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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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Supergravitational conformal Galileons

The worldvolume actions of 3+1 dimensional bosonic branes embedded in a five-dimensional bulk space can lead to important effective field theories, such as the DBI conformal Galileons, and may, when the Null Energy Condition is violated, play an essential role in cosmological theories of the early universe. These include Galileon Genesis and “bouncing” cosmology, where a pre-Big Bang contracting phase bounces smoothly to the presently observed expanding universe. Perhaps the most natural arena for such branes to arise is within the context of superstring and M -theory vacua. Here, not only are branes required for the consistency of the theory, but, in many cases, the exact spectrum of particle physics occurs at low energy. However, such theories have the additional constraint that they must be N = 1 supersymmetric. This motivates us to compute the worldvolume actions of N = 1 supersymmetric three-branes, first in flat superspace and then to generalize them to N = 1 supergravitation. In this paper, for simplicity, we begin the process, not within the context of a superstring vacuum but, rather, for the conformal Galileons arising on a co-dimension one brane embedded in a maximally symmetric AdS 5 bulk space. We proceed to N = 1 supersymmetrize the associated worldvolume theory and then generalize the results to N = 1 supergravity, opening the door to possible new cosmological scenarios

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Membrane Protein Structure, Function, and Dynamics: a Perspective from Experiments and Theory

It is fundamental for the flourishing biological cells that membrane proteins mediate the process. Membrane-embedded transporters move ions and larger solutes across membranes; receptors mediate communication between the cell and its environment and membrane-embedded enzymes catalyze chemical reactions. Understanding these mechanisms of action requires knowledge of how the proteins couple to their fluid, hydrated lipid membrane environment. Here, we present here current studies in computational and experimental membrane protein biophysics, and show how they address outstanding challenges in understanding the complex environmental effects on the structure, function, and dynamics of membrane proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Study of Intermittent Turbulence in Stable Arctic Boundary Layers

Abstract Polar boundary layers are difficult to model due to the existence of intermittent turbulence within stable layers. Here we present a case study evaluation of coherent structures in a stable boundary layer observed during a series of flights with an uncrewed aircraft system (DataHawk2) on 19 October 2016 at Oliktok Point, Alaska as part of the ERASMUS (Evaluation of Routine Atmospheric Sounding Measurements using Unmanned Systems) field campaign. During a sequence of five flights over a nine-hour period, 57 profiles of atmospheric properties (0–400 m a.g.l) were collected. Turbulence was identified using derived Richardson Number, temperature structure function parameter, and turbulence kinetic energy dissipation. Throughout all flights on this strongly stable day, intermittent turbulence was observed. These turbulent layers showed well-mixed potential temperature profiles embedded within otherwise stable potential temperature profiles; often resulting in a characteristic staircase pattern. Turbulent layers ranged from 1 to 30 m deep, with most individual layers being 1–2 m deep. Vertical propagation velocities of layers in the lower atmosphere were on the order of a few cm s −1 , typical of non-convective environments. In different regions of the profile, turbulence was driven by a different balance of buoyancy and shear forces, with turbulence in the near surface environment driven by strong shear forces overcoming strong resistance to buoyancy, while turbulence in elevated layers characterized by weaker shear forces overcoming weaker resistance to buoyancy. We discuss the potential of such datasets for improving subgrid parameterizations of small-scale turbulence embedded within stable boundary layers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Two-dimensional versus three-dimensional constraints in hetero-epitaxy/orientation relationships

Molecular dynamics simulations have been performed to compare the orientation relationships (ORs) that develop between Ag films/particles equilibrated with Ni, depending on whether the Ag is subjected to three-dimensional (3-D) confinement by being embedded in Ni, or to 2-D confinement by equilibration with a Ni substrate. Previous results of both simulations and experiments have shown that Ag films equilibrated with planar Ni substrates display a large number of different ORs; in particular, Ag equilibrated on Ni{100} displays an OR of Ag{111} <110> // Ni{100} <110>, often referred to as an oct-cube OR. Here it is shown that a Ag particle embedded in Ni displays an OR of Ag{111} <110> // Ni{111} <110>, i.e., a cube-on-cube OR. It has also been shown that as the confinement of a Ag particle is gradually increased from 2-D to 3-D, by equilibrating a Ag particle on Ni(100) substrates with progressively deeper dimples, a transition in OR occurs from oct-cube to cube-on-cube. So, this result contradicts the conventional notion which supposes that the ORs displayed in the presence of 3-D confinement (e.g., during phase transformations) will also tend to be displayed in epitaxy on a substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Quantum size effects and tunable visible photoluminescence in a-Si:H/nc-Si:H superlattices

Quantum size effects are commonly observed in semiconductor nanocrystals and quantum dots. Here, we demonstrate unexpected quantum size effects in an unusual bulk system with multiple interfaces, consisting of alternating layers of nanocrystalline silicon (nc-Si:H) and amorphous silicon (a-Si:H) material thin films. The nc-Si:H layers consist of silicon nanocrystals embedded in an amorphous matrix, with an amorphous-crystalline interface separating the two structures. Plasma-enhanced chemical vapor deposition was utilized to grow nanocrystalline-amorphous silicon superlattices with a varying thickness of the nanocrystalline layer. Strong visible photoluminescence at room temperature was deconvoluted into individual peaks. As the nanocrystalline silicon layer thickness was increased from 5 to 20 nm, the photoluminescence spectra red-shifted with the emission wavelength varying as d 2 (d is the size of the nanocrystallites), the characteristic signature underlying quantum size effects. The size d of the nanocrystals was estimated by the measured shift of the Raman peak, and could be tuned by varying the thickness of the nc-Si:H layers. High resolution transmission electron microscopy show nanocrystals with a narrow size distribution, in an amorphous matrix. We also observe long wavelength photoluminescence from interfacial states that leads to persistent photconductivity. In conclusion nanocrystalline-amorphous superlattices offer a unique pathway for synthesizing embedded nanocrystals with controlled sizes and photonic signatures.

36 MATERIALS SCIENCE↗
DOE OSTI2018

On the Ultrasolvability of Some Classes of Minimal Nonsplit p-Extensions with Cyclic Kernel for p > 2

For any nonsplit p > 2-extension of finite groups with a cyclic kernel and a quotient group with two generators all the accompanying extensions of which split, there exists a realization of the quotient group as a Galois group of number fields such that the corresponding embedding problem is ultrasolvable (i.e., this embedding problem is solvable and has only fields as solutions).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. It relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.

58 GEOSCIENCES↗
DOE OSTI2024

EPR studies of ferredoxin in spinach and cyanobacterial thylakoids related to photosystem I-driven NADP + reduction

Photosynthetic light-dependent reactions occur in thylakoid membranes where embedded proteins capture light energy and convert it to chemical energy in the form of ATP and NADPH for use in carbon fixation. One of these integral membrane proteins is Photosystem I (PSI). PSI catalyzes light-driven transmembrane electron transfer from plastocyanin (Pc) to oxidized ferredoxin (Fd). Electrons from reduced Fd are used by the enzyme ferredoxin-NADP + reductase (FNR) for the reduction of NADP + to NADPH. Fd and Pc are both small soluble proteins whereas the larger FNR enzyme is associated with the membrane. To investigate electron shuttling between these diffusible and embedded proteins, thylakoid photoreduction of NADP + was studied. As isolated, both spinach and cyanobacterial thylakoids generate NADPH upon illumination without extraneous addition of Fd. These findings indicate that isolated thylakoids either (i) retain a “pool” of Fd which diffuses between PSI and membrane bound FNR or (ii) that a fraction of PSI is associated with Fd, with the membrane environment facilitating PSI-Fd-FNR interactions which enable multiple turnovers of the complex with a single Fd. To explore the functional association of Fd with PSI in thylakoids, electron paramagnetic resonance (EPR) spectroscopic methodologies were developed to distinguish the signals for the reduced Fe-S clusters of PSI and Fd. Temperature-dependent EPR studies show that the EPR signals of the terminal [4Fe-4S] cluster of PSI can be distinguished from the [2Fe-2S] cluster of Fd at > 30 K. At 50 K, the cw X-band EPR spectra of cyanobacterial and spinach thylakoids reduced with dithionite exhibit EPR signals of a [2Fe-2S] cluster with g-values g x = 2.05, g y = 1.96, and g z = 1.89, confirming that Fd is present in thylakoid preparations capable of NADP + photoreduction. Quantitation of the EPR signals of P 700 + and dithionite reduced Fd reveal that Fd is present at a ratio of ~ 1 Fd per PSI monomer in both spinach and cyanobacterial thylakoids. Light-driven electron transfer from PSI to Fd in thylakoids confirms Fd is functionally associated (< 0.4 Fd/PSI) with the acceptor end of PSI in isolated cyanobacterial thylakoids. Furthermore, these EPR experiments provide a benchmark for future spectroscopic characterization of Fd interactions involved in multistep relay of electrons following PSI charge separation in the context of photosynthetic thylakoid microenvironments.

Electron paramagnetic resonance↗
DOE OSTI2023

Solving larger maximum clique problems using parallel quantum annealing

Quantum annealing has the potential to find low energy solutions of NP-hard problems that can be expressed as quadratic unconstrained binary optimization problems. However, the hardware of the quantum annealer manufactured by D-Wave Systems, which we consider in this work, is sparsely connected and moderately sized (on the order of thousands of qubits), thus necessitating a minor-embedding of a logical problem onto the physical qubit hardware. The combination of relatively small hardware sizes and the necessity of a minor-embedding can mean that solving large optimization problems is not possible on current quantum annealers. In this research, we show that a hybrid approach combining parallel quantum annealing with graph decomposition allows one to solve larger optimization problem accurately. We apply the approach to the Maximum Clique problem on graphs with up to 120 nodes and 6395 edges.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Phenomenological Model of Nonlinear Dynamics and Deterministic Chaotic Gas Migration in Bentonite: Experimental Evidence and Diagnostic Parameters

Understanding gas migration in compacted clay materials, e.g., bentonite and claystone, is important for the design and performance assessment of an engineered barrier system of a radioactive waste repository system, as well as many practical applications. Existing field and laboratory data on gas migration processes in low-permeability clay materials demonstrate the complexity of flow and transport processes, including various types of instabilities, caused by nonlinear dynamics of coupled processes of liquid–gas exchange, dilation, fracturing, fracture healing, etc., which cannot be described by classical models of fluid dynamics in porous media. We here show that the complexity of gas migration processes can be explained using a phenomenological concept of nonlinear dynamics and deterministic chaos theory. To do so, we analyzed gas pressure and gas influx (i.e., input) and outflux (i.e., output), recorded during the gas injection experiment in the compact Mx80-D bentonite sample, and calculated a set of the diagnostic parameters of nonlinear dynamics and chaos, such a global embedding dimension, a correlation dimension, an information dimension, and a spectrum of Lyapunov exponents, as well as plotted 2D and 3D pseudo-phase-space strange attractors, based on the univariate influx and outflux time series data. These results indicate the presence of phenomena of low-dimensional deterministic chaotic behavior of gas migration in bentonite. In particular, during the onset of gas influx in the bentonite core, before the breakthrough, the development of gas flow pathways is characterized by the process of chaotic gas diffusion. After the breakthrough, with inlet-to-outlet movement of gas, the prevailing process is chaotic advection. During the final phase of the experiment, with no influx to the sample, the relaxation pattern of gas outflux is resumed back to a process of chaotic diffusion. The types of data analysis and a proposed phenomenological model can be used to establish the basic principles of experimental data-gathering, modeling predictions, and a research design.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Decomposition Algorithms for Solving NP-hard Problems on a Quantum Annealer

NP-hard problems such as the maximum clique or minimum vertex cover problems, two of Karp’s 21 NP-hard problems, have several applications in computational chemistry, biochemistry and computer network security. Adiabatic quantum annealers can search for the optimum value of such NP-hard optimization problems, given the problem can be embedded on their hardware. However, this is often not possible due to certain limitations of the hardware connectivity structure of the annealer. This paper studies a general framework for a decomposition algorithm for NP-hard graph problems aiming to identify an optimal set of vertices. Our generic algorithm allows us to recursively divide an instance until the generated subproblems can be embedded on the quantum annealer hardware and subsequently solved. Furthermore, the framework is applied to the maximum clique and minimum vertex cover problems, and we propose several pruning and reduction techniques to speed up the recursive decomposition. The performance of both algorithms is assessed in a detailed simulation study.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Transient Heat and Material Flow Modeling of Friction Stir Processing of Magnesium Alloy using Threaded Tool

A three-dimensional transient computational fluid dynamics (CFD) model was developed to investigate the material flow and heat transfer during friction stir processing (FSP) in an AZ31B magnesium alloy. The material was assumed to be a non-Newtonian viscoplastic fluid, and the Zener-Hollomon parameter was used to describe the dependence of material viscosity on temperature and strain rate. The material constants used in the constitutive equation were determined experimentally from compression tests of the AZ31B Mg alloy under a wide range of strain rates and temperatures. A dynamic mesh method, combining both Lagrangian and Eulerian formulations, was used to capture the material flow induced by the movement of the threaded tool pin. Massless inert particles were embedded in the simulation domain to track the detailed history of material flow. The actual FSP was also carried out on a wrought Mg plate where temperature profiles were recorded by embedding thermocouples. The predicted transient temperature history was found to be consistent with that measured during FSP. Finally, the influence of the thread on the simulated results of thermal history and material flow was studied by comparing two models: one with threaded pin and the other with smooth pin surface.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Numerical study of the stress state of a deformation twin in magnesium

We present here a numerical study of the distribution of the local stress state associated with deformation twinning in Mg, both inside the twinned domain and in its immediate neighborhood, due to the accommodation of the twinning transformation shear. A full-field elastoviscoplastic formulation based on fast Fourier transformation is modified to include the shear transformation strain associated with deformation twinning. We have performed two types of twinning transformation simulations with: (i) the twin completely embedded inside a single crystal and (ii) the twin front terminating at a grain boundary. We show that: (a) the resulting stress distribution is more strongly determined by the shear transformation than by the intragranular character of the twin or the orientation of the neighboring grain; (b) the resolved shear stress on the twin plane along the twin direction is inhomogeneous along the twin–parent interface; and (c) there are substantial differences in the average values of the shear stress in the twin and in the parent grain that contains the twin. We discuss the effect of these local stresses on twin propagation and growth, and the implications of our findings for the modeling of deformation twinning.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Integrating a reservoir regulation scheme into a spatially distributed hydrological model

During the past several decades, numerous reservoirs have been built across the world for a variety of purposes such as flood control, irrigation, municipal/industrial water supplies, and hydropower generation. Consequently, natural streamflow timing and magnitude have been altered significantly by reservoir operations. In addition, the hydrological cycle can be modified by land use/land cover and climate changes. To understand the fine scale feedback between hydrological processes and water management decisions, a distributed hydrological model embedded with a reservoir component is of desire. In this study, a multi-purpose reservoir module with predefined complex operational rules was integrated into the Distributed Hydrology Soil Vegetation Model (DHSVM). Conditional operating rules, which are designed to reduce flood risk and enhance water supply reliability, were adopted in this module. The performance of the integrated model was tested over the upper Brazos River Basin in Texas, where two U.S. Army Corps of Engineers reservoirs, Lake Whitney and Aquilla Lake, are located. The integrated DHSVM model was calibrated and validated using observed reservoir inflow, outflow, and storage data. The error statistics were summarized for both reservoirs on a daily, weekly, and monthly basis. Using the weekly reservoir storage for Lake Whitney as an example, the coefficients of determination (R2) and the Nash-Sutcliff Efficiency (NSE) are 0.85 and 0.75, respectively. These results suggest that this reservoir module has promise for use in sub-monthly hydrological simulations. Enabled with the new reservoir component, the DHSVM model provides a platform to support adaptive water resources management under the impacts of evolving anthropogenic activities and substantial environmental changes.

Zhao, Gang↗
DOE OSTI2025

Direct NeTS sampling of nuclear graphite $S(α, β, T)$ in Serpent

For advanced reactor applications, Neural Thermal Scattering (NeTS) modules were developed to predict the thermal scattering law (TSL or $S(α, β, T)$) of a nuclear graphite neutron moderator. NeTS are multi-layer, feedforward artificial neural networks, which act as universal function approximators designed for TSL datasets. In this case, a 4-layer neural network with 164 neurons per layer is trained using FLASSH evaluated data in PyTorch and serialized as a torchscript dictionary to predict $S(α, β, T)$ on-the-fly. Relative, absolute and maximum percent deviations of NeTS from File 7 data generated using the FLASSH code are on the order of 0.01%, 0.1% and 1%, respectively, with low inference latencies of 0.000172 s per $S(α, β, T)$ at a given temperature. Capturing the full dimensionality of possible inelastic neutron-lattice interactions, NeTS functionality is embedded in the Serpent Monte Carlo code, where $S(α, β, T)_{NeTS}$ sampling is conducted on-the-fly and compared to ACE look-up-tables for predicting TREAT criticality. k-eff differences between sampling algorithms of 6 pcm are observed and are within the order of Monte Carlo uncertainty. Compared to discrete and continuous-energy ACE files (30 MB and 131 MB per temperature), the NeTS format is on the order of 200–300 kB for a continuous-temperature, interpolation-free representation of $S(α, β, T)$ and cross sections. NeTS-in-Serpent runtimes comparable with ACE look-up tables are achieved by scaling NeTS for high performance computing architectures with hybrid OpenMP + MPI parallelization. This work validates a novel, self-contained reactor physics framework for predictive cross sections, and demonstrates a general methodology for embedding modern machine learning libraries within existing neutronic analysis frameworks.

Nuclear Criticality Safety Program (NCSP)↗
DOE OSTI2012

Magnetic rogue wave in a perpendicular anisotropic ferromagnetic nanowire with spin-transfer torque

We present the current controlled motion of a dynamic soliton embedded in spin wave background in ferromagnetic nanowire. With the stronger breather character we get the novel magnetic rogue wave and clarify its formation mechanism. The generation of magnetic rogue wave mainly arises from the accumulation of energy and magnons toward to its central part. We also observe that the spin-polarized current can control the exchange rate of magnons between the envelope soliton and the background, and the critical current condition is obtained analytically. Even more interesting is that the spin-transfer torque plays the completely opposite role for the cases below and above the critical value. - Highlights: Black-Right-Pointing-Pointer We get the current controlled motion of a dynamic soliton embedded in spin wave background. Black-Right-Pointing-Pointer We get the novel magnetic rogue wave and clarify its formation mechanism. Black-Right-Pointing-Pointer The generation of magnetic rogue wave arises from the accumulation of energy and magnons. Black-Right-Pointing-Pointer The spin-polarized current controls exchange rate of magnons between the envelope soliton and the background. Black-Right-Pointing-Pointer The spin-transfer torque plays the completely opposite role below and above the critical value.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

Compact submanifolds supporting singular interactions

A quantum particle moving under the influence of singular interactions on embedded surfaces furnish an interesting example from the spectral point of view. In these problems, the possible occurrence of a bound-state is perhaps the most important aspect. Such systems can be introduced as quadratic forms and generically they do not require renormalization. Yet an alternative path through the resolvent is also beneficial to study various properties. In the present work, we address these issues for compact surfaces embedded in a class of ambient manifolds. We discover that there is an exact bound state solution written in terms of the heat kernel of the ambient manifold for a range of coupling strengths. Moreover, we develop techniques to estimate bounds on the ground state energy when several surfaces, each of which admits a bound state solution, coexist. -- Highlights: •Schrödinger operator with singular interactions supported on compact submanifolds. •Exact bound-state solution in terms of the heat kernel of the ambient manifold. •Generalization of the variational approach to a collection of submanifolds. •Existence of a lower bound for a unique ground state energy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗