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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Scaling and data collapse from local moments in frustrated disordered quantum spin systems

Recently measurements on various spin–1/2 quantum magnets such as H 3 LiIr 2 O 6 , LiZn 2 Mo 3 O 8 , ZnCu 3 (OH) 6 Cl 2 and 1T-TaS 2 —all described by magnetic frustration and quenched disorder but with no other common relation—nevertheless showed apparently universal scaling features at low temperature. In particular the heat capacity C[H, T] in temperature T and magnetic field H exhibits T/H data collapse reminiscent of scaling near a critical point. Here we propose a theory for this scaling collapse based on an emergent random-singlet regime extended to include spin-orbit coupling and antisymmetric Dzyaloshinskii-Moriya (DM) interactions. We derive the scaling C[H, T]/T ~ H- γ F q [T/H] with F q [x] = x q at small x, with q ϵ {0, 1, 2} an integer exponent whose value depends on spatial symmetries. The agreement with experiments indicates that a fraction of spins form random valence bonds and that these are surrounded by a quantum paramagnetic phase. We also discuss distinct scaling for magnetization with a q-dependent subdominant term enforced by Maxwell’s relations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Programmable catalysis by support polarization: elucidating and breaking scaling relations

The Sabatier principle and the scaling relations have been widely used to search for and screen new catalysts in the field of catalysis. However, these powerful tools can also serve as limitations of catalyst control and breakthrough. To overcome this challenge, this work proposes an efficient method of studying catalyst control by support polarization from first-principles. The results demonstrate that the properties of catalysts are determined by support polarization, irrespective of the magnitude of spontaneous polarization of support. The approach enables elucidating the scaling relations between binding energies at various polarization values of support. Moreover, we observe the breakdown of scaling relations for the surface controlled by support polarization. By studying the surface electronic structure and decomposing the induced charge into contributions from different atoms and orbitals, we identify the inherent structural property of the interface that leads to the breaking of the scaling relations. Specifically, the displacements of the underlying oxide support impose its symmetry on the catalyst, causing the scaling relations between different adsorption sites to break.

Chemical engineering↗
DOE OSTI2025

Non-equilibrium critical scaling and universality in a quantum simulator

Universality and scaling laws are hallmarks of equilibrium phase transitions and critical phenomena. However, extending these concepts to non-equilibrium systems is an outstanding challenge. Despite recent progress in the study of dynamical phases, the universality classes and scaling laws for non-equilibrium phenomena are far less understood than those in equilibrium. In this work, using a trapped-ion quantum simulator with single-spin resolution, we investigate the non-equilibrium nature of critical fluctuations following a quantum quench to the critical point. We probe the scaling of spin fluctuations after a series of quenches to the critical Hamiltonian of a long-range Ising model. With systems of up to 50 spins, we show that the amplitude and timescale of the post-quench fluctuations scale with system size with distinct universal critical exponents, depending on the quench protocol. While a generic quench can lead to thermal critical behavior, we find that a second quench from one critical state to another (i.e. a double quench) results in a new universal non-equilibrium behavior, identified by a set of critical exponents distinct from their equilibrium counterparts. Our results demonstrate the ability of quantum simulators to explore universal scaling beyond equilibrium.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Cross-scale covariance for material property prediction

A simulation can stand its ground against an experiment only if its prediction uncertainty is known. The unknown accuracy of interatomic potentials (IPs) is a major source of prediction uncertainty, severely limiting the use of large-scale classical atomistic simulations in a wide range of scientific and engineering applications. Here we explore covariance between predictions of metal plasticity, from 178 large-scale (~10 8 atoms) molecular dynamics (MD) simulations, and a variety of indicator properties computed at small-scales (≤10 2 atoms). All simulations use the same 178 IPs. In a manner similar to statistical studies in public health, we analyze correlations of strength with indicators, identify the best predictor properties, and build a cross-scale “strength-on-predictors” regression model. This model is then used to estimate regression error over the statistical pool of IPs. Small-scale predictors found to be highly covariant with strength are computed using expensive quantum-accurate calculations and used to predict flow strength, within the statistical error bounds established in our study.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Improving deep learning performance for predicting large-scale geological ${{CO}_{2}}$ sequestration modeling through feature coarsening

Physics-based reservoir simulation for fluid flow in porous media is a numerical simulation method to predict the temporal-spatial patterns of state variables (e.g. pressure p) in porous media, and usually requires prohibitively high computational expense due to its non-linearity and the large number of degrees of freedom (DoF). This work describes a deep learning (DL) workflow to predict the pressure evolution as fluid flows in large-scale 3-dimensional(3D) heterogeneous porous media. In particular, we develop an efficient feature coarsening technique to extract the most representative information and perform the training and prediction of DL at the coarse scale, and further recover the resolution at the fine scale by spatial interpolation. We validate the DL approach to predict pressure field against physics-based simulation data for a field-scale 3D geologic CO 2 sequestration reservoir model. We evaluate the impact of feature coarsening on DL performance, and observe that the feature coarsening not only decreases the training time by >74% and reduces the memory consumption by >75%, but also maintains temporal error 0.63% on average. Besides, the DL workflow provides predictive efficiency with 1406 times speedup compared to physics-based numerical simulation. The key findings from this research significantly improve the training and prediction efficiency of deep learning model to deal with large-scale heterogeneous reservoir models, and thus it can also be further applied to accelerate workflows of history matching and reservoir optimization for close-loop reservoir management.

58 GEOSCIENCES↗
DOE OSTI2023

Effects of grain size and small-scale bedform architecture on CO 2 saturation from buoyancy-driven flow

Small-scale (mm-dm scale) heterogeneity has been shown to significantly impact CO 2 migration and trapping. To investigate how and why different aspects of small-scale heterogeneity affect the amount of capillary trapping during buoyancy-driven upward migration of CO 2 , we conducted modified invasion percolation simulations on heterogeneous domains. Realistic simulation domains are constructed by varying two important aspects of small-scale geologic heterogeneity: sedimentary bedform architecture and grain size contrast between the matrix and the laminae facies. Buoyancy-driven flow simulation runs cover 59 bedform architecture and 40 grain size contrast cases. Simulation results show that the domain effective CO 2 saturation is strongly affected by both grain size and bedform architecture. At high grain size contrasts, bedforms with continuous ripple lamination at the cm scale tend to retain higher CO 2 saturation than bedforms with discontinuous or cross lamination. In addition, the “extremely well sorted” grain sorting cases tend to have lower CO 2 saturation than expected for cross-laminated domains. Finally, both a denser CO 2 phase and greater interfacial tension increase CO 2 saturation. Again, variation in fluid properties seems to have a greater effect on CO 2 saturation for cross-laminated domains. This result suggests that differences in bedform architecture can impact how CO 2 saturation values respond to other variables such as grain sorting and fluid properties.

58 GEOSCIENCES↗
DOE OSTI2023

Scaling of ionic conductance in a fluctuating single-layer nanoporous membrane

Abstract Single-layer membranes have emerged as promising candidates for applications requiring high transport rates due to their low resistance to molecular transport. Owing to their atomically thin structure, these membranes experience significant microscopic fluctuations, emphasizing the need to explore their impact on ion transport processes. In this study, we investigate the effects of membrane fluctuations on the elementary scaling behavior of ion conductance $$G$$ G as a function of ion concentration $$c_{0}$$ c 0 , represented as $$G = \beta c_{0}^{\alpha }$$ G = β c 0 α , using molecular dynamics simulations. Our findings reveal that membrane fluctuations not only alter the conductance coefficient $$\beta$$ β but also the power-law exponent $$\alpha$$ α . We identify two distinct frequency regimes of membrane fluctuations, GHz-scale and THz-scale fluctuations, and examine their roles in conductance scaling. Furthermore, we demonstrate that the alteration of conductance scaling arises from the non-linearity between ion conductance and membrane shape. This work provides a fundamental understanding of ion transport in fluctuating membranes.

42 ENGINEERING↗
DOE OSTI2026

Locating the missing large-scale emission in the jet of M87* with short EHT baselines

In very-long baseline interferometric arrays, nearly co-located stations probe the largest scales and typically cannot resolve the observed source. In the absence of a large-scale structure, closure phases constructed with these stations are zero and, since they are independent of station-based errors, they can be used to probe data issues. Here, we show how these trivial closure phases become nonzero with a brightness distribution on smaller scales than their short baseline would suggest. When applied to sources that are made up of a bright compact and large-scale diffuse component, the trivial closure phases directly measure the centroid relative to the compact source and higher-order image moments. We present a technique to measure these image moments with minimal model assumptions and validate it on synthetic Event Horizon Telescope (EHT) data. We then apply this technique to 2017 and 2018 EHT observations of M87* and find a weak preference for extended emission in the direction of the large-scale jet. We also apply it to 2021 EHT data and measure the source centroid about 1 mas northwest of the compact ring, which is consistent with the jet observed at lower frequencies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Small-Scale Irrigation: Improving Food Security under Changing Climate and Water Resource Conditions in Ethiopia

We develop a new systems modeling tool that integrates knowledge from hydrology, agriculture, and economics to understand the effect of small-scale irrigation on food security and groundwater sustainability in Ethiopia. Irrigation is an effective tool to mitigate climate impacts and improve agricultural yields. Small-scale irrigation, such as decentralized groundwater irrigation, is well suited for developing countries where smallholder farming communities are widely dispersed and can only afford small infrastructure investment. We study the underlying interdependencies between food and water systems in Ethiopia, where small-holder agriculture is the foundation of the nation’s economy and climate variability has led to great challenges to its food security. Our coupled market and crop model with groundwater module captures the interdependencies of climate, water availability (including irrigation), crop yield, farmland allocation, crop production, transport and consumption based on a system approach across multiple spatial scales. We study the implication of small-scale irrigation to Ethiopia’s food security and water resource conditions as a “what-if” question by comparing an irrigation scenario to the calibrated baseline in 2015, a year of significant drought and crop failure over a large portion of Ethiopia. Our model offers fresh insights into geographic disparities in outcomes that are driven by baseline climate variability, soil fertility, and market conditions. In general, we find that small-scale irrigation can potentially improve food security through increases in food consumption, but it requires policy support to direct the increases of production to domestic consumption while maintaining a sustainable groundwater condition. By using Ethiopia as an example, we show the strength of our model to study how water infrastructure resources support critical functions and service in water and food systems.

Zhang, Ying↗
DOE OSTI2014

Process metallurgy simulation for metal drawing process optimization by using two-scale finite element method

We developed two-scale FE analysis procedure based on the crystallographic homogenization method by considering the hierarchical structure of poly-crystal aluminium alloy metal. It can be characterized as the combination of two-scale structure, such as the microscopic polycrystal structure and the macroscopic elastic plastic continuum. Micro polycrystal structure can be modeled as a three dimensional representative volume element (RVE). RVE is featured as by 3×3×3 eight-nodes solid finite elements, which has 216 crystal orientations. This FE analysis code can predict the deformation, strain and stress evolutions in the wire drawing processes in the macro- scales, and further the crystal texture and hardening evolutions in the micro-scale. In this study, we analyzed the texture evolution in the wire drawing processes by our two-scale FE analysis code under conditions of various drawing angles of dice. We evaluates the texture evolution in the surface and center regions of the wire cross section, and to clarify the effects of processing conditions on the texture evolution.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Sub-grid-scale description of turbulent magnetic reconnection in magnetohydrodynamics

Magnetic reconnection requires, at least locally, a non-ideal plasma response. In collisionless space and astrophysical plasmas, turbulence could transport energy from large to small scales where binary particle collisions are rare. We have investigated the influence of small scale magnetohydrodynamics (MHD) turbulence on the reconnection rate in the framework of a compressible MHD approach including sub-grid-scale (SGS) turbulence. For this sake, we considered Harris-type and force-free current sheets with finite guide magnetic fields directed out of the reconnection plane. The goal is to find out whether unresolved by conventional simulations MHD turbulence can enhance the reconnection process in high-Reynolds-number astrophysical plasmas. Together with the MHD equations, we solve evolution equations for the SGS energy and cross-helicity due to turbulence according to a Reynolds-averaged turbulence model. The SGS turbulence is self-generated and -sustained through the inhomogeneities of the mean fields. By this way, the feedback of the unresolved turbulence into the MHD reconnection process is taken into account. It is shown that the turbulence controls the regimes of reconnection by its characteristic timescale τ{sub t}. The dependence on resistivity was investigated for large-Reynolds-number plasmas for Harris-type as well as force-free current sheets with guide field. We found that magnetic reconnection depends on the relation between the molecular and apparent effective turbulent resistivity. We found that the turbulence timescale τ{sub t} decides whether fast reconnection takes place or whether the stored energy is just diffused away to small scale turbulence. If the amount of energy transferred from large to small scales is enhanced, fast reconnection can take place. Energy spectra allowed us to characterize the different regimes of reconnection. It was found that reconnection is even faster for larger Reynolds numbers controlled by the molecular resistivity η, as long as the initial level of turbulence is not too large. This implies that turbulence plays an important role to reach the limit of fast reconnection in large Reynolds number plasmas even for smaller amounts of turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Experimental and numerical analysis of the performance and wake of a scale–model horizontal axis marine hydrokinetic turbine

Here, this paper presents an experimental and numerical study of a scale-model Horizontal Axis Hydrokinetic Turbine (HAHT). The model turbine is based on the U.S. Department of Energy Reference Model 1 (RM1), with the blade geometry modified to reproduce the design C p –TSR performance curve of the RM1 at the flume scale Reynolds numbers (5 × 10 4 –10 × 10 5 ). The performance and wake structure of a 45:1 scale turbine were measured using a load cell (torque applied on shaft) and a magnetic angular encoder (rotor rpm), and by planar particle image velocimetry, respectively. The details of the rotor flow field and three-dimensional wake evolution are analyzed from the numerical solution of the RANS equations solved around a computational model of the turbine. The comparison of experimental and numerical results highlights the strengths and limitations of the experimental and numerical analyses in the characterization of HAHT. Useful guidelines for developing experimental flume scale data and using them for validating numerical tools, as well as for performing a similar type of analysis and design validation of full scale devices as pilot projects start to go in the water in the United States, are provided.

13 HYDRO ENERGY↗
DOE OSTI2020

Scaling arguments for a plasma experiment relevant to an interplanetary coronal mass ejection

We present the design of a plasma experiment scaled to be relevant to an interplanetary coronal mass ejection (ICME) traveling from the Sun to the Earth. The experiment would launch a compact torus of plasma (the scaled analog of the coronal mass ejected by the Sun) into a magnetized background plasma (the scaled analog of the interplanetary medium, the diffuse magnetized plasma that fills the Solar System). We present the complete process of scaling the ICME system to a laboratory experiment: beginning with the ICME features that we aim to replicate with a laboratory experiment, explaining how these desired features are translated into specific design constraints, and presenting a set of experimental parameters that meet those constraints. We find that the experiment would be possible with plasma conditions typically achieved in large-scale facilities such as the Big Red Ball at the University of Wisconsin or the LArge Plasma Device at the University of California, Los Angeles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Improvements in the orbitalwise scaling down of Perdew–Zunger self-interaction correction in many-electron regions

The Perdew-Zunger (PZ) method offers a way to remove the self-interaction (SI) error from density functional approximations on an orbital by orbital basis. The PZ method provides significant improvements for the properties such as barrier heights or dissociation energies but results in over-correcting the properties well described by SI-uncorrected semi-local functional. One cure to rectify the over-correcting tendency is to scale down the magnitude of SI-correction of each orbital in the many electron region. We have implemented the orbitalwise scaled down SI-correction (OSIC) scheme of Vydrov et al. [J. Chem. Phys. 124, 094108 (2006)] using the Fermi-L owdin SI-correction method. After validating the OSIC implementation with previously reported OSICLSDA results, we examine its performance with the most successful non-empirical SCAN meta-GGA functional. Using different forms of scaling factors to identify one-electron regions, we assess the performance of OSIC-SCAN for a wide range of properties: total energies, ionization potentials and electron affinities for atoms, atomization energies, dissociation and reaction energies, and reaction barrier heights of molecules. Our results show that OSIC-SCAN provides superior results than the previously reported OSIC-LSDA, -PBE, and -TPSS results. Furthermore, we propose selective scaling of OSIC (SOSIC) to remove its major shortcoming that destroys the -1/r asymptotic behavior of the potentials. The SOSIC method gives the highest occupied orbital eigenvalues practically identical to those in PZSIC and unlike OSIC provides bound atomic anions even with larger powers of scaling factors. Furthermore, SOSIC compared to PZSIC or OSIC provides more balanced description of total energies and barrier heights.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Laser-driven, ion-scale magnetospheres in laboratory plasmas. I. Experimental platform and first results

We report magnetospheres are a ubiquitous feature of magnetized bodies embedded in a plasma flow. While large planetary magnetospheres have been studied for decades by spacecraft, ion-scale “mini” magnetospheres can provide a unique environment to study kinetic-scale, collisionless plasma physics in the laboratory to help validate models of larger systems. In this work, we present preliminary experiments of ion-scale magnetospheres performed on a unique high-repetition-rate platform developed for the Large Plasma Device at the University of California, Los Angeles. The experiments utilize a high-repetition-rate laser to drive a fast plasma flow into a pulsed dipole magnetic field embedded in a uniform magnetized background plasma. 2D maps of the magnetic field with high spatial and temporal resolution are measured with magnetic flux probes to examine the evolution of magnetosphere and current density structures for a range of dipole and upstream parameters. The results are further compared to 2D particle-in-cell simulations to identify key observational signatures of the kinetic-scale structures and dynamics of the laser-driven plasma. We find that distinct 2D kinetic-scale magnetopause and diamagnetic current structures are formed at higher dipole moments, and their locations are consistent with predictions based on pressure balances and energy conservation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Mechanism for sequestering magnetic energy at large scales in shear-flow turbulence

Straining of magnetic fields by large-scale shear flow, which is generally assumed to lead to intensification and generation of small scales, is reexamined in light of the persistent observation of large-scale magnetic fields in astrophysics. It is shown that, in magnetohydrodynamic turbulence, unstable shear flows have the unexpected effect of sequestering magnetic energy at large scales due to counteracting straining motion of nonlinearly excited large-scale stable eigenmodes. This effect is quantified via dissipation rates, energy transfer rates, and visualizations of magnetic field evolution by artificially removing the stable modes. In conclusion, these analyses show that predictions based upon physics of the linear instability alone miss substantial dynamics, including those of magnetic fluctuations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

The role of breakup and coalescence in fine-scale bubble-induced turbulence. II. Kinematics

This second part of our research explores the kinematic aspect of fine-scale bubble-induced turbulence (BIT) to (i) present the effect of bubble breakup and coalescence and (ii) compare it against the universal kinematic fine-scale turbulence characteristics reported in the literature. To this end, we simulate a dilute bubbly system of 0.5% void fraction using two distinct numerical simulations. In the volume-of-fluid (VoF) simulation, bubbles undergo breakup and coalescence. In the immersed boundary method (IBM) simulation, however, they act as rigid spheres. We also perform a simulation of classical homogeneous isotropic turbulence (HIT). The first important outcome of this study is that BIT is radically different from HIT in terms of its kinematic fine-scale characteristics. In the vorticity-dominating regions, BIT exhibits a weak vortex stretching. This weak vortex stretching is due to (a) the intermediate strain-rate eigenvalues skewed weakly to positive and (b) the extensive strain-rate eigenvector aligning perpendicular to the vorticity vector. The BIT has, on average, not only a weak enstrophy production but also a weak strain production in strain-dominating regions. The weak strain production is due to (a) the presence of vortex stretching in highly strained fluid elements and (b) the absolute magnitude of compressive strain-rate eigenvalue being as close to the extensive strain-rate eigenvalue. Thus, none of the kinematic fine-scale HIT characteristics is noted for BIT. The second important conclusion is that bubble breakup and coalescence play little to no influence on the kinematics of fine-scale BIT as VoF and IBM simulations produce similar results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Invariant discovery of features across multiple length scales: Applications in microscopy and autonomous materials characterization

Physical imaging is a foundational characterization method in areas from condensed matter physics and chemistry to astronomy and spans length scales from atomic to universe. Images encapsulate crucial data regarding atomic bonding, materials microstructures, and dynamic phenomena such as microstructural evolution and turbulence, among other phenomena. The challenge lies in effectively extracting and interpreting this information. Variational Autoencoders (VAEs) have emerged as powerful tools for identifying the underlying factors of variation in image data, providing a systematic approach to distilling meaningful patterns from complex data sets. However, a significant hurdle in their application is the definition and selection of appropriate descriptors reflecting local structures. Here, we introduce the scale-invariant VAE approach (SI-VAE) based on the progressive training of the VAE with the descriptors sampled at different length scales. The SI-VAE allows the discovery of the length scale-dependent factors of variation in the system. Here, we illustrate this approach using the ferroelectric domain images and generalize it to the movies of the electron-beam induced phenomena in graphene and topography evolution across combinatorial libraries. This approach can further be used to initialize the decision making in automated experiments including structure–property discovery and can be applied across a broad range of imaging methods. This approach is universal and can be applied to any spatially resolved data including both experimental imaging studies and simulations, and can be particularly useful for exploration of phenomena such as turbulence and scale-invariant transformation fronts.

36 MATERIALS SCIENCE↗