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At least 1,567 records · Page 87

All sources NASA NTRS DOE OSTI

DOE OSTI2013

COSMIC DUST AGGREGATION WITH STOCHASTIC CHARGING

The coagulation of cosmic dust grains is a fundamental process which takes place in astrophysical environments, such as presolar nebulae and circumstellar and protoplanetary disks. Cosmic dust grains can become charged through interaction with their plasma environment or other processes, and the resultant electrostatic force between dust grains can strongly affect their coagulation rate. Since ions and electrons are collected on the surface of the dust grain at random time intervals, the electrical charge of a dust grain experiences stochastic fluctuations. In this study, a set of stochastic differential equations is developed to model these fluctuations over the surface of an irregularly shaped aggregate. Then, employing the data produced, the influence of the charge fluctuations on the coagulation process and the physical characteristics of the aggregates formed is examined. It is shown that dust with small charges (due to the small size of the dust grains or a tenuous plasma environment) is affected most strongly.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Effects of carbon nanotubes on twin and texture evolution of magnesium matrix composite during compression process

Highlights: • The CNTs existing at grain boundaries lead to stress concentration, and stimulate the formation of twins. • Crystal rotation and non-basal slip alternately dominate the deformation of the CNTs/Mg composite. • The texture changes from random texture to strong basal texture, strong non-basal texture at the three corresponding stages. • Crystal rotation and non-basal slip system are the main toughening mechanisms of the CNTs/Mg composite. - Abstract: A compression test is performed to investigate the effects of carbon nanotubes (CNTs) on twin and texture evolution of the 1.0 wt.% CNTs reinforced magnesium matrix (CNTs/Mg) composite. The compression process consists of elastic, yield and hardening stages, and the number of twin significantly increases at the yield stage. During the compression process, the crystal rotation and non-basal slip caused by twin shear alternately dominate the deformation of the 1.0 wt.% CNTs/Mg composite. The CNTs existing at grain boundaries lead to stress concentration, and the stress concentration stimulates the formation of twins at the yield stage. The formed twins interact with dislocations, result in crystal rotation and promotion of the non-basal slip system at the hardening stage under the effect of twin shear, thus, improve the toughness of the CNTs/Mg composite.

36 MATERIALS SCIENCE↗

NASA NTRS2011

Cloud Macroscopic Organization: Order Emerging from Randomness

Clouds play a central role in many aspects of the climate system and their forms and shapes are remarkably diverse. Appropriate representation of clouds in climate models is a major challenge because cloud processes span at least eight orders of magnitude in spatial scales. Here we show that there exists order in cloud size distribution of low-level clouds, and that it follows a power-law distribution with exponent gamma close to 2. gamma is insensitive to yearly variations in environmental conditions, but has regional variations and land-ocean contrasts. More importantly, we demonstrate this self-organizing behavior of clouds emerges naturally from a complex network model with simple, physical organizing principles: random clumping and merging. We also demonstrate symmetry between clear and cloudy skies in terms of macroscopic organization because of similar fundamental underlying organizing principles. The order in the apparently complex cloud-clear field thus has its root in random local interactions. Studying cloud organization with complex network models is an attractive new approach that has wide applications in climate science. We also propose a concept of cloud statistic mechanics approach. This approach is fully complementary to deterministic models, and the two approaches provide a powerful framework to meet the challenge of representing clouds in our climate models when working in tandem.

Yuan, Tianle↗

NASA NTRS1999

Benefits of Force Limiting Vibration Testing

Force limited random vibration testing is used at NASA John Glenn Research Center (formerly NASA Lewis Research Center) for qualifying aerospace hardware for flight. The benefit of force limiting testing is that it limits overtesting of flight hardware, by controlling input force and acceleration from the shaker (dual control) to the test article. The purpose of force limiting is to replicate the test article resonant response for the actual flight mounting condition. The force limiting testing technology has been implemented at the Jet Propulsion Laboratory for the past 10 years on various spacecraft testing programs. The Cassini mission to Saturn, most notably, utilized force limiting vibration testing as part of the spacecraft system level vibration testing. NASA John Glenn Research Center is responsible for microgravity combustion and fluid science research on the Shuttle and the International Space Station. Qualification testing of delicate and vibration sensitive science instrumentation is particularly challenging to successfully qualify for flight. In order to facilitate the testing process, force limiting has been implemented to minimize overtesting of flight hardware. This paper will address recent flight camera testing (qualification random vibration and strength testing) for the Combustion Module-2 mission and the impact of Semi-empirical Method force limits.

McNelis, Mark E.↗

DOE OSTI2020

Binary pseudorandom array test standard optimized for characterization of large field-of-view optical interferometers

Recently, a technique for calibrating the modulation transfer function (MTF) of a broad variety of metrology instrumentation has been demonstrated. This technique is based on test samples structured as one-dimensional binary pseudo-random (BPR) sequences and two-dimensional BPR arrays (BPRAs). The inherent power spectral density of BPR gratings (sequences) and arrays has a deterministic white-noise-like character that allows direct determination of the MTF with uniform sensitivity over the entire spatial frequency range and field-of-view of an instrument. As such, the BPR samples satisfy the characteristics of a test standard: functionality, ease of specification and fabrication, reproducibility, and low sensitivity to manufacturing error. Here we discuss our recent developments directed to the optimization of the sample design, fabrication, application, and data processing procedures, suitable for thorough characterization of large aperture optical interferometers. Compared with the previous coded-aperture based design, the improved, 'highly randomized' BPRA pattern of the new test standard provides better accuracy and reliability of instrument MTF and aberration characterization, and enables operation optimization of large aperture optical interferometers. We describe the pattern generation algorithm and tests to verify the compliance to desired BPRA topography. The data acquisition and analysis procedures for different applications of the technique are also discussed.

Yashchuk, Valeriy V.↗

NASA NTRS2006

Chance of Necessity: Modeling Origins of Life

The fundamental nature of processes that led to the emergence of life has been a subject of long-standing debate. One view holds that the origin of life is an event governed by chance, and the result of so many random events is unpredictable. This view was eloquently expressed by Jacques Monod in his book Chance or Necessity. In an alternative view, the origin of life is considered a deterministic event. Its details need not be deterministic in every respect, but the overall behavior is predictable. A corollary to the deterministic view is that the emergence of life must have been determined primarily by universal chemistry and biochemistry rather than by subtle details of environmental conditions. In my lecture I will explore two different paradigms for the emergence of life and discuss their implications for predictability and universality of life-forming processes. The dominant approach is that the origin of life was guided by information stored in nucleic acids (the RNA World hypothesis). In this view, selection of improved combinations of nucleic acids obtained through random mutations drove evolution of biological systems from their conception. An alternative hypothesis states that the formation of protocellular metabolism was driven by non-genomic processes. Even though these processes were highly stochastic the outcome was largely deterministic, strongly constrained by laws of chemistry. I will argue that self-replication of macromolecules was not required at the early stages of evolution; the reproduction of cellular functions alone was sufficient for self-maintenance of protocells. In fact, the precise transfer of information between successive generations of the earliest protocells was unnecessary and could have impeded the discovery of cellular metabolism. I will also show that such concepts as speciation and fitness to the environment, developed in the context of genomic evolution also hold in the absence of a genome.

Pohorille, Andrew↗

DOE OSTI2015

Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies

Sampling orthogonal polynomial bases via Monte Carlo is of interest for uncertainty quantification of models with random inputs, using Polynomial Chaos (PC) expansions. It is known that bounding a probabilistic parameter, referred to as coherence, yields a bound on the number of samples necessary to identify coefficients in a sparse PC expansion via solution to an ℓ{sub 1}-minimization problem. Utilizing results for orthogonal polynomials, we bound the coherence parameter for polynomials of Hermite and Legendre type under their respective natural sampling distribution. In both polynomial bases we identify an importance sampling distribution which yields a bound with weaker dependence on the order of the approximation. For more general orthonormal bases, we propose the coherence-optimal sampling: a Markov Chain Monte Carlo sampling, which directly uses the basis functions under consideration to achieve a statistical optimality among all sampling schemes with identical support. We demonstrate these different sampling strategies numerically in both high-order and high-dimensional, manufactured PC expansions. In addition, the quality of each sampling method is compared in the identification of solutions to two differential equations, one with a high-dimensional random input and the other with a high-order PC expansion. In both cases, the coherence-optimal sampling scheme leads to similar or considerably improved accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

A 3D Ginibre Point Field

We introduce a family of three-dimensional random point fields using the concept of the quaternion determinant. The kernel of each field is an n-dimensional orthogonal projection on a linear space of quaternionic polynomials. We find explicit formulas for the basis of the orthogonal quaternion polynomials and for the kernel of the projection. For number of particles n→∞, we calculate the scaling limits of the point field in the bulk and at the center of coordinates. We compare our construction with the previously introduced Fermi-sphere point field process.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Analysis of the Space Propulsion System Problem Using RAVEN

This paper presents the solution of the space propulsion problem using a PRA code currently under development at Idaho National Laboratory (INL). RAVEN (Reactor Analysis and Virtual control ENviroment) is a multi-purpose Probabilistic Risk Assessment (PRA) software framework that allows dispatching different functionalities. It is designed to derive and actuate the control logic required to simulate the plant control system and operator actions (guided procedures) and to perform both Monte- Carlo sampling of random distributed events and Event Tree based analysis. In order to facilitate the input/output handling, a Graphical User Interface (GUI) and a post-processing data-mining module are available. RAVEN allows also to interface with several numerical codes such as RELAP5 and RELAP-7 and ad-hoc system simulators. For the space propulsion system problem, an ad-hoc simulator has been developed and written in python language and then interfaced to RAVEN. Such simulator fully models both deterministic (e.g., system dynamics and interactions between system components) and stochastic behaviors (i.e., failures of components/systems such as distribution lines and thrusters). Stochastic analysis is performed using random sampling based methodologies (i.e., Monte-Carlo). Such analysis is accomplished to determine both the reliability of the space propulsion system and to propagate the uncertainties associated to a specific set of parameters. As also indicated in the scope of the benchmark problem, the results generated by the stochastic analysis are used to generate risk-informed insights such as conditions under witch different strategy can be followed.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Single trap dynamics in electrolyte-gated Si-nanowire field effect transistors

Liquid-gated silicon nanowire (NW) field effect transistors (FETs) are fabricated and their transport and dynamic properties are investigated experimentally and theoretically. Random telegraph signal (RTS) fluctuations were registered in the nanolength channel FETs and used for the experimental and theoretical analysis of transport properties. The drain current and the carrier interaction processes with a single trap are analyzed using a quantum-mechanical evaluation of carrier distribution in the channel and also a classical evaluation. Both approaches are applied to treat the experimental data and to define an appropriate solution for describing the drain current behavior influenced by single trap resulting in RTS fluctuations in the Si NW FETs. It is shown that quantization and tunneling effects explain the behavior of the electron capture time on the single trap. Based on the experimental data, parameters of the single trap were determined. The trap is located at a distance of about 2 nm from the interface Si/SiO{sub 2} and has a repulsive character. The theory of dynamic processes in liquid-gated Si NW FET put forward here is in good agreement with experimental observations of transport in the structures and highlights the importance of quantization in carrier distribution for analyzing dynamic processes in the nanostructures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2018

Quantitative Boltzmann–Gibbs Principles via Orthogonal Polynomial Duality

We study fluctuation fields of orthogonal polynomials in the context of particle systems with duality. We thereby obtain a systematic orthogonal decomposition of the fluctuation fields of local functions, where the order of every term can be quantified. This implies a quantitative generalization of the Boltzmann–Gibbs principle. In the context of independent random walkers, we complete this program, including also fluctuation fields in non-stationary context (local equilibrium). For other interacting particle systems with duality such as the symmetric exclusion process, similar results can be obtained, under precise conditions on the n particle dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2013

Estimating anisotropic diffusion of neutrons near the boundary of a pebble bed random system

Due to the arrangement of the pebbles in a Pebble Bed Reactor (PBR) core, if a neutron is located close to a boundary wall, its path length probability distribution function in directions of flight parallel to the wall is significantly different than in other directions. Hence, anisotropic diffusion of neutrons near the boundaries arises. We describe an analysis of neutron transport in a simplified 3-D pebble bed random system, in which we investigate the anisotropic diffusion of neutrons born near one of the system's boundary walls. While this simplified system does not model the actual physical process that takes place near the boundaries of a PBR core, the present work paves the road to a formulation that may enable more accurate diffusion simulations of such problems to be performed in the future. Monte Carlo codes have been developed for (i) deriving realizations of the 3-D random system, and (ii) performing 3-D neutron transport inside the heterogeneous model; numerical results are presented for three different choices of parameters. These numerical results are used to assess the accuracy of estimates for the mean-squared displacement of neutrons obtained with the diffusion approximations of the Atomic Mix Model and of the recently introduced [1] Non-Classical Theory with angular-dependent path length distribution. The Non-Classical Theory makes use of a Generalized Linear Boltzmann Equation in which the locations of the scattering centers in the system are correlated and the distance to collision is not exponentially distributed. We show that the results predicted using the Non-Classical Theory successfully model the anisotropic behavior of the neutrons in the random system, and more closely agree with experiment than the results predicted by the Atomic Mix Model. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2016

DeepSAT: A Deep Learning Approach to Tree-Cover Delineation in 1-m NAIP Imagery for the Continental United States

High resolution tree cover classification maps are needed to increase the accuracy of current land ecosystem and climate model outputs. Limited studies are in place that demonstrates the state-of-the-art in deriving very high resolution (VHR) tree cover products. In addition, most methods heavily rely on commercial softwares that are difficult to scale given the region of study (e.g. continents to globe). Complexities in present approaches relate to (a) scalability of the algorithm, (b) large image data processing (compute and memory intensive), (c) computational cost, (d) massively parallel architecture, and (e) machine learning automation. In addition, VHR satellite datasets are of the order of terabytes and features extracted from these datasets are of the order of petabytes. In our present study, we have acquired the National Agriculture Imagery Program (NAIP) dataset for the Continental United States at a spatial resolution of 1-m. This data comes as image tiles (a total of quarter million image scenes with ~60 million pixels) and has a total size of ~65 terabytes for a single acquisition. Features extracted from the entire dataset would amount to ~8-10 petabytes. In our proposed approach, we have implemented a novel semi-automated machine learning algorithm rooted on the principles of "deep learning" to delineate the percentage of tree cover. Using the NASA Earth Exchange (NEX) initiative, we have developed an end-to-end architecture by integrating a segmentation module based on Statistical Region Merging, a classification algorithm using Deep Belief Network and a structured prediction algorithm using Conditional Random Fields to integrate the results from the segmentation and classification modules to create per-pixel class labels. The training process is scaled up using the power of GPUs and the prediction is scaled to quarter million NAIP tiles spanning the whole of Continental United States using the NEX HPC supercomputing cluster. An initial pilot over the state of California spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles has produced true positive rates of around 88 percent for fragmented forests and 74 percent for urban tree cover areas, with false positive rates lower than 2 percent for both landscapes.

Imagery↗

DOE OSTI2018

β-delayed Fission in r-process Nucleosynthesis

In this work, we present β-delayed neutron emission and β-delayed fission (βdf) calculations for heavy, neutron-rich nuclei using the coupled Quasi-Particle Random Phase Approximation plus Hauser-Feshbach (QRPA+HF) approach. From the initial population of a compound nucleus after β-decay, we follow the statistical decay, taking into account competition between neutrons, γ-rays, and fission. We find a region of the chart of nuclides where the probability of βdf is ~100%, which likely prevents the production of superheavy elements in nature. For a subset of nuclei near the neutron dripline, neutron multiplicity and the probability of fission are both large, leading to the intriguing possibility of multi-chance βdf, a decay mode for extremely neutron-rich heavy nuclei. In this decay mode, β-decay can be followed by multiple neutron emission, leading to subsequent daughter generations that each have a probability to fission. We explore the impact of βdf in rapid neutron-capture process (r-process) nucleosynthesis in the tidal ejecta of a neutron star–neutron star merger and show that it is a key fission channel that shapes the final abundances near the second r-process peak.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Numerical models for the prediction of failure for multilayer fusion Al-alloy sheets

Initiation and propagation of cracks in monolithic and multi-layer aluminum alloys, called “Fusion”, is investigated. 2D plane strain finite element simulations are performed to model deformation due to bending and to predict failure. For this purpose, fracture strains are measured based on microscopic pictures of Nakajima specimens. In addition to, micro-structure of materials is taken into account by introducing a random grain distribution over the sheet thickness as well as a random distribution of the measured yield curve. It is shown that the performed experiments and the introduced FE-Model are appropriate methods to highlight the advantages of the Fusion material, especially for bending processes.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Influence of differential speed rolling ratio on the ridging behavior of ultra purified 17%Cr ferritic stainless steel

Highlights: • Differential rolling process improves ridging resistance of ferritic stainless steel. • Texture orientation inhomogeneity were attributed to non-uniform deformation. • Shear bands results in homogeneous deformation and recrystallization nucleation. • Uniform recrystallization grains and random orientation grains were obtained. - Abstract: The effect of the differential speed rolling on the ridging resistance and the crystallographic texture evolution of ultra purified 17%Cr ferritic stainless steel was investigated in order to select the optimal procedure for improving the surface quality. In the present study, the three different cold rolling processes were carried out: a conventional cold rolling and two different speed ratios asymmetric rolling. In the conventional cold rolling, the ridging of ferritic stainless steel was pronounced due to the band-like clusters of grains with similar crystallographic orientations. For differential speed rolling, ridging depth decreased and ridging was less pronounced when a higher different speed ratio was applied. The results show that severe ridging is attributed to the presence of band-like clusters of γ-fiber (<111>//ND) oriented grains. The shear bands introduced by differential speed rolling can enhance the nucleation for recrystallization both in grain interiors and grain boundaries, which can fragment the band-like clusters of similar orientation effectively, promoting the random grain orientation and improving surface quality.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Identification and characterization of circular RNAs in rapid atrial pacing dog atrial tissue

Highlights: • Revealed the expression characterization of circRNAs in dog atrial tissue. • Compared differentially expressed circRNAs between atrial fibrillation and control dog. • Found extensive interaction among circRNAs and AF related miRNAs and mRNAs. Circular RNAs (circRNAs) have emerged as novel molecules of interest in gene regulation as other noncoding RNAs, and participating in the process of many diseases. However, the expression and functions of circRNAs in Rapid atrial pacing (RAP) dog atrial tissue still unknown. 12 canines were randomly assigned to control and pacing group. RAP at 500 beats per minute was maintained 14 days in the pacing group. The expression characterization of circRNAs were revealed by high-throughput sequencing. We totally predicted 15,990 circRNAs in dog atrial tissues. Moreover, we found 146 differentially expressed circRNAs between control and RAP dogs. Five circRNAs were selected for subsequent RT-PCR validation, and four circRNAs confirmed with the high throughput sequencing analysis. GO analysis showed that the differentially expressed circRNAs might involve in the process of “structural constituent of cytoskeleton, ion channel activity”. We explored the circRNA-miRNA interaction network, and found extensive interaction among differentially expressed circRNAs and AF related miRNAs and mRNAs. Our work firstly identified the characterization of circRNAs in the dog atrial, and revealed the differentially expressed circRNAs in the RAP dog, this might lay a solid foundation on the function of circRNA in the mechanisms of AF.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Binding kinetics of harmonically confined random walkers

Diffusion-mediated binding of molecules under the influence of discrete spatially confining potentials is a commonly encountered scenario in systems subjected to explicit fields or implicit fields arising from tethering restraints. Here, in this work, we derive analytical expressions for the mean binding time of two random walkers geometrically confined by means of two harmonic potentials in one- and two-dimensional systems, which show excellent agreement with Brownian dynamics simulations. As a demonstration of its utility, we use this theory to maximize the communication speed in existing DNA walkers, obtaining quantitative agreement with previously reported experimental findings. The analytical expressions derived in this paper are broadly applicable to diverse systems, providing ways to characterize communication processes and optimize the rate of signal propagation for sensing and computing applications at the nanoscale.

36 MATERIALS SCIENCE↗