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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Interpreting strain tensor data to characterize and monitor reservoirs for CO2 storage and other applications

Recent advances in instrumentation have made it feasible to measure the transient strain tensor caused by small changes in fluid volume or pressure in the subsurface and this has opened the door to new opportunities for characterization and monitoring. We have deployed strainmeters and then conducted injection well tests in an underlying reservoir at 530m depth. The resulting data indicated that the horizontal strain at shallow strainmeters (30 to 40m depth) was tensile and the vertical strain was compressive. The radial strain was less than the horizontal strain, and the strain rates decreased from 100 nanostrain/day to roughly 10 n/d over a few days. The signal at two strainmeters at shallow depth were consistent, although the magnitude of the horizontal strains were different reflecting the different radial directions from the well. The signal at a deep strainmeter deployed at reservoir depth was much different, with tensile vertical strains and compressive horizontal strains. These data can be interpreted by inverting poroelastic forward models developed using numerical and analytical methods. The average horizontal strain in the caprock resembles the transient pressure in the underlying reservoir and classic type-curve methods from transient well testing can be used for preliminary interpretations of strain data. We have developed closed-form analytical solutions to a pressurized poroelastic inclusion and inhomogeneity in a half-space. This model is fast and can be inverted to estimate reservoir stiffness and geometry. Numerical models developed using finite element methods allow more details of the subsurface to be included in the inversion, but they require much longer run times and this makes inversion cumbersome using standard methods. We have developed an inversion approach that uses a proxy model created using machine learning to do most of the forward calculations. The proxy model is periodically updated and refined using the finite element model to ensure accuracy. This approach significantly reduces the computational requirements and makes it feasible to use Bayesian inversion with large numerical models. We have shown that the strain tensor in the caprock is sensitive to pressure in the reservoir, boundaries in the reservoir, and pressure in the caprock caused by leaks. These results indicate that coupling strain tensor data with inversion has the potential to help evaluate reservoirs during initial characterization, and to monitor them during the CO2 injection and storage process.

Murdoch, Larry↗
DOE OSTI2025

Toward more-robust, AI-enabled subsurface seismic imaging for geotechnical applications

Non-invasive seismic imaging has the potential to cost-effectively evaluate large volumes of subsurface material to inform geotechnical site investigation. However, seismic imaging using full waveform inversion (FWI) requires significant computational time and is dependent on an initial starting model. As a result, FWI has not yet been widely adopted into geotechnical practice. Previous efforts, on relatively simple two-layered models, indicate that data-driven artificial intelligence (AI) models may be as effective as FWI at predicting 2D images of shear wave velocity (V s ). Furthermore, the AI model predictions can be made almost instantaneously after data acquisition and do not require an initial starting model. We examine the generality of these findings by developing a new AI model for subsurface seismic imaging, whereby we make several notable contributions. First, we architect a multimodal AI model that combines time- and frequency-domain representations of the seismic wavefield to predict a 50 m by 20 m subsurface image of V s . Second, we developed a new diverse dataset of 100,000 images with their corresponding seismic wavefields to train the AI model. Third, we propose four physics-informed data augmentations for data-driven seismic imaging. Fourth, we develop two prediction consistency tests to evaluate the model’s performance when the true subsurface is unknown. Our final model, which has been made publicly available, is capable of predicting a subsurface V s image from a single seismic wavefield with an average, mean absolute percent error (MAPE) of 24 %. The predictive model is applied to a field dataset and shown to be consistent with local geology and shear-wave refraction measurements from the same location.

Artificial intelligence↗
DOE OSTI2021

3D Theoretical and simulation tools for microbunched cooling

The concept of microbunched electron cooling (MBEC, introduced in Ref. [1]) is currently under investigation as a candidate for the strong hadron cooling (SHC) component of EIC. Most of the theoretical treatments of this scheme are based on a simplified model for the longitudinal space charge [2–4]. In this model, the particle beams are treated as collections of thin charged disks, with the interaction function for two such disks being calculated by averaging the forces between constituent point charges. Although the disk model is flexible and captures a large part of the underlying physics, it lacks the fidelity and robustness of an analysis that explicitly treats the beams as collections of point charges. In what follows, we explore such a model, both from a theory-based and a simulation perspective.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Towards multi-fidelity deep learning of wind turbine wakes

We report engineering wake models that accurately predict wake in a computationally efficient manner are very important for tasks such as layout optimization and control of wind farms. In this paper, we explore an application of deep learning (DL) to learn the wake model from hierarchies of physics-based approaches ranging from analytical models to an approximate form of the Reynolds-averaged Navier-Stokes equations. We first illustrate the application of principal component analysis to obtain a lower-dimensional representation that allows a computationally tractable training and deployment of DL models. Then, the DL model is trained to learn the mapping from input parameter space to the principal components, which are then used to reconstruct the three-dimensional flow field. Additionally, we investigate a composite framework consisting of two neural networks to learn the correlation between low- and high-fidelity data with Gauss and curl models treated as proxies for low- and high-fidelity models, respectively. The prediction from both DL models matches well with the high-fidelity data with a maximum relative percentage error for the kinetic energy flux of <1%. This work opens up possibilities for data-efficient construction of surrogate models for wake prediction that can be used to study the influence of wind speed and yaw angles on wind farm power production.

17 WIND ENERGY↗
DOE OSTI2022

Simple Autoignition Model for the Derived Cetane Number of Oxygenated Compounds and Fuel Blends

A simple four-step autoignition model was used to derive an expression for the ignition delay and derived cetane number (DCN) measured by ignition quality testers (IQT) for oxygenated compounds and blends as a function of each compound’s global initiation and net chain branching rate constants. Expressions for these values were determined assuming they could be related to the functional groups present in a given compound. Measurements for 124 compounds and 94 binary and ternary blends, gathered from the literature and performed at UW-Madison, were used to obtain the explicit dependence of the measured ignition delay on each functional group. The new model was able to successfully describe the ignition behavior of both the compounds and blends, with an average DCN error of 5.0 (22%) and 3.5 (15%), respectively. Additionally, the blend model could naturally be modified into a mixing rule by incorporating existing IQT ignition delay data for each compound. Use of the mixing rule was found to offer improvements over the full prediction, with an average DCN error of 3.2 (14%).

09 BIOMASS FUELS↗
DOE OSTI2021

Test of lepton flavor universality and search for lepton flavor violation in B → Kℓℓ decays

We present measurements of the branching fractions for the decays B → Kμ + μ - and B → Ke + e - , and their ratio (R K ), using a data sample of 711 fb -1 that contains 772 × 10 6 B$\bar{B}$ events. The data were collected at the Υ(4S) resonance with the Belle detector at the KEKB asymmetric-energy e + e - collider. The ratio R K is measured in five bins of dilepton invariant-mass-squared (q 2 ): q 2 $\epsilon$ (0.1, 4.0), (4.00, 8.12), (1.0, 6.0), (10.2, 12.8) and (> 14.18) GeV 2 /c 4 , along with the whole q 2 region. The R K value for q 2 $\epsilon$ (1.0, 6.0) GeV 2 /c 4 is 1.03$^{+0.28}_{-0.24}$ ± 0.01. The first and second uncertainties listed are statistical and systematic, respectively. All results for RK are consistent with Standard Model predictions. We also measure CP-averaged isospin asymmetries in the same q 2 bins. The results are consistent with a null asymmetry, with the largest difference of 2.6 standard deviations occurring for the q 2 $\epsilon$ (1.0, 6.0) GeV 2 /c 4 bin in the mode with muon final states. The measured differential branching fractions, dB/dq 2 , are consistent with theoretical predictions for charged B decays, while the corresponding values are below the expectations for neutral B decays. We have also searched for lepton-flavor-violating B → Kμ ± e ∓ decays and set 90% confidence-level upper limits on the branching fraction in the range of 10 -8 for B + → K + μ ± e ∓ , and B 0 → K 0 μ ± e ∓ modes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Framework for optimization of long-term, multi-period investment planning of integrated urban energy systems

In order to achieve stringent greenhouse gas emission reductions, a transition of our entire energy system from fossil to renewable resources needs to be designed. Such an energy transition brings two main challenges: most renewables generate variable electric energy, yet most demand is currently not electric (carrier mismatch) and does not always manifest at the same time as supply (temporal mismatch). Integrating multiple energy infrastructures can address both challenges by using the synergy between different energy carriers; building on existing infrastructure, while allowing a robust and flexible integration of the new. This paper proposes an optimization framework for long-term, multi-period investment planning of urban energy systems in an integrated manner. We formulate it as a mixed-integer linear program, combining a capacitated facility location with a multi-dimensional, capacitated network design problem. It includes generation and network expansion planning as well as interconnections between networks and storage infrastructure for each energy system. It can incorporate pathway effects like techno-economic developments, policy measures, and weather variations. The intended use is to support urban decision makers with long-term investment planning, though it can be tailored to fit other geographical or temporal scales. We demonstrate the model using two cases based on an average city in The Netherlands, which wants to reduce its CO 2 -emissions with 95% by 2050. In the first case, we include explicit carbon-emission constraints to study the effects of the carrier mismatch. In the second case, we implement interannual weather variations to analyze the temporal mismatch. The results give valuable insights into the energy transition design strategy for urban decision makers. They also show the future potential, as well as the computational challenges of the optimization framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Statistical chronometry of meteorites. I. A Test of 26 Al homogeneity and the Pb-Pb age of the solar system’s $t=0$

Here, we use rapidly cooled achondrites to test the assumption of 26 Al homogeneity in the solar nebula, by checking if there is a single value of t SS , the absolute “Pb-Pb” age of the Solar System’s t=0, that makes concordant their ages from the Al-Mg and Pb-Pb systems. We find that values t SS =4568.42 ± 0.24 Myr do make these ages concordant, and therefore the hypothesis of homogeneous 26 Al is not falsified. This age, defined to be when the solar nebula had ( 26 Al/ 27 Al) = 5.23 × 10 –5 , is significantly older than the ≈ 4567.3 Myr inferred from direct measurements of Pb-Pb ages in CAIs. Discrepancies between the Al-Mg and Pb-Pb chronometers in chondrules and CAIs have previously been interpreted as arising from heterogeneities in 26 Al, under the presumption that the Al-Mg and Pb-Pb systems in CAIs closed simultaneously. We examine this assumption and show that resetting is to be expected in CAIs. In particular, we quantitatively demonstrate that it is plausible that Pb-Pb ages of CAIs were reset at late times, without resetting the earlier Al-Mg ages, if they were transiently heated in the same manner as chondrules. We critically examine Pb-Pb isochrons, refining data and suggesting best practices for their calculation and reporting. We advocate reporting chronometry as times of formation after t=0 rather than absolute ages, as only the former is useful for astrophysical models of the solar nebula. We advocate averaging of multiple samples, rather than anchoring to individual meteorites, to improve precision.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Light absorption enhancement of black carbon in a pyrocumulonimbus cloud

Abstract Pyrocumulonimbus (pyroCb) firestorm systems have been shown to inject significant amounts of black carbon (BC) to the stratosphere with a residence time of several months. Injected BC warms the local stratospheric air, consequently perturbing transport and hence spatial distributions of ozone and water vapor. A distinguishing feature of BC-containing particles residing within pyroCb smoke is their thick surface coatings made of condensed organic matter. When coated with non-refractory materials, BC’s absorption is enhanced, yet the absorption enhancement factor ( E abs ) for pyroCb BC is not well constrained. Here, we perform particle-scale measurements of BC mass, morphology, and coating thickness from inside a pyroCb cloud and quantify E abs using an established particle-resolved BC optics model. We find that the population-averaged E abs for BC asymptotes to 2.0 with increasing coating thickness. This value denotes the upper limit of E abs for thickly coated BC in the atmosphere. Our results provide observationally constrained parameterizations of BC absorption for improved radiative transfer calculations of pyroCb events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Evidence of Inverse Hall-Petch Behavior and Low Friction and Wear in High Entropy Alloys

We present evidence of inverse Hall-Petch behavior for a single-phase high entropy alloy (CoCrFeMnNi) in ultra-high vacuum and show that it is associated with low friction coefficients (~0.3). Grain size measurements by STEM validate a recently proposed dynamic amorphization model that accurately predicts grain size-dependent shear strength in the inverse Hall-Petch regime. Wear rates in the initially soft (coarse grained) material were shown to be remarkably low (~10 –6 mm 3 /N-m), the lowest for any HEA tested in an inert environment where oxidation and the formation of mixed metal-oxide films is mitigated. The combined high wear resistance and low friction are linked to the formation of an ultra-nanocrystalline near-surface layer. The dynamic amorphization model was also used to predict an average high angle grain boundary energy (0.87 J/m 2 ). This value was used to explain cavitation-induced nanoporosity found in the highly deformed surface layer, a phenomenon that has been linked to superplasticity.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Role of deep levels and barrier height lowering in current-flow mechanism in 150 μ m thick epitaxial n-type 4H–SiC Schottky barrier radiation detectors

Schottky barrier detectors (SBDs) require larger surface areas than conventional electronics to increase the detection efficiency although such SBDs manifest large diode ideality factors due to inhomogeneous areal distribution of surface barrier height (SBH). Inhomogeneous SBH distributions lead to various current flow mechanisms in SBDs, which need to be identified to optimize detector performance. In this Letter, we identify the current flow mechanism in large area Schottky barrier diodes for radiation detection fabricated on 150 μm thick n-4H–SiC epitaxial layers. The analysis of temperature-dependent forward current–voltage (I–V–T) characteristics of SBDs revealed two linear regions in current–voltage curves up to 450 K, one corresponding to the current flow through a low barrier patch, while the other corresponds to that of average barrier distribution. Applying a SBH distribution model to the reverse I–V–T characteristics, an activation energy of 0.76 eV for the current flow over the Schottky barrier was calculated. Additionally, the activation energy did not directly correspond to any of the defect levels observed from the deep level transient spectroscopy (DLTS). Above 450 K, a Schottky type barrier lowering suggested a current flow through a low barrier patch of ≈ 0.8 eV. The absence of any SBH lowering below 450 K indicated that the current corresponded to a neutrally charged trap level at ≈ 0.6 eV below the conduction band edge, which was consistent with DLTS measurements revealing the presence of an electron trap level Z1/2 at 0.59 eV below the conduction band edge.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Accurate equation of state of H 2 – He binary mixtures up to 5.4 GPa

Brillouin scattering spectroscopy has been used to obtain an accurate (<1%) ρ-P equation of state (EOS) of 1:1 and 9:1 H 2 -He molar mixtures from 0.5 to 5.4 GPa at 296 K. Our calculated equations of state indicate close agreement with the experimental data right to the freezing pressure of hydrogen at 5.4 GPa. The measured velocities agree on average, within 0.5%, of an ideal mixing model. The ρ-P EOSs presented have a standard deviation of under 0.3% from the measured densities and under 1% deviation from ideal mixing. Furthermore, a detailed discussion of the accuracy, precision, and sources of error in the measurement and analyses of our equations of state is presented.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Distinct universality classes of diffusive transport from full counting statistics

The hydrodynamic transport of local conserved densities furnishes an effective coarse-grained description of the dynamics of a many-body quantum system. However, the full quantum dynamics contains much more structure beyond the simplified hydrodynamic description. Here we show that systems with the same hydrodynamics can nevertheless belong to distinct dynamical universality classes, as revealed by new classes of experimental observables accessible in synthetic quantum systems, which can, for instance, measure simultaneous site-resolved snapshots of all of the particles in a system. Specifically, we study the full counting statistics of spin transport, whose first moment is related to linear-response transport, but the higher moments go beyond. We present an analytic theory of the full counting statistics of spin transport in various integrable and nonintegrable anisotropic one-dimensional spin models, including the XXZ spin chain. We find that spin transport, while diffusive on average, is governed by a distinct non-Gaussian dynamical universality class in the models considered. We consider a setup in which the left and right half of the chain are initially created at different magnetization densities, and consider the probability distribution of the magnetization transferred between the two half-chains. We derive a closed-form expression for the probability distribution of the magnetization transfer, in terms of random walks on the half-line. We show that this distribution strongly violates the large-deviation form expected for diffusive chaotic systems, and explain the physical origin of this violation. Here, we discuss the crossovers that occur as the initial state is brought closer to global equilibrium. Our predictions can directly be tested in experiments using quantum gas microscopes or superconducting qubit arrays.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Past-completeness of inflationary spacetimes

Here, we discuss the question of whether or not inflationary spacetimes can be geodesically complete in the infinite past. Geodesic completeness is a necessary condition for averting an initial singularity during eternal inflation. It is frequently argued that cosmological models which are expanding sufficiently fast (having average Hubble expansion rate H avg > 0) must be incomplete in null and timelike past directions. This well-known conjecture relies on specific bounds on the integral of the Hubble parameter over a past- directed timelike or null geodesic. As stated, we show this claim is an open issue. We show that the calculation of H avg yields a continuum of results for a given spacetime predicated upon the underlying topological assumptions. We present an improved definition for H avg and introduce an uncountably infinite cohort of cosmological solutions which are geodesically complete despite having H avg > 0. We discuss a standardized definition for inflationary spacetimes as well as quantum (semiclassical) cosmological concerns over physically reasonable scale factors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Denoising Seismic Waveforms Using a Wavelet-Transform-Based Machine-Learning Method

Seismic waveform data recorded at stations can be thought of as a superposition of the signal from a source of interest and noise from other sources. Frequency‐based filtering methods for waveform denoising do not result in desired outcomes when the targeted signal and noise occupy similar frequency bands. Recently, denoising techniques based on deep‐learning convolutional neural networks (CNNs), in which a recorded waveform is decomposed into signal and noise components, have led to improved results. These CNN methods, which use short‐time Fourier transform representations of the time series, provide signal and noise masks for the input waveform. These masks are used to create denoised signal and designaled noise waveforms, respectively. However, advancements in the field of image denoising have shown the benefits of incorporating discrete wavelet transforms (DWTs) into CNN architectures to create multilevel wavelet CNN (MWCNN) models. The MWCNN model preserves the details of the input due to the good time–frequency localization of the DWT. In this report we use a data set of over 382,000 constructed seismograms recorded by the University of Utah Seismograph Stations network to compare the performance of CNN and MWCNN‐based denoising models. Evaluation of both models on constructed test data shows that the MWCNN model outperforms the CNN model in the ability to recover the ground‐truth signal component in terms of both waveform similarity and preservation of amplitude information. Model evaluation of real‐world data shows that both the CNN and MWCNN models outperform standard band‐pass filtering (BPF; average improvement in signal‐to‐noise ratio of 9.6 and 19.7 dB, respectively, with respect to BPF). Evaluation of continuous data suggests the MWCNN denoiser can improve both signal detection capabilities and phase arrival time estimates.

58 GEOSCIENCES↗
DOE OSTI2024

New Two-Cylinder Prototype Demonstration and Concept Design of a Next Generation Class 3-6 Opposed Piston Engine (Final Report)

The objective of the project is to research, develop, and test an Opposed Piston (OP) engine prototype capable of ≥10% fuel economy improvement over a 2015 baseline diesel engine while meeting prevailing emissions standards and include a cost analysis of the proposed technologies that validates an operating cost payback of less than 2 years. Results: In direct comparison with the baseline Isuzu model, the OP engine exhibited a noteworthy average fuel economy improvement exceeding 12% across five distinct driving cycles, including the Interstate cycle, Congested interstate cycle, GM-city cycle, HWFET cycle, and FTP cycle, with Interstate cycle benefited the most.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

High y + Shear-Stress Turbulence Implementation for High Flux Isotope Reactor Narrow Channel Flows

The research objective of this work was to improve the engineering predictions of the turbulence characteristics of flows in curved narrow channels. Such channel flows are commonly encountered in nuclear research and test reactors, with one of them being the high-flux isotope reactor (HFIR). Research reactors bear high heat fluxes, and the proper computing of turbulence is paramount for safe and reliable reactor operation. The study builds on the results of a previous direct numerical simulation of turbulence to inform a well-known Reynolds-averaged Navier–Stokes shear-stress turbulence model and improves its accuracy in simulating parallel channel flows. A new formulation of the loss term in the dissipation conservation equation is suggested. Combined with high wall distance computational grids, the new implementation provides a fast-running flow solution, suitable for engineering purposes. Model generalization for parallel channel flows, in a broader range of frictional Reynolds numbers, is suggested by introducing a new form of the model constants.

CFD↗
DOE OSTI2022

Properties of the Prompt Optical Counterpart Arising from the Cooling of Electrons in Gamma-Ray Bursts

This work extends a contemporaneous effort to study the properties of the lower-energy counterpart synchrotron emission produced by the cooling of relativistic gamma-ray burst (GRB) electrons through radiation (synchrotron and self-Compton) emission and adiabatic losses. We derive the major characteristics (pulse duration, lag time after burst, and brightness relative to the burst) of the prompt optical counterpart (POC) occurring during or after the GRB. Depending on the magnetic field lifetime, duration of electron injection, and electron transit time Δt o from hard X-ray (GRB) to optical-emitting energies, a POC may appear during the GRB pulse (of duration δt γ ) or after (delayed OC). The signature of counterparts arising from the cooling of GRB electrons is that POC pulses (Δto < δtγ) last as long as the corresponding GRB pulse (δt o ≃ δt γ ), while delayed OC pulses (Δt o > δt γ ) last as long as the transit time (δt o ≃ Δt o ). If OC variability can be measured, then another signature for this OC mechanism is that the GRB variability is passed on to POCs but not to delayed OCs. Within the GRB electron cooling model for counterparts, POCs should be on average dimmer than delayed ones (consistent with the data), and harder GRB low-energy slopes β LE should be associated more often with the dimmer POCs. The latter sets an observational bias against detecting POCs from (the cooling of electrons in) GRBs with a hard slope β LE , making it more likely that the detected POCs of such bursts arise from another mechanism.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗