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Results for “Intrinsic computation”

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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Computational approaches to vision

Vision is examined in terms of a computational process, and the competence, structure, and control of computer vision systems are analyzed. Theoretical and experimental data on the formation of a computer vision system are discussed. Consideration is given to early vision, the recovery of intrinsic surface characteristics, higher levels of interpretation, and system integration and control. A computational visual processing model is proposed and its architecture and operation are described. Examples of state-of-the-art vision systems, which include some of the levels of representation and processing mechanisms, are presented.

Barrow, H. G.↗
DOE OSTI2021

Identifying Genomic Islands with Deep Neural Networks

Background Horizontal gene transfer is the main source of adaptability for bacteria, through which genes are obtained from different sources including bacteria, archaea, viruses, and eukaryotes. This process promotes the rapid spread of genetic information across lineages, typically in the form of clusters of genes referred to as genomic islands (GIs). Different types of GIs exist, and are often classified by the content of their cargo genes or their means of integration and mobility. While various computational methods have been devised to detect different types of GIs, no single method is capable of detecting all types. Results We propose a method, which we call Shutter Island, that uses a deep learning model (Inception V3, widely used in computer vision) to detect genomic islands. The intrinsic value of deep learning methods lies in their ability to generalize. Via a technique called transfer learning, the model is pre-trained on a large generic dataset and then re-trained on images that we generate to represent genomic fragments. We demonstrate that this image-based approach generalizes better than the existing tools. Conclusions We used a deep neural network and an image-based approach to detect the most out of the correct GI predictions made by other tools, in addition to making novel GI predictions. The fact that the deep neural network was re-trained on only a limited number of GI datasets and then successfully generalized indicates that this approach could be applied to other problems in the field where data is still lacking or hard to curate.

Computer Vision↗
DOE OSTI2021

A Geometry-Driven Longitudal Topic Model

A simple and scalable framework for longitudinal analysis of Twitter data is developed that combines latent topic models with computational geometric methods. Dimensionality reduction tools from computational geometry are applied to learn the intrinsic manifold on which the latent, temporal topics reside. Then shortest path distances on the manifold are used to link together these topics. The proposed framework permits visualization of the low-dimensional embedding which provides clear interpretation of the complex, high-dimensional trajectories that may exist among latent topics. Practical application of the proposed framework is demonstrated through its ability to capture and effectively visualize natural progression of latent COVID-19 related topics learned from Twitter data. Interpretability of the trajectories is achieved by comparing to real-world events. In addition, the framework permits study of spatial variation in Twitter behavior for learned topics. The analysis demonstrates that the proposed framework is able to capture granular-level impact of COVID-19 on public discussions. We end by arguing that Twitter data, when analyzed within the proposed framework, can serve as a valuable supplementary data stream for COVID-related studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Enhancing the connection between computation and experiments in electrocatalysis

Combining computational and experimental methods is a powerful approach to understand the variables that govern catalyst performance and ultimately design improved materials. However, the effectiveness of this approach rests on the strength of the relationships between calculated parameters and experimental measurements. These relationships are complicated by the intricacy and dynamic behaviour of catalytic active sites, and by the non-trivial relationship between calculated reaction energetics and observed rates. In this Perspective, we highlight opportunities to enhance the connection between computation and experiment in electrocatalysis. These include measuring the intrinsic kinetic behaviour of catalysts, creating precise models for the active site and its environment, and forming clear relationships between calculated reaction energetics and observed rates. As experimental and computational methods continue to become more powerful, clear connections between the two will maximize their utility to guide the design of efficient and selective electrocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Uncovering acoustic signatures of pore formation in laser powder bed fusion

Abstract We present a machine learning workflow to discover signatures in acoustic measurements that can be utilized to create a low-dimensional model to accurately predict the location of keyhole pores formed during additive manufacturing processes. Acoustic measurements were sampled at 100 kHz during single-layer laser powder bed fusion (LPBF) experiments, and spatio-temporal registration of pore locations was obtained from post-build radiography. Power spectral density (PSD) estimates of the acoustic data were then decomposed using non-negative matrix factorization with custom $$\varvec{k}$$ k -means clustering (NMF $$\varvec{k}$$ k ) to learn the underlying spectral patterns associated with pore formation. NMF $$\varvec{k}$$ k returned a library of basis signals and matching coefficients to blindly construct a feature space based on the PSD estimates in an optimized fashion. Moreover, the NMF $$\varvec{k}$$ k decomposition led to the development of computationally inexpensive machine learning models which are capable of quickly and accurately identifying pore formation with classification accuracy of supervised and unsupervised label learning greater than 95% and 90%, respectively. The intrinsic data compression of NMF k , the relatively light computational cost of the machine learning workflow, and the high classification accuracy makes the proposed workflow an attractive candidate for edge computing toward in-situ keyhole pore prediction in LPBF.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Preorganized Electric Field Leads to Minimal Geometrical Reorientation in the Catalytic Reaction of Ketosteroid Isomerase

Electrostatic interactions play a pivotal role in enzymatic catalysis and are increasingly modeled explicitly in computational enzyme design; nevertheless, they are challenging to measure experimentally. Using vibrational Stark effect (VSE) spectroscopy, we have measured electric fields inside the active site of the enzyme ketosteroid isomerase (KSI). These studies have shown that these fields can be unusually large, but it has been unclear to what extent they specifically stabilize the transition state (TS) relative to a ground state (GS). In the following, we use crystallography and computational modeling to show that KSI’s intrinsic electric field is nearly perfectly oriented to stabilize the geometry of its reaction’s TS. Moreover, we find that this electric field adjusts the orientation of its substrate in the ground state so that the substrate needs to only undergo minimal structural changes upon activation to its TS. This work provides evidence that the active site electric field in KSI is preorganized to facilitate catalysis and provides a template for how electrostatic preorganization can be measured in enzymatic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Dipole-Dipole Frequency Shifts in Multilevel Atoms

Dipole-dipole interactions lead to frequency shifts that are expected to limit the performance of next-generation atomic clocks. In this work, we compute dipolar frequency shifts accounting for the intrinsic atomic multilevel structure in standard Ramsey spectroscopy. When interrogating the transitions featuring the smallest Clebsch-Gordan coefficients, we find that a simplified two-level treatment becomes inappropriate, even in the presence of large Zeeman shifts. Further, for these cases, we show a net suppression of dipolar frequency shifts and the emergence of dominant nonclassical effects for experimentally relevant parameters. Our findings are pertinent to current generations of optical lattice and optical tweezer clocks, opening a way to further increase their current accuracy, and thus their potential to probe fundamental and many-body physics.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1975

Galactic evolution. I - Single-zone models

The two basic approaches of physical theory required to calculate the evolution of a galactic system are considered, taking into account stellar evolution theory and the dynamics of a gas-star system. Attention is given to intrinsic (stellar) physics, extrinsic (dynamical) physics, and computations concerning the fractionation of an initial mass of gas into stars. The characteristics of a 'standard' model and its variants are discussed along with the results obtained with the aid of these models.

Thuan, T. X.↗
NASA NTRS1979

Simplified and refined finite element approaches for determining stresses and internal forces in geometrically nonlinear structural analysis

Two methods for determining stresses and internal forces in geometrically nonlinear structural analysis are presented. The simplified approach uses the mid-deformed structural position to evaluate strains when rigid body rotation is present. The important feature of this approach is that it can easily be used with a general-purpose finite-element computer program. The refined approach uses element intrinsic or corotational coordinates and a geometric transformation to determine element strains from joint displacements. Results are presented which demonstrate the capabilities of these potentially useful approaches for geometrically nonlinear structural analysis.

Robinson, J. C.↗
NASA NTRS1989

The effect of hot gas in early-type galaxies on the cosmic microwave background

The effects on the cosmic microwave background which are due to Compton scattering by the hot gas contained in early-type galaxies (the Sunyaev-Zeldovich effect) are computed. Using the known properties of the gas deduced from X-ray observations, it is found that the fractional attenuation DeltaT/T at the center of a gas-rich galaxy is likely to be less than 10 to the -5th, which is just below current limits of detectability. A distribution function is derived for the attenuation which is due to a population of early-type galaxies out to some redshift and the expected rms fluctuations in the background on subarcmin scales are computed. These fluctuations are comparable to those intrinsic to the microwave background in the 'cold dark matter' scenario on these angular scales, but they fall orders of magnitude below the detection limits and below the level of fluctuations expected from nonlinear density perturbations at the epoch of galaxy formation.

Trester, Jeffrey J.↗
DOE OSTI2025

Silver diamine fluoride differentially affects dentin and hypomineralized enamel permeabilities

OBJECTIVES: To investigate the physicochemical effect of silver diamine fluoride (SDF) by correlating permeability with mineral density and elemental composition of hypomineralized enamel and carious dentin. METHODS: Enamel and dentin from human carious primary teeth with and without SDF treatment in-vivo, and hypomineralized enamel from permanent molars with and without SDF treatment in-vitro were scanned using micro X-ray computed tomography. Spatial maps of biometals (calcium, zinc), phosphorus, and silver were generated using X-ray fluorescence microprobe. Permeabilities were computed using Porous Microstructure Analysis software. RESULTS: The intrinsic permeability of SDF-treated carious dentin was 14.3 % lower than untreated sound dentin (6.39e-15 ± 3.01e-15 m² vs 7.46e-15 ± 1.82e-15 m²; P < 0.0001), while untreated carious dentin was 98.4 % higher (1.48e-14 ± 7.11e-15 m²; P < 0.0001). SDF-treated and untreated transparent dentin showed similar reduced permeabilities (75.6 % and 78.4 % lower than untreated sound dentin, respectively; P = 0.93). Severely hypomineralized enamel showed permeability reaching 108.1 % of adjacent sound dentin (5.71e-15 ± 2.04e-15 m² vs 5.28e-15 ± 1.30e-15 m²; P = 0.1409) and was significantly higher than mildly hypomineralized enamel (1.39e-15 ± 1.04e-15 m²; P < 0.0001). SDF treatment did not significantly impact the permeability of severely hypomineralized enamel (12.4 % reduction; P = 0.07). Principal component regression identified Zn level as a significant effector of tissue permeabilities in carious primary teeth (P < 0.0001). SIGNIFICANCE: This study introduces a computational method to measure dental tissue permeability, and demonstrates that SDF significantly reduces permeability in carious dentin but not intact hypomineralized enamel. The study reveals biometal Zn localization can alter dentin and enamel permeabilities, providing new insights into pathobiological mechanisms underlying caries and hypomineralization.

Chou, Conrad↗
DOE OSTI2022

Topological Superconductivity Based on Antisymmetric Spin–Orbit Coupling

Topological superconductivity (TSC) has drawn much attention for its fundamental interest and application in quantum computation. An outstanding challenge is the lack of intrinsic TSC materials with a p-wave pairing gap, which has led to the development of an effective p-wave theory of coupling s-wave gap with Rashba spin–orbit coupling (RSOC). However, the RSOC-strict mechanism and materials pose still both fundamental and practical limitations. Here, we generalize this theory to antisymmetric SOC (ASOC). Using k·p perturbation theory, we demonstrate that 2D crystals, with point groups of C 2 , C 4 , C 6 , C 2v , C 4v , C 6v , D 2 , D 4 , D 6 , S 4 , or D 2d , can all facilitate the desired ASOC. Remarkably, this enables us to discover 314 TSC candidates by screening 2D material databases, which are further confirmed by first-principles calculations of Majorana boundary modes and the topological invariant of the superconducting gap. As a result, our work fundamentally enriches TSC theory and greatly expands the classes of TSC materials for experimental exploration.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Assessing Carrier Mobility, Dopability, and Defect Tolerance in the Chalcogenide Perovskite Ba Zr S 3

The chalcogenide perovskite Ba Zr S 3 has attracted much attention as a promising solar absorber for thin-film photovoltaics. Here we use first-principles calculations to evaluate its carrier transport and defect properties. We find that Ba Zr S 3 has a phonon-limited electron mobility of 37 cm 2 / V s, which is comparable to that in halide perovskites, but lower hole mobility of 11 cm 2 / V s. The defect computations indicate that Ba Zr S 3 is intrinsically n -type due to shallow sulfur vacancies, but that strong compensation by sulfur vacancies will prevent attempts to make it p -type. We also establish that Ba Zr S 3 shows some degree of defect tolerance, presenting only few low formation energy, deep intrinsic defects. Among the deep defects, sulfur interstitials are the dominant nonradiative recombination centers but exhibit a moderate capture coefficient. Our work highlights the material’s intrinsic limitations in carrier mobility and p -type doping, and suggests focusing on suppressing the formation of sulfur interstitials to achieve longer carrier lifetime. Published by the American Physical Society 2024

Yuan, Zhenkun (ORCID:0000000272005973)↗
DOE OSTI2024

High-temperature carbon dioxide capture in a porous material with terminal zinc hydride sites

Carbon capture can mitigate point-source carbon dioxide (CO 2 ) emissions, but hurdles remain that impede the widespread adoption of amine-based technologies. Capturing CO 2 at temperatures closer to those of many industrial exhaust streams (>200°C) is of interest, although metal oxide absorbents that operate at these temperatures typically exhibit sluggish CO 2 absorption kinetics and instability to cycling. Here, in this study, we report a porous metal–organic framework featuring terminal zinc hydride sites that reversibly bind CO 2 at temperatures above 200°C—conditions that are unprecedented for intrinsically porous materials. Gas adsorption, structural, spectroscopic, and computational analyses elucidate the rapid, reversible nature of this transformation. Extended cycling and breakthrough analyses reveal that the material is capable of deep carbon capture at low CO 2 concentrations and high temperatures relevant to postcombustion capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Global Characteristics of Observable Foreshocks for Large Earthquakes

Abstract Foreshocks are the only currently widely identified precursory seismic behavior, yet their utility and even identifiability are problematic, in part because of extreme variation in behavior. Here, we establish some global trends that help identify the expected frequency of foreshocks as well the type of earthquake most prone to foreshocks. We establish these tendencies using the global earthquake catalog of the U.S. Geological Survey National Earthquake Information Center with a completeness level of magnitude 5 and mainshocks with Mw≥7.0. Foreshocks are identified using three clustering algorithms to address the challenge of distinguishing foreshocks from background activity. The methods give a range of 15%–43% of large mainshocks having at least one foreshock but a narrower range of 13%–26% having at least one foreshock with magnitude within two units of the mainshock magnitude. These observed global foreshock rates are similar to regional values for a completeness level of magnitude 3 using the same detection conditions. The foreshock sequences have distinctive characteristics with the global composite population b-values being lower for foreshocks than for aftershocks, an attribute that is also manifested in synthetic catalogs computed by epidemic-type aftershock sequences, which intrinsically involves only cascading processes. Focal mechanism similarity of foreshocks relative to mainshocks is more pronounced than for aftershocks. Despite these distinguishing characteristics of foreshock sequences, the conditions that promote high foreshock productivity are similar to those that promote high aftershock productivity. For instance, a modestly higher percentage of interplate mainshocks have foreshocks than intraplate mainshocks, and reverse faulting events slightly more commonly have foreshocks than normal or strike-slip-faulting mainshocks. The western circum-Pacific is prone to having slightly more foreshock activity than the eastern circum-Pacific.

Geochemistry & Geophysics↗
NASA NTRS1984

Memory efficient solution of the primitive equations for numerical weather prediction on the CYBER 205

Numerical Weather Prediction (NWP), for both operational and research purposes, requires only fast computational speed but also large memory. A technique for solving the Primitive Equations for atmospheric motion on the CYBER 205, as implemented in the Mesoscale Atmospheric Simulation System, which is fully vectorized and requires substantially less memory than other techniques such as the Leapfrog or Adams-Bashforth Schemes is discussed. The technique presented uses the Euler-Backard time marching scheme. Also discussed are several techniques for reducing computational time of the model by replacing slow intrinsic routines by faster algorithms which use only hardware vector instructions.

Tuccillo, J. J.↗
NASA NTRS2008

System and method of analyzing vibrations and identifying failure signatures in the vibrations

An apparatus, computer program product and method of analyzing structures. Intrinsic Mode Functions (IMFs) are extracted from the data and the most energetic IMF is selected. A spline is fit to the envelope for the selected IMF. The spline derivative is determined. A stability spectrum is developed by separating the positive and negative results into two different spectra representing stable (positive) and unstable (negative) damping factors. The stability spectrum and the non-linearity indicator are applied to the data to isolate unstable vibrations.

Huang, Norden E.↗
NASA NTRS2019

Dynamic Smagorinsky Modeled Large-Eddy Simulations of Turbulence Using Tetrahedral Meshes

Eddy-resolving numerical computations of turbulent flows are emerging as viable alternatives to Reynolds Averaged Navier-Stokes (RANS) calculations for flows with an intrinsically steady mean state due to the advances in large-scale parallel computing. In these computations, medium to large turbulent eddies are resolved by the numerics while the smaller or subgrid scales are either modeled or taken care of by the inherent numerical dissipation. To advance the state of the art of unstructured-mesh turbulence simulation capabilities, large eddy simulations (LES) using the dynamic Smagorinsky model (DSM) on tetrahedral meshes are carried out with the space-time conservation element, solution element (CESE) method. In contrast to what has been reported in the literature, the present implementation of dynamic models allows for active backscattering without any ad-hoc limiting of the eddy viscosity calculated from the subgrid-scale model. For the benchmark problems involving compressible isotropic turbulence decay as well as the shock/turbulent boundary layer interaction benchmark problems, no numerical instability associated with kinetic energy growth is observed and the volume percentage of the backscattering portion accounts for about 38-40% of the simulation domain. A slip-wall model in conjunction with the implemented DSM is used to simulate a relatively high Reynolds number Mach 2.85 turbulent boundary layer over a 30° ramp with several tetrahedral meshes and a wall-normal spacing of either Δγ& = 10 or Δγ& = 20. The computed mean wall pressure distribution, separation region size, mean velocity profiles, and Reynolds stress agree reasonably well with experimental data.

CESE method↗