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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multi-Scale Seismic Measurements for Site Characterization and CO2 Monitoring in an Enhanced Oil Recovery/Carbon Capture, Utilization, and Sequestration Project, Farnsworth Field, Texas

To address the challenges of climate change, significantly more geologic carbon sequestration projects are beginning. The characterization of the subsurface and the migration of the plume of supercritical carbon dioxide are two elements of carbon sequestration that can be addressed through the use of the available seismic methods in the oil and gas industry. In an enhanced oil recovery site in Farnsworth, TX, we employed three separate seismic techniques. The three-dimensional (3D) surface seismic survey required significant planning, design, and processing, but produces both a better understanding of the subsurface structure and a three-dimensional velocity model, which is essential for the second technique, a timelapse vertical seismic profile, and the third technique, cross-well seismic tomography. The timelapse 3D Vertical Seismic Profile (3D VSP) revealed both significant changes in the reservoir between the second and third surveys and geo-bodies that may represent the extent of the underground carbon dioxide. The asymmetry of the primary geo-body may indicate the preferential migration of the carbon dioxide. The third technique, cross-well seismic tomography, suggested a strong correlation between the well logs and the tomographic velocities, but did not observe changes in the injection interval.

Energy & Fuels↗
DOE OSTI2022

Monitoring Fracture Saturation With Internal Seismic Sources and Twin Neural Networks

Seismic coda-wave analysis is a well-developed method for detecting subtle physical changes in complex media by measuring arrival times in the late-arriving energy from multiply scattered or reflected waves. However, a challenge arises when multiply scattered waves are not sufficiently separated in time from the direct arrivals to provide a clear coda wave train. Additional complications for monitoring changes in fracture systems arise when the signals originate from unsynchronized internal sources, such as natural or induced seismicity, from acoustic emission, or from transportable intra-fracture sources (chattering dust), that generate uncontrolled signals that vary in arrival time, amplitude and frequency content. Here, we use a twin neural network (TNN also known as a Siamese neural network) for dimensionality reduction to analyze signals from chattering dust to classify the fluid saturation state of a synthetic fracture system. The TNN with shared weights generates a low-dimensional representation of the data input by minimizing contrastive loss, serving as the input to a multiclass classifier that accurately classifies whether multiple fractures in a fracture system are fully saturated or partially saturated, or whether a change in saturation has occurred in different fractures in the system. Furthermore, these results show that information buried in unresolved codas from uncontrolled sources can be extracted using machine learning to monitor the evolution of fracture systems caused by physical and chemical processes even when the scattered and direct wave fields overlap.

58 GEOSCIENCES↗
DOE OSTI2022

Multifunctional transitional metal-based phosphide nanoparticles towards improved polysulfide confinement and redox kinetics for highly stable lithium-sulfur batteries

The shuttle effect and the sluggish redox kinetics of lithium polysulfides (LiPSs) are the major issues impeding the practical applications of lithium-sulfur batteries (LSBs). Herein, a highly-efficient Ni 2 P electrocatalyst supported on N, P co-doped graphene (Ni 2 P@NPG) is developed via a simple “recrystallization-self-assembly” method to address the above issues. Here, the ultrafine Ni 2 P nanoparticles ensure abundant adsorption-diffusion-conversion interfaces for accelerating LiPSs transformation and Li 2 S deposition, which extremely decreases the accumulation of LiPSs in the electrolyte and therefore prevents the migration of LiPSs. Their superior catalytic performance is demonstrated by reduced Gibbs free energy changes of rate-limiting step based on the systematic theoretical calculations and the reduced shuttle effect is tested by the three-dimensional reconstructions of Raman depth profiles. Benefiting from these synergistic effects, the LSBs with Ni 2 P@NPG modified separators present a superior cycling performance with an average capacity decay rate of 0.048 % per cycle at 1C around the 400 cycles and a high-rate capacity of 731 mAh/g at 2C. Even with a high-sulfur loading of 3.53 mg cm –2 , the cell can still contain a reversible capacity of 809 mAh/g at 0.2C with a remarkable columbic efficiency of 98.4 %.

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

Latent Representation Learning for Structural Characterization of Catalysts

Supervised machine learning-enabled mapping of the X-ray absorption near edge structure (XANES) spectra to local structural descriptors offers new methods for understanding the structure and function of working nanocatalysts. We briefly summarize a status of XANES analysis approaches by supervised machine learning methods. We present an example of an autoencoder-based, unsupervised machine learning approach for latent representation learning of XANES spectra. This new approach produces a lower-dimensional latent representation, which retains a spectrum–structure relationship that can be eventually mapped to physicochemical properties. Furthermore, the latent space of the autoencoder also provides a pathway to interpret the information content “hidden” in the X-ray absorption coefficient. Our approach (that we named latent space analysis of spectra, or LSAS) is demonstrated for the supported Pd nanoparticle catalyst studied during the formation of Pd hydride. By employing the low-dimensional representation of Pd K-edge XANES, the LSAS method was able to isolate the key factors responsible for the observed spectral changes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Selective bond formation triggered by short optical pulses: quantum dynamics of a four-center ring closure

Here we report bond formation induced by an ultrashort UV pulse. The photochemical process is described by quantum dynamics as coherent electronic and nuclear motions during the ultrashort pulse induced ring closure of norbornadiene to quadricyclane. Norbornadiene consists of two ethylene moieties connected by a rigid (CH 2 ) 3 bridge. Upon photoexcitation, two new sigma bonds are formed, resulting in the closure of a four-atom ring. As a medium-sized polyatomic molecule, norbornadiene exhibits a high density of strongly coupled electronic states from about 6 eV above the ground state. We report on inducing the formation of the new bonds using a short femtosecond UV pulse to pump a non-equilibrium electronic density in the open form that evolves towards the closed ring form. As the coherent electronic-nuclear coupled dynamics unfold, the excited states change character through non-adiabatic interactions and become valence states for the two new C–C bonds of quadricyclane. Our three-dimensional fully quantum dynamical grid simulations during the first 200 fs show that short UV pulses of different polarization initiate markedly different initial non-equilibrium electronic densities that follow different dynamical paths to the S 0 /S 1 conical intersection. They lead to different initial relative yields of quadricyclane, thereby opening the way to controlling bond-making with attopulses.

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

Toward 3D data visualization using virtual reality tools

Virtual Reality (VR) offers the opportunity to display data, instrumentation, and experimental setups in three dimensions and gives the user the ability to interact with the objects. This technology moves visualization beyond two-dimensional projections on a flat screen with a fixed field of view in which a keyboard or another similar controller is needed to change the view. Advances in both hardware and software for VR make it possible for the non-expert to develop visualization tools for scientific applications both for viewing and for sharing data or diagnostic hardware between users in three dimensions. Furthermore, this manuscript describes application development using two VR software tools, Unity gaming engine and A-frame, for visualizing data and high energy physics targets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

A Multilevel in Space and Energy Solver for 3-D Multigroup Diffusion and Coarse-Mesh Finite Difference Eigenvalue Problems

The Multilevel in Space and Energy Diffusion (MSED) method accelerates the iterative convergence of multigroup diffusion eigenvalue problems by performing work on lower-order equations with only one group and/or coarser spatial grids. It consists of two primary components: (1) a grey (one-group) diffusion eigenvalue problem that is solved via Wielandt-shifted power iteration (PI) and (2) a multigrid-in-space linear solver. In previous work, the efficiency of MSED was verified using Fourier analysis and numerical results from a one-dimensional multigroup diffusion code. Since that work, MSED has been implemented as a solver for the coarse-mesh finite difference (CMFD) system in the three-dimensional Michigan Parallel Characteristics Transport (MPACT) code. In this paper, the results from the implementation of MSED in MPACT are introduced, and the changes needed to make MSED more suitable for MPACT are described. For problems without feedback, the conclusions in this paper show that MSED can reduce the CMFD run time by an order of magnitude and the overall run time by a factor of 2 to 3 compared to the default CMFD solver in MPACT [PI with the generalized minimal residual (GMRES) method]. For problems with feedback, the convergence of the outer Picard iteration scheme is worsened by the well-converged CMFD solutions produced by the standard MSED method. To overcome this unintuitive deficiency, MSED may be run with looser convergence criteria (a modified version of the MSED method called MSED-L) to circumvent the issue until the multiphysics iteration in MPACT is improved. Results show that MSED-L can reduce the CMFD run time in MPACT by an order of magnitude, without negatively impacting the outer Picard iteration scheme.

3-D↗
DOE OSTI2020

Production of relativistic electrons at subrelativistic laser intensities

Relativistic electron temperatures were measured from kilojoule, subrelativistic laser-plasma interactions. Experiments reflect an order of magnitude higher temperatures than expected from a ponderomotive scaling, where temperatures of up to 2.2 MeV were generated using an intensity of 1 × 10 18 W/cm 2 . Two-dimensional particle-in-cell simulations suggest that electrons gain superponderomotive energies by stochastic acceleration as they sample a large area of rapidly changing laser phase. We further demonstrate that such high temperatures are possible from subrelativistic intensities by using lasers with long pulse durations and large spatial scales.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Ion intercalation engineering of electronic properties of two-dimensional crystals of 2H-TaSe 2

Ion intercalation was recently used to explore two-dimensional (2D) transition metal dichalcogenides (TMDs) with precise tuning of ion concentration in a field-effect-transistor configuration. However, how to systematically change the properties of 2D TMDs, e.g., superconductivity and charge density waves, by ion intercalation has not been explored. As such, we report in this paper results of electrical transport measurements on 2D crystals of 2H-TaSe 2 intercalated with Li ions that is tuned continuously by ionic gating. Shubnikov–de Haas magnetoconductance oscillation and Hall coefficient measurements on crystals of 2H-TaSe 2 revealed an ion intercalation induced multi- to single-band change in the Fermi surface (FS) topology, deep in the charge density wave phase, resulting in a reduction of the number of independent channels for electronic conduction. A remarkable crossover from weak antilocalization to weak localization tuned by gate voltage or temperature was found and attributed to the ion intercalation induced variations in the spin-orbital coupling and electron-phonon interaction. These observations provide new insight into the enhancement of superconductivity and the suppression of charge density waves in 2D 2H-TaSe 2 induced by ion intercalation and demonstrate furthermore the great potential of ion intercalation for engineering electronic properties of 2D TMDs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Improved Particle Swarm Algorithm Using Rubik’s Cube Topology for Bilevel Building Energy Transaction

Following the rapid growth of distributed energy resources (e.g., renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as reducing power loss and stabilizing the main power grid. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. Additionally, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush–Kuhn–Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence-based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubik’s Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubik’s Cube topology-based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology-based PSO and its scalability on larger scale applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Grassmannian Diffusion Maps--Based Dimension Reduction and Classification for High-Dimensional Data

This work introduces the Grassmannian diffusion maps (GDMaps), a novel nonlinear dimensionality reduction technique that defines the affinity between points through their representation as low-dimensional subspaces corresponding to points on the Grassmann manifold. Here, the method is designed for applications, such as image recognition and data-based classification of constrained high-dimensional data where each data point itself is a high-dimensional object (i.e., a large matrix) that can be compactly represented in a lower-dimensional subspace. The GDMaps is composed of two stages. The first is a pointwise linear dimensionality reduction wherein each high-dimensional object is mapped onto the Grassmann manifold representing the low-dimensional subspace on which it resides. The second stage is a multipoint nonlinear kernel-based dimension reduction using diffusion maps to identify the subspace structure of the points on the Grassmann manifold. To this end, an appropriate Grassmannian kernel is used to construct the transition matrix of a random walk on a graph connecting points on the Grassmann manifold. Spectral analysis of the transition matrix yields low-dimensional Grassmannian diffusion coordinates embedding the data into a low-dimensional reproducing kernel Hilbert space. Further, a novel data classification/recognition technique is developed based on the construction of an overcomplete dictionary of reduced dimension whose atoms are given by the Grassmannian diffusion coordinates. Three examples are considered. First, a "toy" example shows that the GDMaps can identify an appropriate parametrization of structured points on the unit sphere. The second example demonstrates the ability of the GDMaps to revealing the intrinsic subspace structure of high-dimensional random field data. In the last ex- ample, a face recognition problem is solved considering face images subject to varying illumination conditions, changes in face expressions, and occurrence of occlusions. The technique presented high recognition rates (i.e., 95% in the best case) using a fraction of the data required by conventional methods.

42 ENGINEERING↗
DOE OSTI2022

Demonstrating the Value of 3D Models to Support Large-Scale Digital Modifications at Nuclear Power Plants

Many Nuclear Power Plants are currently in the process of extending their operating licenses for continued generation. The use of three-dimensional (3D) modeling in the early stages of large scale NPP modernization efforts is one lower cost method that can verify proposed design changes against established guidelines and allows for visual presentation of the 3D model to various stakeholders in the project. Guidance from Nuclear Regulatory Commission NUREG 0711 and 0700, and other sources on performing HF/E for control rooms and design modifications can be visually represented in 3D models. Distance and measurements, workstation design, anthropometric considerations, and early feedback of modifications are used in 3D models to identify potential human issues early in the design process. 3D modeling is a useful tool for early design and help to reduce costs and present visuals to stakeholders early in the design.

3D Models↗
NASA NTRS1972

The coronal transport of the flare associated scatter free electrons

A total of 11 scatter-free electron events from McMath plage region 8905 were observed by IMP 4 during the period from 29 July to 3 August 1967. The transit times and duration of these electron events are examined in detail. The duration of 170- to 1000-keV electrons shows a strong dependence upon the heliolongitude of the associated flare. Typical values of the duration full width at half maximum vary from 4 min at 50 deg W to 12 min at 10 deg and 90 deg W heliolongitudes. In addition, the difference in times at which the maximum intensities of the 22- to 45-keV and 170- to 1000-keV electrons occur is observed to change from 18 min near 50 deg W to 13 min at 10 deg and 90 deg W heliolongitudes. An idealized two-dimensional diffusion model for the transport of these electrons in the solar corona is proposed. The 22- to 45-keV electrons escape promptly from flare site to the feet of the interplanetary magnetic field lines, whereas 170- to 1000-keV electrons suffer slight scattering. The diffusion coefficient for 170- to 1000-keV electrons is estimated to be 3 X 10 to the 18th power sq cm/sec. Finally, a possible relation between the scatter-free and the classical diffusive-type electron events is discussed.

Wang, J. R.↗
NASA NTRS1982

Powerplant Thermal-Pollution Models

Three models predict nature of thermal plumes from powerplant discharge into water. Free-surface model accomodates major changes in ocean currents. Rigid-model accurately predicts changes in thermal plume caused by other inputs and outputs, such as pumped-water storage and hydroelectric-plant discharges. One-dimensional model predicts approximate stratification in lake with such inputs and outputs over a long period.

Lee, S. S.↗
NASA NTRS1980

Scale effects in the dynamic transfer functions for cavitating inducers

Dynamic transfer functions for two cavitating inducers of the same geometry but different size are presented, compared and discussed. The transfer functions for each inducer indicate similar trends as the cavitation number is decreased; only minor changes are noted with changes in the flow coefficient, the uniformity of the inlet flow or the temperature of the water (21-74 C). The non-dimensional results for the two sizes are compared with themselves and with theoretical calculations based on the bubbly flow model. All three sets of results compare well and lend further credence to the theoretical model. The best values of the two parameters in the model are evaluated and recommended for use in applications.

Brennen, C. E.↗
NASA NTRS1981

Three methods for performing Hankel transforms

Three methods for performing Hankel transforms with optical or digital processors are described. The first method is applicable when the input data is available in Cartesian (x-y) format and uses the close connection between generalized Hankel transform and the two dimensional Fourier transform in Cartesian coordinates. The second method is useful when the input data is in polar (r - theta) format and uses change of variables to perform the nth order Hankel transform as a correlation integral. The third method utilizes the von Neumann addition theorem for Bessel functions to extract the Hankel coefficients from a correlation between the radial part of the input and a Bessel function. Initial experimental results obtained for optical implementation of the first two methods are presented.

Athale, R. A.↗
NASA NTRS1981

Cluster adsorption on amorphous and crystalline surfaces - A molecular dynamics study of model Pt on Cu and model Pd on Pt

Molecular dynamics was used to study the structure, dispersion and short-time behavior of ten-atom clusters adsorbed onto amorphous and crystalline substrates, in which the cluster atoms differed from the substrate atoms. Two adatom-substrate model systems were chosen; one, in which the interaction energy between adatom pairs was greater than that between substrate pairs, and the other, in which the reverse was true. At relatively low temperature ranges, increased dispersion of cluster atoms occurred: (a) on the amorphous substrate as compared to the FCC(100) surface, (b) with increasing reduced temperature, and (c) with adatom-substrate interaction energy stronger than adatom-adatom interaction. Two-dimensional clusters (rafts) on the FCC(100) surface displayed migration of edge atoms only, indicating a mechanism for the cluster rotation and shape changes found in experimental studies.

Garofalini, S. H.↗
NASA NTRS1981

Application of a laser interferometer skin-friction meter in complex flows

The application of a nonintrusive laser-interferometer skin-friction meter, which measures skin friction with a remotely located laser interferometer that monitors the thickness change of a thin oil film, is extended both experimentally and theoretically to several complex wind-tunnel flows. These include two-dimensional seperated and reattached subsonic flows with large pressure and shear gradients, and two and three-dimensional supersonic flows at high Reynolds number, which include variable wall temperatures and cross-flows. In addition, it is found that the instrument can provide an accurate location of the mean reattachment length for separated flows. Results show that levels up to 120 N/sq m, or 40 times higher than previous tests, can be obtained, despite encountering some limits to the method for very high skin-friction levels. It is concluded that these results establish the utility of this instrument for measuring skin friction in a wide variety of flows of interest in aerodynamic testing.

Monson, D. J.↗