a uniform chiral order spontaneously breaking time reversal symmetry, which is uniquely characterized by the half-integer quantized topological Chern number protected by a robust excitation gap. The CSL is found to be at the neighbor of the previously identified Z2 spin liquid, which may lead to an exotic quantum phase transition between two gapped topological spin liquids.

MAGNETIC PROPERTIES AND MATERIALS↗
DOE OSTI2018

Multi-scale computational analysis of unidirectional carbon fiber reinforced polymer composites under various loading conditions

In this study, a multi-scale computational analysis based on representative volume element (RVE) modeling and molecular dynamics (MD) simulations is developed to investigate the microscopic failure mechanisms of unidirectional (UD) carbon fiber reinforced polymer (CFRP) composites. The average properties of the 200-nm thickness interphase region between fiber and matrix are characterized through MD simulations and an analytical gradient model. The results demonstrate that the interphase region has higher Young’s modulus and strength, compared to the bulk matrix. This stiffened interphase region influences the composite response significantly. Specifically, the traditional two-phase model with zero-thickness interface fails to capture the stress-strain behavior compared to the experimental data. However, by adding the interphase region to a modified RVE model, the accuracy of simulation results will be improved significantly. Furthermore, a coupled experimental-computational micromechanics approach is adopted to calibrate and validate the cohesive parameters of the interface. By including the cohesive interface, our modified RVE model accurately captures the failure strength of the composites. Finally, different failure mechanisms for specimens are investigated using our multi-scale computational framework. In conclusion, the results show that the failure modes of UD CFRP composites are very complex and multiple failure mechanisms co-exist depending on the loading conditions, agreeing well with our experimental analyses.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Inhibition of soluble epoxide hydrolase attenuates hepatic fibrosis and endoplasmic reticulum stress induced by carbon tetrachloride in mice

Liver fibrosis is a pathological condition in which chronic inflammation and changes to the extracellular matrix lead to alterations in hepatic tissue architecture and functional degradation of the liver. Inhibitors of the enzyme soluble epoxide hydrolase (sEH) reduce fibrosis in the heart, pancreas and kidney in several disease models. In this study, we assess the effect of sEH inhibition on the development of fibrosis in a carbon tetrachloride (CCl{sub 4})-induced mouse model by monitoring changes in the inflammatory response, matrix remolding and endoplasmic reticulum stress. The sEH inhibitor 1-trifluoromethoxyphenyl-3-(1-propionylpiperidin-4-yl) urea (TPPU) was administered in drinking water. Collagen deposition in the liver was increased five-fold in the CCl{sub 4}-treated group, and this was returned to control levels by TPPU treatment. Hepatic expression of Col1a2 and 3a1 mRNA was increased over fifteen-fold in the CCl{sub 4}-treated group relative to the Control group, and this increase was reduced by 50% by TPPU treatment. Endoplasmic reticulum (ER) stress observed in the livers of CCl{sub 4}-treated animals was attenuated by TPPU treatment. In order to support the hypothesis that TPPU is acting to reduce the hepatic fibrosis and ER stress through its action as a sEH inhibitor we used a second sEH inhibitor, trans-4-(4-[3-(4-trifluoromethoxy-phenyl)-ureido]-cyclohexyloxy)-benzoic acid (t-TUCB), and sEH null mice. Taken together, these data indicate that the sEH may play an important role in the development of hepatic fibrosis induced by CCl{sub 4}, presumably by reducing endogenous fatty acid epoxide chemical mediators acting to reduce ER stress. - Highlights: • We administer an inhibitor of sEH in a CCl4 murine model. • sEH inhibition reduces liver collagen deposition and pro-fibrotic gene expression. • sEH inhibition induces MMP-1a activity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

3D Modeling Effect of Spherical Inclusions on the Magnetostriction of Bulk Superconductors

In this paper, the dependence of the effective magnetostriction of bulk superconductors on the elastic parameters including the volume fraction and elastic modulus ratio is studied by a three-dimensional model consisting of a spherical inclusion–superconducting matrix system. The effect of the elastic modulus and volume fraction on the magnetostriction is also obtained through the magnetostriction loop. The results indicate that the elastic modulus and volume fraction have obvious effects on the effective magnetostriction of the superconducting composite, which gives an explanation about the differences between the experimental and the theoretical results. Furthermore, it is worth pointing out that the linear field dependence of magnetostriction is unique to the Bean model by comparing the curve shapes of the magnetostriction loop with and without inclusion.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

Effects of error covariance structure on estimation of model averaging weights and predictive performance

When conducting model averaging for assessing groundwater conceptual model uncertainty, the averaging weights are often evaluated using model selection criteria such as AIC, AICc, BIC, and KIC (Akaike Information Criterion, Corrected Akaike Information Criterion, Bayesian Information Criterion, and Kashyap Information Criterion, respectively). However, this method often leads to an unrealistic situation in which the best model receives overwhelmingly large averaging weight (close to 100%), which cannot be justified by available data and knowledge. It was found in this study that this problem was caused by using the covariance matrix, CE, of measurement errors for estimating the negative log likelihood function common to all the model selection criteria. This problem can be resolved by using the covariance matrix, Cek, of total errors (including model errors and measurement errors) to account for the correlation between the total errors. An iterative two-stage method was developed in the context of maximum likelihood inverse modeling to iteratively infer the unknown Cek from the residuals during model calibration. The inferred Cek was then used in the evaluation of model selection criteria and model averaging weights. While this method was limited to serial data using time series techniques in this study, it can be extended to spatial data using geostatistical techniques. The method was first evaluated in a synthetic study and then applied to an experimental study, in which alternative surface complexation models were developed to simulate column experiments of uranium reactive transport. It was found that the total errors of the alternative models were temporally correlated due to the model errors. The iterative two-stage method using Cek resolved the problem that the best model receives 100% model averaging weight, and the resulting model averaging weights were supported by the calibration results and physical understanding of the alternative models. Using Cek obtained from the iterative two-stage method also improved predictive performance of the individual models and model averaging in both synthetic and experimental studies.

error correlation↗
DOE OSTI2020

Density Matrix Quantum Circuit Simulation via the BSP Machine on Modern GPU Clusters

As quantum computers evolve, simulations of quantum programs on classical computers will be essential in validating quantum algorithms, understanding the effect of system noise, and design applications for future quantum computers. In this paper, we propose a novel multi-GPU programming model called MG-BSP that constructs a virtual BSP machine on top of modern multi-GPU platforms, and tweak the programming model to build a multi-GPU density matrix quantum simulator. We propose and evaluated a new formulation minimizing communication and prove that the transformation conserves original semantics when noise is introduced. We build the tool-chain to support quantum assembly open standard, synthesize testing quantum circuit, and enable ultra-deep quantum simulation. We evaluated our design on four state-of-the-art multi-GPU platforms including the latest DGX-1 and DGX-2 systems. We demonstrate simulation of 1 million gates in 94 minutes, far deeper circuits than has been demonstrated in prior work. A roofline-model analysis show that we have reached near-optimal performance under memory bound.

Li, Ang↗
DOE OSTI2015

Solvable four-state Landau-Zener model of two interacting qubits with path interference

In this paper, I identify a nontrivial four-state Landau-Zener model for which transition probabilities between any pair of diabatic states can be determined analytically and exactly. The model describes an experimentally accessible system of two interacting qubits, such as a localized state in a Dirac material with both valley and spin degrees of freedom or a singly charged quantum dot (QD) molecule with spin orbit coupling. Application of the linearly time-dependent magnetic field induces a sequence of quantum level crossings with possibility of interference of different trajectories in a semiclassical picture. I argue that this system satisfies the criteria of integrability in the multistate Landau-Zener theory, which allows one to derive explicit exact analytical expressions for the transition probability matrix. Finally, I also argue that this model is likely a special case of a larger class of solvable systems, and present a six-state generalization as an example.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Non-Destructive Imaging of a Liquid Moving Through Porous Media Using a Computer Tomography Scanner

The most common approach used by modelers to describe movement of liquids through a porous solid, such as cement, sediment, or glass, is to assume a uniform flow rate, such as a Darcy Flux or a diffusion constant. However, this convenient simplification is problematic because in many cases it ignors the presence of fractures and macropores, which commonly dominate water flow and contaminant transport. For this reason, it is common that such modeling results do not reflect the multi-modal flow detected in laboratory and field studies. The objective of this seedling study was to develop a new capability for SRNL to track liquid moving through micro- (matrix-) and macro-flow using an X-ray Computed Topography (CT) Scanner. 4-dimensional anamated renditions were created that permited quantifying traditional matrix flow and macropore flow. These animations were modelled using a public domain software, HYDRUS 1-D, describing one dimension, dual-porosity and dual-permeability processes. This new capability provides a proof of concept for reducing model uncertainty applicable to waste disposal risk calculations, environmental remediation, and waste form development when describing the movement of liquids as they pass through glass, cement, fractured rock, or soil.

47 OTHER INSTRUMENTATION↗