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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Initialization and assimilation of cloud and rainwater in a regional model

The initialization and assimilation of cloud and rainwater quantities in a mesoscale regional model was examined. Forecasts of explicit cloud and rainwater are made using conservation equations. The physical processes include condensation, evaporation, autoconversion, accretion, and the removal of rainwater by fallout. These physical processes, some of which are parameterized, represent source and sink in terms in the conservation equations. The question of how to initialize the explicit liquid water calculations in numerical models and how to retain information about precipitation processes during the 4-D assimilation cycle are important issues that are addressed.

Raymond, William H.↗
DOE OSTI2025

Implementation of Triply Periodic Minimal Surfaces (TPMS) as surface objects in OpenMC

Triply Periodic Minimal Surfaces (TPMS) represent a promising geometry for future fuel designs due to their significant surface-to-volume ratio, which facilitates efficient cooling of nuclear fuel, a crucial factor for safety and efficiency. Demonstrating the remarkable capabilities of TPMS fuel requires initial modeling and simulation. This paper presents an implementation of TPMS in the Monte Carlo code OpenMC, enabling reactor physics modeling of TPMS. Here, the primary advantages over traditional methods using CAD files include reduced memory requirements for computations and high-fidelity implementation. This implementation has been tested against CAD files loaded in Serpent2, yielding promising results with low biases in the $k_{\textrm{eff}}$, comparable to biases in the material balance sheet. The implementation presented in this work will be used in future reactor physics computations related to new reactor designs involving TPMS-based fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Monitoring spatiotemporal evolution of fractures during hydraulic stimulations at the first EGS collab testbed using anisotropic elastic-waveform inversion

The EGS Collab project acquired continuous active-source seismic monitoring (CASSM) data before, during, and after hydraulic stimulations at the first testbed at the depth of 4850 ft (1478 m) at the Sanford Underground Research Facility in Lead, South Dakota, for monitoring fracture creation and evolution. CASSM acquisition was conducted using 24 hydrophones, 18 accelerometers, and 17 piezoelectric sources within four fracture-parallel wells and two orthogonal wells. 3D anisotropic traveltime tomography and anisotropic elastic-waveform inversion of the campaign cross-borehole seismic data show that the rock within the stimulation region is a heterogeneous horizontal transverse isotropic medium. Here we use these inversion results as the initial models and apply 3D anisotropic first-arrival traveltime tomography and 3D anisotropic elastic-waveform inversion to the CASSM data acquired after each stimulation in May, 2018 and December, 2018. We observe the spatiotemporal evolution of seismic velocities and anisotropic parameters caused by hydraulic fracture stimulations, showing the regions of rock alternation caused by hydraulic fracture stimulation.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

The local structure of 0.5Ba(Zr 0.2 Ti 0.8 )O 3 -0.5(Ba 0.7 Ca 0.3 )TiO 3 from neutron total scattering measurements and multi-edge X-ray absorption analysis

Neutron total scattering measurements and multi-edge X-ray absorption analysis were performed on a 0.5Ba(Zr 0.2 Ti 0.8 )O 3 -0.5(Ba 0.7 Ca 0.3 )TiO 3 powder sample. The TiIII-II edges showed that titanium is distorted in the rhombohedral [111] direction (in a BaTiO 3 -like chemical and bonding environment). Extended X-ray fine structure analysis (EXAFS) was performed on the zirconium K-edge and it was found that zirconium resides in the center of the ZrO 6 octahedra in cubic symmetry. Furthermore, the local structure was initially modelled with the orthorhombic Amm2 space group with unsatisfactory results. To better model the local structure, the results from the EXAFS analysis were incorporated into the small-box pair distribution function (PDF) refinements and the best fit of the observed data was a combination of barium calcium titanate (BCT) and barium calcium zirconate (BCZ) phases.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Rise of Neural Networks for Materials and Chemical Dynamics

Machine learning (ML) is quickly becoming a premier tool for modeling chemical processes and materials. ML-based force fields, trained on large data sets of high-quality electron structure calculations, are particularly attractive due their unique combination of computational efficiency and physical accuracy. This Perspective summarizes some recent advances in the development of neural network-based interatomic potentials. Designing high-quality training data sets is crucial to overall model accuracy. One strategy is active learning, in which new data are automatically collected for atomic configurations that produce large ML uncertainties. Another strategy is to use the highest levels of quantum theory possible. Transfer learning allows training to a data set of mixed fidelity. A model initially trained to a large data set of density functional theory calculations can be significantly improved by retraining to a relatively small data set of expensive coupled cluster theory calculations. These advances are exemplified by applications to molecules and materials.

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

Strong Upper-Plate Heterogeneity at the Hikurangi Subduction Margin (North Island, New Zealand) Imaged by Adjoint Tomography

We use earthquake-based adjoint tomography to invert for three-dimensional structure of the North Island, New Zealand, and the adjacent Hikurangi subduction zone. The study area, having a shallow depth to the plate interface below the North Island, offers a rare opportunity for imaging material properties at an active subduction zone using land-based measurements. Starting from an initial model derived using ray tomography, we perform iterative model updates using spectral element and adjoint simulations to fit waveforms with periods ranging from 4–30 s. We perform 28 model updates using an L-BFGS optimization algorithm, improving data fit and introducing P- and S-wave velocity changes of up to ±30%. Resolution analysis using point spread functions show that our measurements are most sensitive to heterogeneities in the upper 30 km. The most striking velocity changes coincide with areas related to the active Hikurangi subduction zone. Lateral velocity structures in the upper 5 km correlate well with New Zealand geology. Here, the inversion reveals increased along-strike heterogeneity on the margin. In Cook Strait we observe a low-velocity zone interpreted as deep sedimentary basins. In the central North Island, low-velocity anomalies are linked to surface geology, and we relate velocity structures at depth to crustal magmatic activity below the Taupō Volcanic Zone.

58 GEOSCIENCES↗
DOE OSTI2023

Changes in Tropical Cyclones Undergoing Extratropical Transition in a Warming Climate: Quasi-Idealized Numerical Experiments of North Atlantic Landfalling Events

The current study extends earlier work that demonstrated future extratropical transition (ET) events will feature greater intensity and heavier precipitation to specifically consider potential changes in the impacts of landfalling ET events in a warming climate. A quasi-idealized modeling framework allows comparison of highly similar present-day and future event simulations; the model initial conditions are based on observational composites, increasing representativeness of the results. The future composite ET event features substantially more impactful weather conditions in coastal areas, with heavier precipitation and greater storm intensity. Specifically, a Category 2 present-day storm attained Category 4 Saffir-Simpson intensity in the future simulation and maintained greater intensity throughout the entire life cycle, although the storm undergoes less reintensification during the post-ET process, a result of reduced baroclinic conversion. These findings suggest increased potential for coastal hazards due to stronger tropical cyclone winds and heavier rainfall, leading to more severe coastal flooding and storm surge.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Corrugation-driven symmetry breaking in magic-angle twisted bilayer graphene

Abstract The discovery of unconventional superconductivity in magic-angle twisted bilayer graphene (tBLG) supported the twist-angle-induced flat band structure predictions made a decade earlier. Numerous physical properties have since been linked to the interlayer twist angle using the flat band prediction as a guideline. However, some key observations like the nematic phase and striped charge order behind the superconductivity are missing in this initial model. Here we show that a thermodynamically stable large out-of-plane displacement, or corrugation of the bilayer, induced by the interlayer twist, demonstrates partially filled states of the flat band structure, accompanied by a broken symmetry, in the magic-angle regime and the presence of symmetry breaking associated with the superconductivity in tBLG. The distinction between low and high corrugation can also explain the observed evolution of the vibrational spectra of tBLG as a function of twist angle. Our observation that large out-of-plane deformation modes enable partial filling of states near the Fermi energy may lead to a strategy for offsetting the effects of disorder in the local twist angle, which suppresses unconventional superconductivity and correlated insulator behavior in magic-angle tBLG.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Tailoring diesel bioblendstock from integrated catalytic upgrading of carboxylic acids: a “fuel property first” approach

Abstract Lignocellulosic biomass offers the potential to produce renewable fuels at a scale commensurate with petroleum consumption. Hybrid approaches that combine biological and chemocatalytic processes have garnered increasing attention due to their flexibility for feedstock utilization and diversity of potential products. Of note, lignocellulosic sugars can be converted biologically to short-chain carboxylic acids, while subsequent chemocatalytic upgrading can elongate the carbon backbone and remove oxygen from the structure to produce drop-in hydrocarbon fuels. However, hybrid conversion processes are typically not designed with the fuel properties in mind a priori . In this work, we apply a “fuel property first” design approach to produce a tailored hydrocarbon bioblendstock with lower intrinsic sooting and drop-in diesel fuel potential. Initially, model predictions for six fuel properties critical to diesel applications (physicochemical requirements, energy content, safety considerations, autoignition ability, and sooting tendency) were used to screen an array of hydrocarbons accessible from upgrading individual and mixed C 2 /C 4 acids. This screening step allowed for down-selection to a non-cyclic branched C 14 hydrocarbon (5-ethyl-4-propylnonane) that can be synthesized from butyric acid through sequential catalytic reactions of acid ketonization, ketone condensation, and hydrodeoxygenation. Following evaluation of each conversion step with model compounds, butyric acid was then converted through an integrated catalytic process scheme to achieve >80% overall carbon yield to a hydrocarbon mixture product containing >60% of the target C 14 hydrocarbon. The potential of this conversion strategy to produce a hydrocarbon diesel bioblendstock from lignocellulosic biomass was then demonstrated using corn stover-derived butyric acid produced from Clostridium butyricum fermentation. Experimental fuel property testing of the purified C 14 blendstock validated the majority of the fuel property model predictions, including <50% of the intrinsic sooting tendency when compared to conventional diesel. Meanwhile, the crude conversion product met fuel property target metrics, validating conversion process development. When the C 14 bioblendstock was blended into a petroleum diesel at 20 vol.%, the blend maintained low cloud point, high energy density, and cetane number. Notably, the blend reduced sooting tendency by more than 10%, highlighting the potential of the tailored bioblendstock to reduce particulate emissions.

09 BIOMASS FUELS↗
DOE OSTI2022

Ponderomotive force driven density modifications parallel to B on the LAPD

The ponderomotive force has previously been identified as a possible driver of observed density modifications close to radio frequency actuators during operation. This nonlinear force redistributes density in regions of gradients in the magnitude of an oscillating electric field and describes the influence of the fast time scale RF wave dynamics on slow time scale plasma transport. Depletion of the saturation current (a proxy for the density) measured at the Large Plasma Device (LAPD) was 30–35% during ion cyclotron range of frequencies operation. A coupled 1D plasma transport and cold plasma frequency domain wave solver was developed to self-consistently describe ponderomotive effects and was used to compare with results obtained from the LAPD experiment. The scaled current density driver for the wave model yielded an RF B field in close agreement with two components of the experimental data. However, the 1D parallel model did not accurately reproduce the amplitude or spatial distribution observed in experimental measurements of By. Within the limitations of the 1D model, initial simulation results showed that the ponderomotive force depleted up to 8% for high power (1 MW) and around 1% for the experimental power of 120 kW. This could suggest that the ponderomotive force is not the main driver of density modification for the LAPD experiments presented in this paper. Higher fidelity tools of at least 2D will be required to give a more realistic description of the RF E fields and the effect of the ponderomotive force on the LAPD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Financial-technical co-design for capital-intensive, resource-responsive energy systems

Because of their capital-intensive operation, wind energy systems that are competitive in terms of the cost of the energy that they produce lead to risk-reward trade-offs that make their business cases less favorable than those of conventional energy generation technologies. However, wind energy systems tend to be designed to maximize energy production or minimize cost of energy rather than to maximize their business cases. In this work, we attempt to exploit designs specifically tailored to business cases. We develop a novel framework for analyzing energy systems that ties their design variables to monthly operating incomes using simple models and historical hourly market and resource data. Using this approach, we demonstrate that for a wind site with abundant wind resource in the California Independent System Operator market, we can control the trade-off between mean and 5th percentile monthly returns by choosing the specific power of the turbine at a fixed modeled initial capital cost. Our framework gives a measure of the risk-reward spectrum of energy generation assets that could be built at a given site with respect to the sub-annual resource/market variation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Stellar population and metal production in AGN discs

ABSTRACT As gravitational wave detections increase the number of observed compact binaries (consisting of neutron stars or blacks), we begin to probe the different conditions producing these binaries. Most studies of compact remnant formation focus either on stellar collapse from the evolution of field binary stars in gas-free environments or on the formation of stars in clusters where dynamical interactions capture the compact objects, forming binaries. But a third scenario exists. In this paper, we study the fate of massive stars formed, accrete gas, and evolve in the dense discs surrounding supermassive black holes. We calculate the explosions produced and compact objects formed by the collapse of these massive stars. Nucleosynthetic yields may provide an ideal, directly observable, diagnostic of the formation and fate of these stars in active galactic nuclei. We present a first study of the explosive yields from these stars, comparing these yields with the observed nucleosynthetic signatures in the discs around supermassive stars with quasars. We show that, even though these stars tend to form black holes, their rapid rotation leads to discs that can eject a considerable amount of iron during the collapse of the star. The nucleosynthetic yields from these stars can produce constraints on the number of systems formed in this manner, but further work is needed to exploit variations from the initial models presented in this paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Longitudinal dynamics and particle production in relativistic nuclear collisions

This work presents a three-dimensional dynamical initialization model for relativistic heavy-ion collisions, implementing local energy-momentum conservation and baryon charge fluctuations at string junctions. Constraining parameters using experimental data from p + p collisions at various collision energies, the model provides a very good description of the charged hadron and net proton rapidity distributions in Au +Au collisions from 7.7 to 200 GeV and Pb + Pb collisions at 8.77 and 17.3 GeV. Here we demonstrate the importance of fluctuations of baryon densities to string junctions for describing net-proton distributions at collision energies of 62.4 and 200 GeV. Including this improved baryon stopping description along with the requirement of strangeness neutrality also yields a good description of identified particle yields as functions of the collision energy above 7.7 GeV. We further study asymmetric p + Al and (p,d, 3 He) + Au collisions at the top RHIC energy and p + Pb, Xe + Xe, and Pb + Pb collisions at LHC energies. We identify the produced particle rapidity distributions in asymmetric collision systems as particularly useful for constraining models of the early-time longitudinal dynamics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Learning Heterogeneous Features Jointly: A Deep End-to-End Framework for Multi-Step Short-Term Wind Power Prediction

Leveraging multiple heterogeneous measurements to predict wind power has long been a challenging task in the electrical community. In this paper, a deep architecture incorporated with multitask learning and multimodal learning for wind power prediction, termed predictive stacked autoencoder (PSAE), is presented. PSAE is a unified framework integrating multiple stacked autoencoders (SAEs), one feature fusion layer, and one prediction terminal layer, which expands the architecture from two spatial dimensions, including the depth and width, compared to conventional prediction models. Initially, the SAEs at the bottom of PSAE extracted features from multiple kinds of measurements respectively. Following, the feature fusion layer encodes the high-order features extracted by different SAEs into a unified feature that is more informative and representative for wind power prediction. Finally, the prediction terminal layer functions as a regression machine which generates the predicted targets based on the fusion features. Trained in an end-to-end (E2E) manner, PSAE is capable of learning heterogeneous features jointly and achieving the prediction task of sequence-to-sequence (S2S). Experiments for multi-step short-term predictions are conducted on real-world data, and the results demonstrate the superiority of PSAE to prior methods.

17 WIND ENERGY↗
DOE OSTI2025

sup3ruhi (Super Resolution for Renewable Resource Data and Urban Heat Islands) [SWR-25-05]

Urban heat is a growing concern, particularly in dense metropolitan areas where high temperatures increase the risk of heat-related illness and drive energy expenses for cooling. Estimating the effects of urban heat remains a challenge due to limitations in describing the built environment, computational constraints, and the need for high-resolution data. This software presents open-source, computationally efficient machine learning methods that enhance the accuracy of urban temperature estimates compared to historical reanalysis data. Models trained using this software have been applied to urban microclimates in Los Angeles and Seattle showing greater accuracy and less bias when compared to low-resolution reanalysis datasets like ERA5 and even when compared to high-resolution mesoscale numerical weather models like WRF with an urban canopy model. Initial findings highlight how machine learning can support urban heat resilience planning by enabling improved assessments of local heat islands, mitigation strategies, and their energy implications. This software is an extension of (sup3r). This software supports the following publication: Buster, Grant, et al. Tackling Extreme Urban Heat: A Machine Learning Approach to Assess the Impacts of Climate Change and the Efficacy of Climate Adaptation Strategies in Urban Microclimates. arXiv:2411.05952, arXiv, 8 Nov. 2024. arXiv.org, https://doi.org/10.48550/arXiv.2411.05952. And has related public data records available at: Buster, Grant, Cox, Jordan, Benton, Brandon, and King, Ryan. Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI). United States: N.p., 16 Oct, 2024. Web. https://data.openei.org/submissions/6220.

Buster, Grant [National Renewable Energy Laborator↗
DOE OSTI2022

Classification of Cloud Particle Imagery from Aircraft Platforms Using Convolutional Neural Networks

Abstract A vast amount of ice crystal imagery exists from a variety of field campaign initiatives that can be utilized for cloud microphysical research. Here, nine convolutional neural networks are used to classify particles into nine regimes on over 10 million images from the Cloud Particle Imager probe, including liquid and frozen states and particles with evidence of riming. A transfer learning approach proves that the Visual Geometry Group (VGG-16) network best classifies imagery with respect to multiple performance metrics. Classification accuracies on a validation dataset reach 97% and surpass traditional automated classification. Furthermore, after initial model training and preprocessing, 10 000 images can be classified in approximately 35 s using 20 central processing unit cores and two graphics processing units, which reaches real-time classification capabilities. Statistical analysis of the classified images indicates that a large portion (57%) of the dataset is unusable, meaning the images are too blurry or represent indistinguishable small fragments. In addition, 19% of the dataset is classified as liquid drops. After removal of fragments, blurry images, and cloud drops, 38% of the remaining ice particles are largely intersecting the image border (≥10% cutoff) and therefore are considered unusable because of the inability to properly classify and dimensionalize. After this filtering, an unprecedented database of 1 560 364 images across all campaigns is available for parameter extraction and bulk statistics on specific particle types in a wide variety of storm systems, which can act to improve the current state of microphysical parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

GEFSv12 High- and Low-Skill Day-10 Tornado Forecasts

Abstract On average, modern numerical weather prediction forecasts for daily tornado frequency exhibit no skill beyond day 10. However, in this extended-range lead window, there are particular model cycles that have exceptionally high forecast skill for tornadoes because of their ability to correctly simulate the future synoptic pattern. Here, model initial conditions that produced a more skillful forecast for tornadoes over the United States were exploited while also highlighting potential causes for low-skill cycles within the Global Ensemble Forecasting System, version 12 (GEFSv12). There were 88 high-skill and 91 low-skill forecasts in which the verifying day-10 synoptic pattern for tornado conditions revealed a western U.S. thermal trough and an eastern U.S. thermal ridge, a favorable configuration for tornadic storm occurrence. Initial conditions for high skill forecasts tended to exhibit warmer sea surface temperatures throughout the tropical Pacific Ocean and Gulf of Mexico, an active Madden–Julian oscillation, and significant modulation of Earth-relative atmospheric angular momentum. Low-skill forecasts were often initialized during La Niña and negative Pacific decadal oscillation conditions. Significant atmospheric blocking over eastern Russia—in which the GEFSv12 overforecast the duration and characteristics of the downstream flow—was a common physical process associated with low-skill forecasts. This work helps to increase our understanding of the common causes of high- or low-skill extended-range tornado forecasts and could serve as a helpful tool for operational forecasters. Significance Statement This research provides a framework for the anticipation of a more (or less) skillful 10-day tornado forecast in an operational numerical weather prediction system. High-skill forecasts were associated with substantial tropical convection and warm sea surface temperature throughout the Pacific Ocean and Gulf of Mexico, whereas the underlying cause of low-skill forecasts were typically associated with a blocking anticyclone over eastern Russia. These findings are important because they permit increased or decreased confidence in a long-range forecast of tornado occurrence based on a dynamical prediction system.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

Chimera D-Series Gravitational Wave Emission Sourced from Neutrino Anisotropy

Gravitational wave data sourced from the time-dependent anisotropic neutrino emission, as well as the time-dependent fluid quadrupole motion, in the Chimera D-Series three-dimensional core collapse supernova simulations. Data from three models initiated from three different progenitors are presented: D9.6-3D, D15-3D, and D25-3D. Please see the README for more information about the data structure and progenitors.

79 ASTRONOMY AND ASTROPHYSICS↗