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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Thermally stable voltage-controlled perpendicular magnetic anisotropy in Mo|CoFeB|MgO structures

We study voltage-controlled magnetic anisotropy (VCMA) and other magnetic properties in annealed Mo|CoFeB|MgO layered structures. The interfacial perpendicular magnetic anisotropy (PMA) is observed to increase with annealing over the studied temperature range, and a VCMA coefficient of about 40 fJ/V-m is sustained after annealing at temperatures as high as 430 °C. Ab initio electronic structure calculations of interfacial PMA as a function of strain further show that strain relaxation may lead to the increase of interfacial PMA at higher annealing temperatures. Measurements also show that there is no significant VCMA and interfacial PMA dependence on the CoFeB thickness over the studied range, which illustrates the interfacial origin of the anisotropy and its voltage dependence, i.e., the VCMA effect. The high thermal annealing stability of Mo|CoFeB|MgO structures makes them compatible with advanced CMOS back-end-of-line processes, and will be important for integration of magnetoelectric random access memory into on-chip embedded applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

C 60 -induced Devil's Staircase transformation on a Pb/Si(111) wetting layer

Density functional theory is used to study structural energetics of Pb vacancy cluster formation on C 60 /Pb/Si(111) to explain the unusually fast and error-free transformations between the “Devil's Staircase” (DS) phases on the Pb/Si(111) wetting layer at low temperature (~110K). The formation energies of vacancy clusters are calculated in C 60 /Pb/Si(111) as Pb atoms are progressively ejected from the initial dense Pb wetting layer. Vacancy clusters larger than five Pb atoms are found to be stable with seven being the most stable, while vacancy clusters smaller than five are highly unstable, which agrees well with the observed ejection rate of ~5 Pb atoms per C 60 . Furthermore, the high energy cost (~0.8 eV) for the small vacancy clusters to form indicates convincingly that the unusually fast transformation observed experimentally between the DS phases, upon C 60 adsorption at low temperature, cannot be the result of single-atom random walk diffusion but of correlated multi-atom processes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Diffusive mixing and Tsallis entropy

Brownian motion, the classical diffusive process, maximizes the Boltzmann-Gibbs entropy. The Tsallis q-entropy, which is non-additive, was developed as an alternative to the classical entropy for systems which are non-ergodic. A generalization of Brownian motion is provided that maximizes the Tsallis entropy rather than the Boltzmann-Gibbs entropy. This process is driven by a Brownian measure with a random diffusion coefficient. In addition, the distribution of this coefficient is derived as a function of q for 1 < q < 3. Applications to transport in porous media are considered.

58 GEOSCIENCES↗
DOE OSTI2021

Exploring Sensitivity of ICF Outputs to Design Parameters in Experiments Using Machine Learning

We report building a sustainable burn platform in inertial confinement fusion (ICF) requires an understanding of the complex coupling of physical processes and the effects that key experimental design changes have on implosion performance. While simulation codes are used to model ICF implosions, incomplete physics and the need for approximations deteriorate their predictive capability. Identification of relationships between controllable design inputs and measurable outcomes can help guide the future design of experiments and development of simulation codes, which can potentially improve the accuracy of the computational models used to simulate ICF implosions. In this article, we leverage developments in machine learning (ML) and methods for ML feature importance/sensitivity analysis to identify complex relationships in ways that are difficult to process using expert judgment alone. We present work using random forest (RF) regression for prediction of yield, velocity, and other experimental outcomes given a suite of design parameters, along with an assessment of important relationships and uncertainties in the prediction model. We show that RF models are capable of learning and predicting on ICF experimental data with high accuracy, and we extract feature importance metrics that provide insight into the physical significance of different controllable design inputs for various ICF design configurations. These results can be used to augment expert intuition and simulation results for optimal design of future ICF experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Kernelized Generalized Likelihood Ratio Test for Spectrum Sensing in Cognitive Radio

Spectrum sensing in next-generation wireless radio networks is considered a key technology to overcome the problem of spectrum scarcity. Unfortunately, many approaches to spectrum sensing do not work well in low signal-to-noise ratio (SNR) environments. This paper proposes and analyzes a new algorithm named kernelized generalized likelihood ratio test (KGLRT) for spectrum sensing in cognitive radio systems to overcome this problem. Effectively, KGLRT uses a nonlinear kernel to map input data onto a high-dimensional feature space; then, the widely accepted (linear) generalized likelihood ratio test is used for hypothesis testing. This new algorithm gives a gain of 4 dB in SNR over its linear counterpart. A theoretical analysis for this algorithm is given for the first time and is shown analogous to algorithms used in image signal processing. The detection metrics are found to be concentrated random variables; furthermore, the probability distributions of the detection metrics are proved to follow the F -distributions, which agree with the results obtained using the concentration inequality. The analytical thresholds are derived for target false-alarm probabilities. Here, the thresholds are independent of noise power; thus, the proposed algorithm can overcome noise uncertainty issues at very low SNR levels. Simulations validate the theoretical results.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Phase-change heterostructure enables ultralow noise and drift for memory operation

Artificial intelligence and other data-intensive applications have escalated the demand for data storage and processing. New computing devices, such as phase-change random access memory (PCRAM)–based neuro-inspired devices, are promising options for breaking the von Neumann barrier by unifying storage with computing in memory cells. However, current PCRAM devices have considerable noise and drift in electrical resistance that erodes the precision and consistency of these devices. We designed a phase-change heterostructure (PCH) that consists of alternately stacked phase-change and confinement nanolayers to suppress the noise and drift, allowing reliable iterative RESET and cumulative SET operations for high-performance neuro-inspired computing. Our PCH architecture is amenable to industrial production as an intrinsic materials solution, without complex manufacturing procedure or much increased fabrication cost.

Science & Technology - Other Topics↗
DOE OSTI2014

ANALYSIS OF VARIANCE-BASED MIXED MULTISCALE FINITE ELEMENT METHOD AND APPLICATIONS IN STOCHASTIC TWO-PHASE FLOWS

The stochastic partial differential systems have been widely used to model physical processes, where the inputs involve large uncertainties. Flows in random and heterogeneous porous media is one of the cases where the random inputs (e.g., permeability) are often modeled as a stochastic field with high-dimensional random parameters. To treat the high dimensionality and heterogeneity efficiently, model reduction is employed in both stochastic space and physical space. An analysis of variance (ANOVA)-based mixed multiscale finite element method MsFEM) is developed to decompose the high-dimensional stochastic problem into a set of lower-dimensional stochastic subproblems, which require much less computational complexity and significantly reduce the computational cost in stochastic space, and the mixed MsFEM can capture the heterogeneities on a coarse grid to greatly reduce the computational cost in the spatial domain. In addition, to enhance the efficiency of the traditional ANOVA method, an adaptive ANOVA method based on a new adaptive criterion is developed, where the most active dimensions can be selected to greatly reduce the computational cost before conducting ANOVA decomposition. This novel adaptive criterion is based on variance-decomposition method coupled with sparse-grid probabilistic collocation method or multilevel Monte Carlo method. The advantage of this adaptive criterion lies in its much lower computational overhead for identifying the active dimensions and interactions. A number of numerical examples in two-phase stochastic flows are presented and demonstrate the accuracy and performance of the adaptive ANOVA-based mixed Ms-FEM.

Wei, Jia↗
NASA NTRS1973

Selection of informative parameters of vibroacoustic processes

The problem of selecting informative parameters of vibro-acoustic processes and the construction of apparatus for their determination are discussed. It is assumed that the processes being investigated are structurally uniform and either purely random or contain not very many determinative components.

Koshek, L. N.↗
NASA NTRS1975

Experience gained from computer processing of physical experimental data during the restoration of measured values

The processing stage in which the restored values of the physical parameters are received is described. The following main steps are discussed: estimation of the state of the telemetry data, processing of the calibration data, and determination of the errors in the data; data decommutation and analysis of the structure of measurement cycles for each instrument; decoding, estimates of the reliability of the restored data, and their agreement with the models adopted for the measurement process; and analysis of errors due to deterministic and random factors. A block diagram of the method is presented.

Mamotko, Z. N.↗
NASA NTRS1978

An instability of finite amplitude circularly polarized Alfven waves

A demonstration is presented that a finite-amplitude circularly-polarized Alfven wave is generally unstable in a MHD fluid. The wave decays by a four-wave coupling process in which the daughter waves are forward propagating random density and magnetic fluctuations and a backward-propagating magnetic wave. For parameters typical of the solar corona and the solar wind (thermal to magnetic energy density ratios between 0.1 and 1, and values between 0.1 and 0.9 for the ratio of magnetic energy density of the initial Alfven wave to that of the background magnetic field), large decay rates are found.

Goldstein, M. L.↗
NASA NTRS1986

Discrete-time Markovian-jump linear quadratic optimal control

This paper is concerned with the optimal control of discrete-time linear systems that possess randomly jumping parameters described by finite-state Markov processes. For problems having quadratic costs and perfect observations, the optimal control laws and expected costs-to-go can be precomputed from a set of coupled Riccati-like matrix difference equations. Necessary and sufficient conditions are derived for the existence of optimal constant control laws which stabilize the controlled system as the time horizon becomes infinite, with finite optimal expected cost.

Chizeck, H. J.↗
NASA NTRS1987

Long-wavelength absorption by fractal dust grains

The far-infrared and submillimeter absorption properties of random aggregates of conducting spheres have been studied as a possible source for the long-wavelength absorption of interstellar dust grains. The complex shapes of random aggregates have various fractal dimensions, depending on the process that forms them. The long wavelength absorption versus frequency is affected more by the shape of a conducting grain than by its composition.

Wright, Edward L.↗
NASA NTRS1992

Stochastic stability properties of jump linear systems

Jump linear systems are defined as a family of linear systems with randomly jumping parameters (usually governed by a Markov jump process) and are used to model systems subject to failures or changes in structure. The authors study stochastic stability properties in jump linear systems and the relationship among various moment and sample path stability properties. It is shown that all second moment stability properties are equivalent and are sufficient for almost sure sample path stability, and a testable necessary and sufficient condition for second moment stability is derived. The Lyapunov exponent method for the study of almost sure sample stability is discussed, and a theorem which characterizes the Lyapunov exponents of jump linear systems is presented.

Feng, Xiangbo↗
NASA NTRS1992

Statistical characterization of life drivers for a probabilistic design analysis

This paper discusses the issue of statistical characterization of life drivers for a probabilistic design analysis (PDA) approach to support the conventional deterministic structural design methods that are currently used. The probabilistic approach takes into consideration the modeling inadequacies and uncertainties in many design variables such as loads, environments, and material properties. The importance of the distributional assumption is motivated by illustrating an example where the results differ substantially due to the distribution selected. Different types of distributions are discussed and techniques for estimating the parameters are given. Given this information, procedures are outlined for selecting the appropriate distribution based on the particular type of variable (i.e., dimensional, performance) as well as the information that is available (i.e., test data, engineering analysis). Finally, techniques are given for generating random numbers from these selected distributions within the PDA process.

Fox, Eric P.↗
NASA NTRS1995

A Probabilistic Design Method Applied to Smart Composite Structures

A probabilistic design method is described and demonstrated using a smart composite wing. Probabilistic structural design incorporates naturally occurring uncertainties including those in constituent (fiber/matrix) material properties, fabrication variables, structure geometry and control-related parameters. Probabilistic sensitivity factors are computed to identify those parameters that have a great influence on a specific structural reliability. Two performance criteria are used to demonstrate this design methodology. The first criterion requires that the actuated angle at the wing tip be bounded by upper and lower limits at a specified reliability. The second criterion requires that the probability of ply damage due to random impact load be smaller than an assigned value. When the relationship between reliability improvement and the sensitivity factors is assessed, the results show that a reduction in the scatter of the random variable with the largest sensitivity factor (absolute value) provides the lowest failure probability. An increase in the mean of the random variable with a negative sensitivity factor will reduce the failure probability. Therefore, the design can be improved by controlling or selecting distribution parameters associated with random variables. This can be implemented during the manufacturing process to obtain maximum benefit with minimum alterations.

Shiao, Michael C.↗
NASA NTRS1995

Some wave-particle effects on large-scale Alfven wave propagation and damping

Phase mixing can reduce greatly the torsional Alfven wave's dissipation length for propagation in complex magnetic field-line geometries. This phase mixing causes significant energy transfers from large to small scales where a conversion from ordered wave energy into a particle kinetic form occurs. This conversion during its initial stages is an entropy conserving process well described by Vlasov theory, Nonlinear stages of wave-particle resonance, particle trapping, and collisional resistivity are often invoked as processes eventually responsible for converting ordered wave motions into random thermal motion. Strictly speaking, this entropy producing phase cannot be described within Vlasov theory, and the large-scale effects of these microscopic events resides at the difficult frontier between generalized fluid and kinetic theories. We attempt to describe certain aspects of such resonances within the framework of fluid theory focusing on torsional Alfven wave energy transport and deposition within flux tubes.

Siregar, E.↗
NASA NTRS1995

Field lines and magnetic surfaces in a two-component slab/2D model of interplanetary magnetic fluctuations

A two-component model for the spectrum of interplanetary magnetic fluctuations was proposed on the basis of ISEE observations, and has found an intriguing level of application in other solar wind studies. The model fluctuations consist of a fraction of 'slab' fluctuations, varying only in the direction parallel to the locally uniform mean magnetic field B(0) and a complement of 2D (two-dimensional) fluctuations that vary in the directions transverse to B(0). We have developed an spectral method computational algorithm for computing the magnetic flux surfaces (flux tubes) associated with the composite model, based upon a precise analogy with equations for ideal transport of a passive scalar in planar two dimensional geometry. Visualization of various composite models will be presented, including the 80 percent 2D/ 20 percent slab model with delta B/B(0) approximately equals 1 and a minus 5/3 spectral law, that is thought to approximately represent a snapshot of solar wind turbulence. Characteristically, the visualizations show that flux tubes, even when defined as regular on some plane, shred and disperse rapidly as they are viewed along the parallel direction. This diffusive process, which generalizes the standard picture of field line random walk, will be discussed in detail. Evidently, the traditional picture that flux tubes randomize like strands of spaghetti with a uniform tangle along the axial direction is in need of modification.

Matthaeus, W. H.↗
DOE OSTI2019

Pump-probe ghost imaging with SASE FELs

In this paper we propose a new approach to measuring ultrafast dynamics with free-electron lasers (FELs). Ultrafast experiments are among the most promising avenues of research at x-ray FELs, with potential to reveal the chemical dynamics of charge separation, conical intersection crossing, and biologically mediated reactions. Pump-probe scanning is the standard approach to measure dynamics at x-ray FELs, but at the shortest time scales, and particularly for x-ray pump, x-ray probe experiments, the scans require challenging beam setups and can introduce systematic errors. Here we propose an alternative approach using the randomness of the self-amplified spontaneous emission (SASE) process to drive many simultaneous pump-probe experiments on each shot. Measuring the fluctuations in the incident beam’s time profile on a shot-to-shot basis enables reconstruction of ultrafast dynamics down to the coherence length of the FEL without the need for pump-probe scans. Due to similarity to ghost imaging, in which spatial properties are reconstructed by measuring the incident probe’s transverse properties, we call this ``pump-probe ghost imaging" (PPGI). In this paper we describe the method and simulate an example experiment. We also describe an alternative implementation that uses only spectral measurements, avoiding the need for direct time-domain diagnostics, and extending the method to the attosecond regime.

Ratner, Daniel Fried↗