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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Characterization of flow and transport in a fracture network at the EGS Collab field experiment through stochastic modeling of tracer recovery

Energy extraction from subsurface reservoirs is important for addressing the increasing energy demand and environmental concerns such as global warming. However, the characterization of subsurface reservoirs, particularly reservoirs dominated by fracture networks remains a challenge due to the lack of means to directly observe subsurface processes. This study explores the feasibility and efficacy of characterizing fracture flow and transport processes in an enhanced geothermal system (EGS) testbed through stochastic tracer modeling. There are two enabling factors that allow application of stochastic modeling to characterize a subsurface reservoir. First, an abundance of geological and geophysical measurements enables the development of a high-fidelity and well-constrained fracture network model. Second, high-performance computing (HPC) allows running massive realizations efficiently. Six conservative tracer tests were stochastically modeled and produced satisfactory realizations that successfully reproduce field tracer recovery data from each tracer test. The evolution of flow and transport processes in the fracture network was then analyzed from these satisfactory realizations. This work demonstrates that stochastic tracer modeling on a high-fidelity fracture network model is feasible and can provide important insights regarding flow and transport characteristics in subsurface fractured reservoirs.

58 GEOSCIENCES↗
DOE OSTI2023

Design, performance, and cost savings of using GF-PC additively manufactured tooling for stamping of HSS 590 sheet metal

Conventional sheet metal forming tooling in the automotive industry is made up of hardened steel and used for mass-production. Prototype tooling made of metal is durable, but it is only used for a small number of parts despite its high cost, contributing heavily to the vehicle development cost. Additive Manufacturing (AM) offers a low-cost alternative for fabricating tooling suitable for low-volume production. Here, this study investigates the feasibility of using AM polymer composite tooling for the stamping of 1.5mm thickness HSS 590 steel sheets through a two-pronged approach – experimental and numerical analysis. Sheet metal stamping experiments were conducted with glass fiber reinforced polycarbonate (GF-PC) AM polymer tooling and their performance was evaluated based on various metrics such as tool deformation and part accuracy. Finite element simulations of the stamping process were performed, which accurately captured the tool deformations seen in experiments with the use of anisotropic material models. The effective use of simulations in optimizing process parameters to achieve the desired final part geometry is also demonstrated. The GF-PC AM polymer composite tooling was found to be well suited for low volume production applications with potential cost savings.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Quantitative measurement of pebble fuel anisotropy using generalized ellipsometry

The renewed development of high-temperature gas-cooled reactors has created a need to modernize pebble fuel quality control methods. One important specification in these methods is the coefficient of thermal expansion (CTE) anisotropy, which reflects graphite grain alignment and affects fuel performance. This study investigates the feasibility of using two-modulator generalized ellipsometry microscopy (2-MGEM) as a potential surrogate metric for CTE anisotropy. Graphite matrix compacts with controlled levels of anisotropy were fabricated by varying pre-pressures during forming and were subsequently characterized using both optical dilatometry and 2-MGEM. Measured responses were compared to an isotropic reference pebble produced using an industrial manufacturing process to provide a practical baseline. The resulting measurements revealed a strong quantitative correlation between the CTE anisotropy ratio and the corresponding diattenuation ratio. However, propagated measurement uncertainties in the optical method were found to limit definitive pass/fail discrimination, highlighting the need for improved precision before qualification as a quality control tool. Still, the results establish a quantitative relationship between optical and CTE anisotropy and support further development of 2-MGEM as a potential surrogate method for evaluating graphite matrix anisotropy in pebble fuel manufacturing.

Raftery, Alicia [ORNL] (ORCID:0000000259076427)↗
DOE OSTI2024

Applied radiation tags for warhead dismantlement transparency

Here, this study explores the feasibility of applying radiation tags as a Chain of Custody tool to confirm the dismantlement of individual warheads by investigating time dependent emissions from special nuclear material. Precedents of photon and neutron sources that have been used to irradiate warhead components are presented. Measurements of irradiated Highly Enriched Uranium (HEU) are used to benchmark simulations with the CINDER90 library for MCNP. Delayed gamma emissions are simulated as a function of time since irradiation of moderated HEU and Weapons Grade Plutonium with photon and neutron sources. Models of commercial 9 MV and 15 MV linacs were found to induce ~10 9 fissions/g and ~10 11 fissions/g, respectively, creating 3 to 4 orders of magnitude more delayed gammas than neutron sources, modeled at 10 10 n/s. However, a DT neutron source was found to induce sufficient fissions, ~10 7 fissions/g, to create quantifiable signatures relative to intrinsic emissions. Applied radiation tagging is determined to be technically feasible, but its operational context and practical implementation requires significant development.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Feasibility of full-core pin resolved CFD simulations of small modular reactor with momentum sources

Complex flow structure interactions and heat transfer processes take place in nuclear reactor cores. Given the extreme pressure/temperature and radioactive conditions inside the core, numerical simulations offer an attractive and sometimes more feasible approach to study the related flow and heat transfer phenomena in addition to the experiments. Under the Exascale Computing Project, the full-core simulation of a small modular reactor (SMR) has been pursued coupling Computational Fluid Dynamics (CFD) and neutronics. A key aspect of the modeling of SMR fuel assemblies is the presence of spacer grids and the mixing promoted by mixing vanes or the equivalent. A reduced order methodology is adopted based on momentum sources to mimic the mixing of the vanes. The momentum sources have been carefully calibrated with detailed Large Eddy Simulations (LES) of spacer grids performed with Nek5000. Modeling the spacer grid and mixing vanes (SGMV) effect without body-fitted computational grid avoids the excessive costs in resolving the local geometric details, and thus supports the simulation to be scaled up to the full core. Besides the progress on momentum source modeling, this paper also features the first full-core pin resolved CFD simulation ever performed to the authors' knowledge. This represents a significant advancement in capability for the CFD of nuclear reactors, which will hopefully serve as an inspiration for further integrating high-fidelity numerical simulations in actual engineering designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Measurement of the low-energy antitriton inelastic cross section

In this Letter, the first measurement of the inelastic cross section for antitriton–nucleus interactions is reported, covering the momentum range of 0.8 ≤ p < 2.4 GeV/c. The measurement is carried out using data recorded with the ALICE detector in pp and Pb–Pb collisions at a centre-of-mass energy per nucleon of 13 TeV and 5.02 TeV, respectively. The detector material serves as an absorber for antitriton nuclei. The raw yield of (anti)triton nuclei measured with the ALICE apparatus is compared to the results from detailed ALICE simulations based on the GEANT4 toolkit for the propagation of (anti)particles through matter, allowing one to quantify the inelastic interaction probability in the detector material. This analysis complements the measurement of the inelastic cross section of antinuclei up to A = 3 carried out by the ALICE Collaboration, and demonstrates the feasibility of the study of the isospin dependence of inelastic interaction cross section with the analysis techniques presented in this Letter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Benchmarking of Solar Irradiance Nowcast Performance Derived from All-Sky Imagers

Fluctuations of the incoming solar irradiance impact the power generation from photovoltaic and concentrating solar thermal power plants. Accurate solar nowcasting becomes necessary to detect these sudden changes of generated power and to provide the desired information for optimal exploitation of solar systems. In the framework of the International Energy Agency's Photovoltaic Power Systems Program Task 16, a benchmarking exercise has been conducted relying on a bouquet of solar nowcasting methodologies by all-sky imagers (ASI). In this paper, four ASI systems nowcast the Global Horizontal Irradiance (GHI) with a time forecast ranging from 1 to 20 min during 28 days with variable cloud conditions spanning from September to November 2019 in southern Spain. All ASIs demonstrated their ability to accurately nowcast GHI, with RMSE ranging from 6.9% to 18.1%. Under cloudy conditions, all ASIs' nowcasts outperform the persistence models. Under clear skies, three ASIs are better than persistence. Discrepancies in the observed nowcasting performance become larger at increasing forecast horizons. The findings of this study highlight the feasibility of ASIs to reliably nowcast GHI at different sky conditions, time intervals and horizons. Such nowcasts can be used either to estimate solar power at distant times or detect sudden GHI fluctuations.

all-sky imagers↗
DOE OSTI2025

Utilization of the LS-APGD microplasma/orbitrap-FTMS booster system for detection and isotopic analysis of neodymium nanoparticles

Detection and isotopic analysis of particle populations has seen rapid growth across several application areas, including environmental analysis, nuclear forensics, and food safety. The ability to characterize the particles' unique elemental and isotopic fingerprints could provide information related to formation, processing history, and transport. Regarding nuclear forensics, isotopic analysis of particles derived from diverse materials is often used as a tool to trace the origin and processing history. Mass spectrometric-based techniques currently used for particle population analysis often suffer from limited mass resolution, particularly when dealing with real-world samples that are affected by isobaric and polyatomic interferences from the matrix. To address these analytical challenges, we propose a novel method utilizing the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma ionization source coupled to an ultrahigh resolution Orbitrap mass spectrometer, further enhanced with the FTMS X2T Booster data acquisition and processing unit. The FTMS Booster enables acquisition of extended transient times of up to 3 s, significantly improving mass resolution, thereby reducing or even eliminating the need for prior separation of isobaric or polyatomic interferences. Additionally, the detection of low-abundance isotopes was improved by increasing the signal-to-noise (S/N) ratio. As proof of concept, this study demonstrates the feasibility of the LS-APGD/Orbitrap-FTMS X2T Booster platform for direct analysis using a suspension of well-characterized ∼120 nm neodymium particles. The quality of the isotope ratios values obtained from a few hundred particles were in good agreement with those obtained from homogeneous ionic solutions. These results highlight the potential of the LS-APGD/Orbitrap platform for rapid, accurate, and interference-resilient isotope ratio analysis of particle populations without the need for dissolution and subsequent chemical separations, offering significant advantages for nuclear forensics, safeguards, and environmental applications. The effort here also points to further paths forward, hopefully towards single particle (SP) analysis using microplasma ionization and the ultrahigh resolving power of the Orbitrap mass analyzer.

FTMS X2T booster↗
DOE OSTI2023

Global fire modelling and control attributions based on the ensemble machine learning and satellite observations

Contemporary fire dynamics is one of the most complex and least understood land surface phenomena. Global fire controls related to climate, vegetation, and anthropogenic activity are usually intertwined, and difficult to disentangle in a quantitative way. Here, we leveraged an ensemble of five machine learning (ML) models and multiple satellite-based observations to conduct global fire modeling for three fire metrics (burned area, fire number, and fire size), and quantified driving mechanisms underlying annual fire changes in a spatially resolved manner for the period 2003–2019. Ensemble learning is a meta-approach that combines multiple ML predictions to improve accuracy, robustness, and generalization performance. We found that the optimized ensemble ML well reproduced annual dynamics of global burned area (R 2 = 0.90, P < 0.001), total fire numbers (R 2 = 0.86, P < 0.001), and averaged fire size (R 2 = 0.70, P < 0.001). Additionally, the ensemble ML captured key spatial patterns of multi-year mean magnitudes, annual variabilities, anomalies, and trends for different fire metrics. Our ML-based fire attributions further highlighted the dominant role of enhanced anthropogenic activity in reducing global burned area (–1.9 Mha/yr, P < 0.01), followed by climate control (–1.3 Mha/yr, P < 0.01) and insignificant positive vegetation control (0.4 Mha/yr, P = 0.60). Spatially, climate dominated a much larger burned area (53.7%) than human (23.4%) or vegetation control (22.9%); however, the counteracting effects from regional wetting and drying trends weakened the net climate impacts on global burned area. The fire number and fire size exhibited similar spatial control patterns with burned area; globally, however, fire number tended to be more affected by climate while fire size more influenced by human activities. Overall, our study confirmed the feasibility and efficiency of ensemble ML in global fire modeling and subsequent control attributions, providing a better understanding of contemporary fire regimes and contributing to robust fire projections in a changing environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Neural network reconstruction of the DIII-D tokamak plasma boundary using a reduced set of diagnostics

This study investigates the feasibility of reconstructing the last closed flux surface in the DIII-D tokamak using neural network models trained on reduced input feature sets, addressing an ill-posed task. Two models are compared: one trained solely on coil currents and another incorporating coil currents, plasma current and loop voltage. The model trained exclusively on coil currents achieved a mean point displacement of $0.04$ m on a held-out test set, while the inclusion of plasma current and loop voltage reduced the error to $0.03$ m. This comparison highlights the trade-offs between input feature complexity and reconstruction accuracy, demonstrating the potential of machine learning algorithms to perform effectively in data-limited environments, such as those expected in fusion power plants due to diagnostic constraints imposed by the presence of blankets and shielding.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Cometabolic Vinyl Chloride Degradation at Acidic pH Catalyzed by Acidophilic Methanotrophs Isolated from Alpine Peat Bogs

Remediation of toxic chlorinated ethenes via microbial reductive dechlorination can lead to ethene formation; however, the process stalls in acidic groundwater, leading to the accumulation of carcinogenic vinyl chloride (VC). This study explored the feasibility of cometabolic VC degradation by moderately acidophilic methanotrophs. Furthermore, two novel isolates, Methylomonas sp. strain JS1 and Methylocystis sp. strain MJC1, were obtained from distinct alpine peat bogs located in South Korea. Both isolates cometabolized VC with CH 4 as the primary substrate under oxic conditions at pH at or below 5.5. VC cometabolism in axenic cultures occurred in the presence (10 μM) or absence (<0.01 μM) of copper, suggesting that VC removal had little dependence on copper availability, which regulates expression and activity of soluble and particulate methane monooxygenases in methanotrophs. The model neutrophilic methanotroph Methylosinus trichosporium strain OB3b also grew and cometabolized VC at pH 5.0 regardless of copper availability. Bioaugmentation of acidic peat soil slurries with methanotroph isolates demonstrated enhanced VC degradation and VC consumption below the maximum concentration level of 2 μg L –1 . Community profiling of the microcosms suggested species-specific differences, indicating that robust bioaugmentation with methanotroph cultures requires further research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Bioactivity Profiling of Chemical Mixtures for Hazard Characterization

Abstract The assessment and regulation of chemical toxicity to protect human health and the environment are done one chemical at a time and seldom at environmentally relevant concentrations. However, chemicals are found in the environment as mixtures, and their toxicity is largely unknown. Understanding the hazard posed by chemicals within the mixture is critical to enforce protective measures. Here, we demonstrate the application of bioactivity profiling of environmental water samples using the sentinel and ecotoxicology model species Daphnia to reveal the biomolecular response induced by exposure to real-world mixtures. We exposed a Daphnia strain to 30 sampled waters of the Chaobai River and measured the gene expression response profiles. Using a multiblock correlation analysis, we establish correlations between chemical mixtures identified in 30 water samples with gene expression patterns induced by these chemical mixtures. We identified 80 metabolic pathways putatively activated by mixtures of inorganic ions, heavy metals, polycyclic aromatic hydrocarbons, industrial chemicals, and a set of biocides, pesticides, and pharmacologically active substances. Our data-driven approach discovered both known bioactivity signatures with previously described modes of action and new pathways linked to undiscovered potential hazards. This study demonstrates the feasibility of reducing the complexity of real-world mixture toxicity to characterize the biomolecular effects of a defined number of chemical components based on gene expression monitoring of the sentinel species Daphnia.

Engineering↗
DOE OSTI2026

Electrochemical Recovery of Rare-Earth Elements from Coal Fly Ash Using Ionic Liquids as both Extractant and Electrolyte

Rare-earth elements (REEs) are critical for medical technologies, electronics, and clean energy. Coal fly ash (CFA), a byproduct of coal combustion, offers a promising alternative REE source. However, efficient extraction and separation of REEs from CFA remain challenging due to the complex composition of CFA. This study introduces a sustainable method for REE recovery using a recyclable ionic liquid, betainium bis(trifluoromethylsulfonyl)imide ([Hbet]- [Tf 2 N]), which serves both as the extractant from CFA and as the electrolyte in electrodeposition. In the first stage, [Hbet][Tf 2 N] preferentially extracts REEs from CFA through leaching. In the second stage, the REE-enriched ionic liquid undergoes electrochemical deposition using amperometry techniques, where REEs are reduced and deposited onto the electrode. The deposition experiments were conducted from −0.5 to −2.0 V vs a Pt quasireference electrode in a three-electrode setup comprising titanium as the working electrode and platinum as both the reference and counter electrodes. Varying the applied potential enabled potential-dependent preferential REE deposition. At −0.5 V, neodymium (Nd) showed preferential recovery, reaching 25% with a separation factor of 37 over other REEs. In contrast, applying a more negative potential increased overall deposition, yielding ∼50% Nd recovery and 10−20% recovery for the remaining REEs. After recovery, the ionic liquid was regenerated and reused for a subsequent electrochemical recovery cycle. Overall, this study demonstrates a feasible approach for REE recovery from CFA waste, with potential to enhance resource utilization within the REE supply chain.

coal fly ash↗
DOE OSTI2023

Using Metadynamics to Reveal Extractant Conformational Free Energy Landscapes

Understanding the impact of extractant functionalization on metal-binding energetics in liquid-liquid extraction is essential to guide the development of better separation processes. Traditionally, computational extractant design uses electronic structure calculations on metal-ligand clusters to determine the metal-binding energy of the lowest energy state. Although highly accurate, this approach does not account for all of the relevant physics encountered under experimental conditions. Such methodologies often neglect entropic contributions such as temperature effects and ligand flexibility, in addition to approximating solvent-extractant interactions with implicit solvent models. In this study, we use classical molecular dynamics simulations with an advanced sampling method, metadynamics, to map out extractant molecule conformational free energies in the condensed phase. Here we generate the complete conformational landscape in solution for a family of bidentate malonamide-based extractants with different functionalizations of the headgroup and the side chains. In particular, we show how such alkyl functionalization reshapes the free energy landscape, affecting the free energy penalty of organizing the extractant into the cis-like metal-binding conformation from the trans-like conformation of the free extractant in solution. Specifically, functionalizing alkyl tails to the center of the headgroup has a greater influence on increasing molecular rigidity and disfavoring the binding conformation than functionalizing side chains. These findings are consistent with trends in metal-binding energetics based on experimentally reported distribution ratios. We also consider a different bidentate extractant molecule, carbamoylmethylphosphine oxide, and show how the choice of solvent can further reshape the conformational energetic landscape. This study demonstrates the feasibility of using molecular dynamics simulations with advanced sampling techniques to investigate extractant conformational energetics in solution, which, more broadly, will enable extractant design that accounts for entropic effects and explicit solvation.

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

Self-Assembled BaTiO 3 –Au x Ag 1– x Low-Loss Hybrid Plasmonic Metamaterials with an Ordered “Nano-Domino-like” Microstructure

Metallic plasmonic hybrid nanostructures have attracted enormous research interest due to the combined physical properties coming from different material components and the broad range of applications in nanophotonic and electronic devices. However, the high loss and narrow range of property tunability of the metallic hybrid materials have limited their practical applications. In this study, a metallic alloy-based self-assembled plasmonic hybrid nanostructure, i.e., a BaTiO 3 –Au x Ag 1– x (BTO) vertically aligned nanocomposite, has been integrated by a templated growth method for low-loss plasmonic systems. Comprehensive microstructural characterizations including high-resolution scanning transmission electron microscopy (HRSTEM), energy-dispersive X-ray spectroscopy (EDS), and three-dimensional (3D) electron tomography demonstrate the formation of an ordered “nano-domino-like” morphology with Au 0.4 Ag 0.6 nanopillars as cylindrical cores and BTO as square shells. By comparing with the BTO–Au hybrid thin film, the BTO–Au 0.4 Ag 0.6 alloyed film exhibits much broader plasmon resonance, hyperbolic dispersion, low-loss, and thermally robust features in the UV–vis–NIR wavelength region. This study provides a feasible platform for a complex alloyed plasmonic hybrid material design with low-loss and highly tunable optical properties toward all-optical integrated devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Superior Piezo-/Ferro-Electricity in Antiferroelectric Ag x NbO 3-δ Thin Films by Nanopillar Local Structure Design

Antiferroelectrics are fundamental mother compounds critical in developing innovative lead-free piezoelectrics and ferroelectrics and hold great promise for wide-ranging applications in energy conversion and electronic devices. However, harnessing their superior properties presents a significant challenge due to the delicate balance required between their various states. Here, in this study, through the unique design of nanopillar structures to alleviate the local polar heterogeneity, we have achieved significantly improved piezo-/ferro-electricity in classic lead-free antiferroelectric Ag x NbO 3-δ (x = 1, 0.9, and 0.8) epitaxial thin films. The effective piezoelectric coefficient reaches 440 pm V –1 , 1 order of magnitude larger than the stoichiometric AgNbO 3 , rivaling classic lead zirconate titanate piezoelectrics. Atomic-scale electron microscopy investigations unravel the underlying mechanisms. The nanopillars, characterized by antisite occupancy of both Ag and Nb atoms and forming out-of-phase boundaries with the matrix, reduce the local crystal symmetry via interphase strain. This leads to the creation of flexible multinanodomain structures that significantly facilitate polarization rotation, thus substantially enhancing the piezoelectric performance. This study demonstrates the feasibility of engineering local heterogeneity through nanopillar design, offering a generally applicable method for property improvement of a wide range of antiferroelectrics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Anaerobic Storage and Conversion of Microalgal Biomass to Manage Seasonal Variation in Cultivation

Seasonal variation in microalgal biomass production is a well-known challenge when optimizing economics for algal fuel conversion, especially given the fluctuation in biomass production between winter and summer. Wet storage offers significant potential for cost and energy savings compared to dewatering and dry storage. This study demonstrates the feasibility of preserving harvested Scenedesmus acutus biomass through wet anaerobic storage for use in biochemical conversion. Anaerobic storage effectively preserved biomass with minimal degradation of carbohydrates and preservation of lipids and proteins. Screening experiments identified optimal pretreatment conditions for stored biomass. Scale-up of pretreatment enabled fermentation of the hydrolysate to butyric acid and indicated no observable difference in conversion between unstored and stored biomass. Lipid extraction improved by a relative 12% for stored biomass. These results suggest that wet anaerobic storage can effectively manage seasonal variation in biomass production and is compatible with biochemical approaches for biofuel production.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Deep Learning Emulation of Subgrid-Scale Processes in Turbulent Shear Flows

Deep neural networks (DNNs) are developed from a data set obtained from the dynamic Smagorinsky model to emulate the subgrid-scale (SGS) viscosity (ν sgs ) and diffusivity (κ sgs ) for turbulent stratified shear flows encountered in the oceans and the atmosphere. These DNNs predict ν sgs and κ sgs from velocities, strain rates, and density gradients such that the evolution of the kinetic energy budget and density variance budget terms is similar to the corresponding values obtained from the original dynamic Smagorinsky model. These DNNs also compute ν sgs and κ sgs ~2–4 times quicker than the dynamic Smagorinsky model resulting in a ~2–2.5 times acceleration of the entire simulation. This study demonstrates the feasibility of deep learning in emulating the subgrid-scale (SGS) phenomenon in geophysical flows accurately in a cost-effective manner. In a broader perspective, deep learning-based surrogate models can present a promising alternative to the traditional parameterizations of the subgrid-scale processes in climate models.

58 GEOSCIENCES↗