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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Fast meta-solvers for 3D complex-shape scatterers using neural operators trained on a non-scattering problem

Three-dimensional target identification using scattering techniques requires high accuracy solutions and very fast computations for real-time predictions in some critical applications. We first train a deep neural operator (DeepONet) to solve wave propagation problems described by the Helmholtz equation in a domain without scatterers but at different wavenumbers and with a complex absorbing boundary condition. We then design two classes of fast meta-solvers by combining DeepONet with either relaxation methods, such as Jacobi and Gauss-Seidel, or with Krylov methods, such as GMRES and BiCGStab, using the trunk basis of DeepONet as a coarse-scale preconditioner. We leverage the spectral bias of neural networks to account for the lower part of the spectrum in the error distribution while the upper part is handled inexpensively using relaxation methods or fine-scale preconditioners. The meta-solvers are then applied to solve scattering problems with different shape of scatterers, at no extra training cost. We first demonstrate that the resulting meta-solvers are shape-agnostic, fast, and robust, whereas the standard standalone solvers may even fail to converge without the DeepONet. We then apply both classes of meta-solvers to scattering from a submarine, a complex three-dimensional problem. We achieve very fast solutions, especially with the DeepONet-Krylov methods, which require orders of magnitude fewer iterations than any of the standalone solvers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Impacts of Spatial Resolution in a High-Fidelity Capacity Expansion Model: An ERCOT Case Study

Capacity expansion models are important tools in examining the evolution of the electric power sector. Embedded in these tools are many modeling choices with consequential impacts on computational burden and associated analysis. In this study, we adjust the spatial resolution of the Regional Energy Deployment System (ReEDS) to understand the implications of higher-fidelity modeling on energy system projections and model solve times. The native ReEDS regions capture the contiguous United States in 134 balancing areas whereas the regions in the higher-resolution version are defined by over 3,000 U.S. counties. Using both resolutions, we conduct a case study of the Texas Interconnection (The Electric Reliability Council of Texas [ERCOT]) to explore differences in model projections and to inform appropriate applications of high spatial resolution in a large-scale, applied capacity expansion model.

county↗
DOE OSTI2025

Structural differences between human and mouse neurons and their implementation in generative AIs

Mouse and human brains have different functions that depend on their neuronal networks. We analyzed nanometer-scale three-dimensional structures of brain tissues of the mouse medial prefrontal cortex and compared them with structures of the human anterior cingulate cortex. The obtained results indicated that mouse neuronal somata are smaller and neurites are thinner than those of human neurons. We implemented these characteristics of mouse neurons in convolutional layers of a generative adversarial network (GAN) and a denoising diffusion implicit model (DDIM), which were then subjected to image generation tasks using photo datasets of cat faces, cheese, human faces, birds, and automobiles. The mouse-mimetic GAN outperformed a standard GAN in the image generation task using the cat faces and cheese photo datasets, but underperformed for human faces and birds. The mouse-mimetic DDIM gave similar results, suggesting that the nature of the datasets affected the results. Analyses of the five datasets indicated differences in their image entropy, which should influence the number of parameters required for image generation. The preferences of the mouse-mimetic AIs coincided with the impressions commonly associated with mice. The relationship between the neuronal network and brain function should be investigated by implementing other biological findings in artificial neural networks.

generative AI↗
DOE OSTI2024

Durability testing of actual Hanford waste glasses and their non-radioactive simulant glasses

The low-activity waste (LAW) fraction of Hanford tank waste will be converted to glass at the Waste Treatment and Immobilization Plant (WTP) and disposed on the Hanford site. The chemical durability of LAW glasses has been researched for decades to satisfy contract requirements. Most LAW glass durability data has been generated on non-radioactive simulant glasses fabricated via crucible melts. These non-radioactive glasses were chosen due to safety and cost reasons with confidence that radioactive waste glasses would exhibit similar behavior. To reduce the risk of significant differences in laboratory test response data between WTP melter waste glass and simulant glass, Product Consistency Tests (PCT, i.e., ASTM C1285-21) and Environmental Protection Agency (EPA) 1313 durability tests were performed on actual and simulant LAW glasses fabricated using laboratory-scaled melters. Actual and simulant glass durability test results are presented and statistically compared. Finally, differences in test responses were found to be within experimental uncertainty.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

A Phase-Field Study on Internal to External Oxidation Transition in High-Temperature Structural Alloys

Structural alloys applied at high temperatures rely on an external dense layer of oxide scale for protection. As some reactive alloy components are selectively oxidized internally, understanding how these dispersed metal oxide particles reach the surface to form a protective scale—the so-called internal to external oxidation transition—is crucial for designing these alloys. While the literature is replete with experimental studies on oxidation of alloys, there is a lack of computational studies in this realm due to the complex nature of coupled reaction and diffusion processes in multicomponent multi-phase alloy systems. In this work, we apply a recently developed phase-field model to simulate the oxidation processes under different compositions and nucleation scenarios to gain insights into how a continuous oxide scale can be established. The results show that while alloy composition is critical for internal to external oxidation transition, the oxide nuclei size, shape and distribution also have significant impact on the transition kinetics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantifying the Impact of Vertical Resolution on the Representation of Marine Boundary Layer Physics for Global-Scale Models

Abstract While GCM horizontal resolution has received the majority of scale improvements in recent years, ample evidence suggests that a model’s vertical resolution exerts a strong control on its ability to accurately simulate the physics of the marine boundary layer. Here we show that, regardless of parameter tuning, the ability of a single-column model (SCM) to simulate the subtropical marine boundary layer improves when its vertical resolution is improved. We introduce a novel objective tuning technique to optimize the parameters of an SCM against profiles of temperature and moisture and their turbulent fluxes, horizontal winds, cloud water, and rainwater from large-eddy simulations (LES). We use this method to identify optimal parameters for simulating marine stratocumulus and shallow cumulus. The novel tuning method utilizes an objective performance metric that accounts for the uncertainty in the LES output, including the covariability between model variables. Optimization is performed independently for different vertical grid spacings and value of time step, ranging from coarse scales often used in current global models (120 m, 180 s) to fine scales often used in parameterization development and large-eddy simulations (10 m, 15 s). Uncertainty-weighted disagreement between the SCM and LES decreases by a factor of ∼5 when vertical grid spacing is improved from 120 to 10 m, with time step reductions being of secondary importance. Model performance is shown to converge at a vertical grid spacing of 20 m, with further refinements to 10 m leading to little further improvement. Significance Statement In successive generations of computer models that simulate Earth’s atmosphere, improvements have been mainly accomplished by reducing the horizontal sizes of discretized grid boxes, while the vertical grid spacing has seen comparatively lesser refinements. Here we advocate for additional attention to be paid to the number of vertical layers in these models, especially in the model layers closest to Earth’s surface where climatologically important marine stratocumulus and shallow cumulus clouds reside. Our experiments show that the ability of a one-dimensional model to represent physical processes important to these clouds is strongly dependent on the model’s vertical grid spacing.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Perturbation theory models for LSST-era galaxy clustering: Tests with subpercent mock catalog measurements in Fourier and configuration space

Here, we analyze the clustering of galaxies using the z = 1.006 snapshot of the CosmoDC2 simulation, a high-fidelity synthetic galaxy catalog designed to validate analysis methods for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). We present sub-percent measurements of the galaxy auto-correlation and galaxy-dark matter cross correlations in Fourier space and configuration space for a magnitude-limited galaxy sample. At these levels of precision, the statistical errors of the measurement are comparable to the systematic effects present in the simulation and measurement procedure; nevertheless, using a hybrid-PT model, we are able to model non-linear galaxy bias with 0.5% precision up to scales of k max = 0.5 h/Mpc and r min = 4 Mpc/h. While the linear bias parameter is measured with 0.01% precision, other bias parameters are determined with considerably weaker constraints and sometimes bimodal posterior distributions. We compare our fiducial model with lower dimensional models where the higher-order bias parameters are fixed at their co-evolution values and find that leaving these parameters free provides significant improvements in our ability to model small scale information. We also compare bias parameters for galaxy samples defined using different magnitude bands and find agreement between samples containing equal numbers of galaxies. Finally, we compare bias parameters between Fourier space and configuration space and find moderate to significant tension between the two approaches. Although our model is often unable to fit the CosmoDC2 galaxy samples within the 0.1% precision of our measurements, our results suggest that the hybrid-PT model used in this analysis is capable of modeling non-linear galaxy bias within the percent level precision needed for upcoming galaxy surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Statistical Treatment of Convolutional Neural Network Superresolution of Inland Surface Wind for Subgrid-Scale Variability Quantification

Abstract Machine learning models have been employed to perform either physics-free data-driven or hybrid dynamical downscaling of climate data. Most of these implementations operate over relatively small downscaling factors because of the challenge of recovering fine-scale information from coarse data. This limits their compatibility with many global climate model outputs, often available between ∼50- and 100-km resolution, to scales of interest such as cloud resolving or urban scales. This study systematically examines the capability of a type of superresolving convolutional neural network (SR-CNNs) to downscale surface wind speed data over land from different coarse resolutions (25-, 48-, and 100-km resolution) to 3 km. For each downscaling factor, we consider three convolutional neural network (CNN) configurations that generate superresolved predictions of fine-scale wind speed, which take between one and three input fields: coarse wind speed, fine-scale topography, and diurnal cycle. In addition to fine-scale wind speeds, probability density function parameters are generated through which sample wind speeds can be generated, accounting for the intrinsic stochasticity of wind speed. For assessing generalization to new data, CNN models are tested on regions with different topography and climate that are unseen during training. The evaluation of superresolved predictions focuses on subgrid-scale variability and the recovery of extremes. Models with coarse wind and fine topography as inputs exhibit the best performance when compared with other model configurations, operating across the same downscaling factor. Our diurnal cycle encoding results in lower out-of-sample generalizability when compared with other input configurations.

17 WIND ENERGY↗
DOE OSTI2021

Experimental Investigation of Polymer Induced Fouling of Heater Tubes in the First-Ever Polymer Flood Pilot on Alaska North Slope

Mineral fouling in heat exchangers has been extensively investigated by researchers in recent times. The oil and gas industry has a long history of fouling issues in production systems as a result of produced fluids treatment. Due to decline in production rates in oilfields new technologies are being developed and field tested in pilots. Polymer flooding is one such technology that involves addition of polymers to injection fluids to enhance oil production. A polymer flood pilot has been set up in the Schrader Bluff viscous oil reservoir at Milne Point field on the Alaska North Slope (ANS). The results from the pilot are encouraging, however a major concern of the operator is the influence of polymer on the production system after breakthrough, especially the fouling in heat exchangers. This study investigates the propensity of polymer fouling on the heater tubes as a function of different variables, with the ultimate goal of determining safe and efficient operating conditions. This work applies a multi-experimental approach to study the severity of polymer-induced fouling in both dynamic and static states of produced fluids as well as studying the stability of polymer solutions at different temperatures. A unique experimental setup was designed and developed in-house to simulate the fouling process on the heating tube. The influence of heating tube skin temperature, tube material, and polymer concentration on fouling tendency was investigated. Each test was run five times with the same tube, and in each run, the freshly prepared synthetic brine and polymer solution was heated from 77°F to 122°F to mimic field-operating conditions. The heating time and fouling amount were recorded for each run. Dynamic Scale Loop (DSL) tests were conducted to study fouling due to polymer at different temperatures (165°F to 350°F) in a dynamic state of fluid flow where the fluids mimic the residence time of fluids in the heat exchanger on the field pilot. Cloud point measurement has also been conducted to find the critical temperature at which the polymer in solution becomes unstable and precipitates out. The morphology and composition of the deposit samples were analyzed by environmental scanning electron microscopy (ESEM) and X-ray diffraction (XRD), respectively. It was found that the presence of polymer in produced fluids would aggravate the fouling issues on both carbon steel and stainless-steel surfaces at all tested skin temperatures. Only higher skin temperatures of 250°F and 350°F could cause polymer-induced fouling issues on the copper tube surface, and the fouling tendency increased with polymer concentration. At the lower skin temperatures of 165°F, no polymer-induced fouling was identified on the copper tube. A critical temperature that is related to the cloud point of the polymer solution was believed to exist, below which polymer-induced fouling would not occur, and only mineral scale was deposited but above which the polymer would aggravate the fouling issue. The cloud point of the tested polymer solution was determined to be between 220°F and 230°F. In the DSL tests it was found that at higher skin temperatures of 250°F and 350°F tube blocking was observed in the DSL tests whereas the tests at 165°F and 200°F did not show any tube blocking in the same time period. These experiments also manifested the influence of cloud point of the solution as deposit rate increased significantly in both carbon steel and stainless-steel tubes when the skin temperature was higher than the solution cloud point. The results of this study have provided guidance to the operator for the field-operations.

Dhaliwal, Anshul↗
DOE OSTI2022

Pressure–Strain Interaction as the Energy Dissipation Estimate in Collisionless Plasma

The dissipative mechanism in weakly collisional plasma is a topic that pervades decades of studies without a consensus solution. We compare several energy dissipation estimates based on energy transfer processes in plasma turbulence and provide justification for the pressure–strain interaction as a direct estimate of the energy dissipation rate. The global and scale-by-scale energy balances are examined in 2.5D and 3D kinetic simulations. We show that the global internal energy increase and the temperature enhancement of each species are directly tracked by the pressure–strain interaction. The incompressive part of the pressure–strain interaction dominates over its compressive part in all simulations considered. The scale-by-scale energy balance is quantified by scale filtered Vlasov–Maxwell equations, a kinetic plasma approach, and the lag dependent von Kármán–Howarth equation, an approach based on fluid models. We find that the energy balance is exactly satisfied across all scales, but the lack of a well-defined inertial range influences the distribution of the energy budget among different terms in the inertial range. Therefore, the widespread use of the Yaglom relation in estimating the dissipation rate is questionable in some cases, especially when the scale separation in the system is not clearly defined. In contrast, the pressure–strain interaction balances exactly the dissipation rate at kinetic scales regardless of the scale separation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Equivalent equilibrium ion distributions in ion sources and beams

Ion sources and ion beams often contain ions of more than one charge-to-mass ratio, due to the presence of multiple ionization states and/or multiple atomic and molecular ion species in the source. We show that, under certain conditions, analysis of these systems can be simplified using the notion of “equivalent equilibrium ion distributions” (EEIDs). These distributions have identical ion trajectories, space-charge distributions, and electric-field distributions, but can be composed of ion species with arbitrary charge-to-mass ratios. We use this result to obtain multi-species generalizations for the perveance of an ion diode, which relates the diode voltage to the extracted beam current, and for the perveance of a drifting ion beam, which determines the axial length-scale for beam expansion due to the self-electric field. Applied to a quasi-neutral plasma ion source containing cold ions and hot electrons, we find that the location of the beam-plasma interface (meniscus), where ions are extracted from the plasma, depends on the electron density and ion energy per unit charge at the interface, independent of the ion composition. For certain types of numerical simulations, EEIDs allow one to calculate the beam optics of an intense multi-species ion source by doing a simulation for a single ion species with an artificial charge-to-mass ratio chosen to minimize computation time. We illustrate these results using the 3D particle-in-cell, finite-element code Aleph. The simulations show how ions in a plasma source self-consistently accelerate to the supersonic speed needed for steady, radially expanding flow. Multi-species equilibria are subject to streaming instabilities because, while the different species have the same kinetic energy per unit charge, their velocities scale with the square root of the charge-to-mass ratio. The simulations show that a strong ion streaming instability can occur in a multi-species plasma ion source.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Mechanisms of phosphate removal by Micron-Scale Zero-Valent iron

Extensive studies have been carried out on phosphate removal by zero valent iron (ZVI). Different mechanisms of phosphate removal by ZVI such as phosphate adsorption and precipitation of ferric phosphate and vivianite (Fe 3 (PO 4 ) 2 ·8H 2 O) have been reported. In this study, attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), X-ray powder diffraction (XRD), and X-ray absorption near edge spectroscopy (XANES) were used to elucidate the mechanisms of phosphate removal by micron-scale zero-valent (mZVI). Time-series ATR-FTIR analysis revealed that phosphate was removed by ZVI in two steps: a) adsorption of phosphate in the first 3 days, and b) slow conversion of the adsorbed phosphate into the precipitated form in 6 days. XRD and XANES analysis determined that iron oxides, ferric ion, and ZVI with oxide layer inhibited the formation of vivianite, resulting in the formation of phosphate precipitates, such as H 2 Fe(II)P 2 O 7 . The results suggested that phosphate is removed by ZVI mainly through precipitation under aerobic conditions. In conclusion, the knowledge gained in this study improves the fundamental understanding of the phosphate removal processes via ZVI.

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

cm 2 -Scale Synthesis of MoTe 2 Thin Films with Large Grains and Layer Control

Owing to the small energy differences between its polymorphs, MoTe 2 can access a full spectrum of electronic states from the 2H semiconducting state to the 1T' semimetallic state and from the T d Weyl semimetallic state to the superconducting state in the 1T' and T d phase at low temperature. Thus, it is a model system for phase transformation studies as well as quantum phenomena such as the quantum spin Hall effect and topological superconductivity. Careful studies of MoTe 2 and its potential applications require large-area MoTe 2 thin films with high crystallinity and thickness control. Here, we present cm 2 -scale synthesis of 2H-MoTe 2 thin films with layer control and large grains that span several microns. Layer control is achieved by controlling the initial thickness of the precursor MoO x thin films, which are deposited on sapphire substrates by atomic layer deposition and subsequently tellurized. Despite the van der Waals epitaxy, the precursor–substrate interface is found to critically determine the uniformity in thickness and grain size of the resulting MoTe 2 films: MoTe 2 grown on sapphire show uniform films while MoTe 2 grown on amorphous SiO 2 substrates form islands. Furthermore, this synthesis strategy decouples the layer control from the variabilities of growth conditions for robust growth results and is applicable to growing other transition-metal dichalcogenides with layer control.

2D materials↗
DOE OSTI2020

Interspecies Microbial Fusion and Large-Scale Exchange of Cytoplasmic Proteins and RNA in a Syntrophic Clostridium Coculture

We report that two different bacterial organisms engage in heterologous cell fusion that leads to massive exchange of cellular material, including proteins and RNA, and the formation of persistent hybrid cells. The interspecies cell fusion observed here involves a syntrophic microbial system, but these heterologous cell fusions were observed even under nonstrict syntrophic conditions, leaving open the possibility that strict syntrophy may not be necessary for interspecies cell fusion and cellular material exchange. Formation of hybrid cells that contain proteins and RNA from both organisms is unexpected and unprecedented. Such fusion events are likely widely distributed in nature, but have gone undetected. The implications are profound and may shed light onto many unexplained phenomena in human health, natural environments, evolutionary biology, and biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Importance of Multiplicity Fluctuations in Entropy Scaling

One of the greatest uncertainties in heavy-ion collisions is the description of the initial state. Different models predict a wide range of initial energy density distributions based on their underlying assumptions. Final flow harmonics are sensitive to these differences in the initial state due to the nearly linear mapping between eccentricities and anisotropic flow harmonics. The Trento code uses a model-agnostic approach by phenomenologically parameterizing the initial state and constraining those parameters from a Bayesian analysis. There the multiplicity fluctuations were determined by a one parameter Γ distribution. However, initial-state models arising from the Color-Glass Condensate (CGC) framework lead to an initial energy density which is outside the functional form considered in Trento and its later Bayesian analyses because they rely on log-normal multiplicity fluctuations. We compare T A T B scaling (CGC-like) to √T A T B scaling (preferred from a Trento Bayesian analysis) and find that the T A T B form together with log-normal fluctuations is a reasonable candidate to describe the multiplicity fluctuations but leads to larger eccentricities, which would affect the extraction of viscosity in small systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Differences in Printed Contacts Lead to Susceptibility of Silicon Cells to Series Resistance Degradation

Here, in this case study, we investigate a degradation mode occurring at the cell level in fielded multi-Si modules. The modules exhibit a mix of affected and unaffected cells. Affected cells show a progressive, series-resistance-related power degradation as shown via module- and cell-level IV curves, along with electroluminescence (EL) and PL imaging at the module, cell, and cell core sample scales. Scanning electron microscopy and energy-dispersive X-ray spectroscopy reveal a difference in the oxides in the silver paste used in screen printing of the gridline contacts. The paste in the affected cells is lead rich, whereas the paste in the unaffected cells is zinc rich. This suggests that the cells were screen printed with different silver paste compositions and possibly firing conditions, and that the different composition correlates with the susceptibility to degradation. Our results indicate degradation of the contact at the oxide-silver interface, causing a severe increase in series resistance across the cell that continues to progress over time.

14 SOLAR ENERGY↗
DOE OSTI2026

Equivalent Point Sources for Simulating Nuclear/Radiological Search Operations

Modeling and simulation can be used to estimate the detection of different types and strengths of radioactive sources. Simulations of shielded gamma-ray sources in complex environments, such as searches in urban areas using vehicle-mounted detectors, can demonstrate what source strengths and shielding combinations should be able to be detected. For faster calculations, gamma-emitting sources that could have different shielding layers can be simulated ahead of time, resulting in equivalent point source emission distributions that can be used in larger simulation models. Larger-scale models will then run faster using equivalent point sources because the shielding layers around the sources have already been accounted for. Accompanying this paper are 260 equivalent point source emission files for 72 sources with different shielding layers, formatted for three different Monte Carlo codes. Users wanting to request versions of the SCALE and/or MCNP software can find details here: https://rsicc.ornl.gov/

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Assessing Clouds Using Satellite Observations Through Three Generations of Global Atmosphere Models

Abstract Clouds are parameterized in climate models using quantities on the model grid‐scale to approximate the cloud cover and impact on radiation. Because of the complexity of processes involved with clouds, these parameterizations are one of the key challenges in climate modeling. Differences in parameterizations of clouds are among the main contributors to the spread in climate sensitivity across models. In this work, the clouds in three generations of an atmosphere model lineage are evaluated against satellite observations. Satellite simulators are used within the model to provide an appropriate comparison with individual satellite products. In some respects, especially the top‐of‐atmosphere cloud radiative effect, the models show generational improvements. The most recent generation, represented by two distinct branches of development, exhibits some regional regressions in the cloud representation; in particular the southern ocean shows a positive bias in cloud cover. The two branches of model development show how choices during model development, both structural and parametric, lead to different cloud climatologies. Several evaluation strategies are used to quantify the spatial errors in terms of the large‐scale circulation and the cloud structure. The Earth mover's distance is proposed as a useful error metric for the passive satellite data products that provide cloud‐top pressure‐optical depth histograms. The cloud errors identified here may contribute to the high climate sensitivity in the Community Earth System Model, version 2 and in the Energy Exascale Earth System Model, version 1.

54 ENVIRONMENTAL SCIENCES↗