SEARCH · Search NASA

Results for “Directional derivatives”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

All sources NASA NTRS DOE OSTI

DOE OSTI2026

Hofmann Stability Charts Revisited for PIP-II: From Classical Theory to Assumption-Free and ML-Driven Maps

The Hofmann stability chart remains a standard for visualizing parametric resonances in space-charge–dominated linacs, but its use typically relies on non-oscillatory Vlasov dispersion relations with simplifying assumptions (continuous focusing, KV phase space, linear optics, limited transverse–longitudinal coupling). We revisit the chart for the PIP-II linac along three tracks. (1) We reproduce the conventional maps in the (νz/νx, νx/ν0x) plane for relevant εz/εx, providing a validated reference. (2) We remove key assumptions by deriving stability surfaces directly from multi-particle tracking with realistic lattice discreteness, RF defocusing, solenoid/quad optics, and bunched-beam dynamics; local tunes and early-time growth rates are estimated from envelope oscillations and projected to the same coordinates. These assumption-reduced maps recover the canonical stopbands while revealing shifts and broadenings driven by tune modulation, non-KV distributions, and transverse–longitudinal coupling at PIP-II intensities. (3) We train a compact machine-learning surrogate that emulates the growth surface from zero-current optics, tune depression, emittance ratio, bunching factor, and selected lattice descriptors, enabling rapid scans and online working-point selection. We compare the three representations on representative PIP-II sections and discuss implications for commissioning guard bands, resonance avoidance, and routine operations.

Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗

DOE OSTI2025

Nyström type exponential integrators for strongly magnetized charged particle dynamics

Solving for charged particle motion in electromagnetic fields (i.e. the particle pushing problem) is a computationally intensive component of particle-in-cell (PIC) methods for plasma physics simulations. This task is especially challenging when the plasma is strongly magnetized due numerical stiffness arising from the wide range of time scales between highly oscillatory gyromotion and long term macroscopic behavior. A promising approach to solve these problems is by a class of methods known as exponential integrators that can solve linear problems exactly and are A-stable. This work extends the standard exponential integration framework to derive Nyström-type exponential integrators that integrates the Newtonian equations of motion as a second-order differential equation directly. In particular, we derive second-order and third-order Nyström-type exponential integrators for strongly magnetized particle pushing problems. Numerical experiments show that the Nyström-type exponential integrators exhibit significant improvement in computation speed over the standard exponential integrators.

general physics↗

DOE OSTI2025

BLOC Site - Radar Wind Profiler / Derived Data Reformatted

A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and combined to derive the horizontal wind field over the radar. These data are typically sampled and averaged hourly or sub-hourly (15-min) and usually have 60-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz system. Both a high-resolution, lower height coverage mode and a low-resolution, higher height coverage mode are used to collect the data.

17 WIND ENERGY↗

DOE OSTI2025

NANT Site - Radar Wind Profiler / Derived Data Reformatted

17 WIND ENERGY↗

DOE OSTI2025

Net-Zero Ethylene: On the Sustainability, Economics, and Scalability of Synthetic and Fossil Production Pathways

The ethylene industry has contributed over 260 million tons of CO 2 annually, warranting a more sustainable approach. The conversion of CO 2 and H 2 O into ethylene is an appealing technology capable of decoupling chemical production from fossil fuels. However, the large energy demand from this process can potentially lead to adverse environmental impacts. Here, in this article, we critically analyze the economic viability, environmental impact, and scalability of the conversion of CO 2 to ethylene via electrochemical reduction (CO 2 R) and compare this with those of CO 2 -neutral fossil routes utilizing carbon capture and direct air capture. Ethylene derived from CO 2 may be economically competitive under optimistic conditions; however, its large energy requirements pose environmental and scalability challenges. Meeting forecast 2050 ethylene demand using CO 2 R would require half of all electricity produced globally today, and, if powered by solar PV, may have greater CO 2 emissions than current petrochemical ethylene production, negating the purpose of this technology. Using Carbon Capture and Storage and Direct Air Capture to decarbonize petrochemical pathways would require roughly an order of magnitude less energy but would have disproportionate health and climate impacts. Lastly, the analysis highlights the importance of low-carbon energy sources to ensure sustainable CO 2 R ethylene production.

CO2R↗

DOE OSTI2026

All-organic self-separating three-dimensionally nanoarchitected electrochemical energy storage devices

This work realizes a three-dimensionally (3D) nanoarchitected, all organic, "self-separating" lithium-ion electrochemical energy storage (EES) device that is cycled as a solid-state full cell. The device is enabled by a monolithic carbon anode with a co-continuous pore network, derived from the structure direction of resols by an ultra-large molar mass block copolymer (BCP), poly(styrene-block-2-dimethylaminoethyl methacrylate) (SA). Electropolymerization of a single-phase conductive and redox-active material, poly((2,3-dihydrothieno[3,4-b][1,4]dioxin-2-yl)methyl 9,10-dioxo-9,10-dihydroanthracene-2-carboxylate) (PAQEDOT), into the pore space provides the cathode of the cell. The device is electronically contacted to the relevant electrode network enabled by the co-continuous nature of each electrode. Electrochemical processing via cycling against external lithium in an electrolyte generates a solid electrolyte interphase (SEI) as a separator and lithiates the cell electrodes, after which the EES device is cycled in the solid state. While the full cell does not demonstrate high cyclability, the best full cell demonstrates a discharge capacity of 267 milliamp hours per gram (mAh/g). This work marks, to the best of knowledge of the authors, the first example of an all-organic materials derived 3D nanoarchitected EES device, as well as the first design of "self-separating" cell fabrication. Furthermore, generalization of the design to another co-continuous carbon form factor is demonstrated.

FOS: Physical sciences↗

DOE OSTI2026

Life Cycle Analysis of Growing Canola for Biofuel Production in the United States

This study quantifies and compares the life cycle greenhouse gas (GHG) emissions of renewable diesel (RD), sustainable aviation fuel (SAF), and biodiesel (BD) produced from two U.S. canola production systems: 1) emerging intermediate winter canola, typically grown in double- or relay-cropping systems between the growing seasons of main crops, and 2) main canola, mostly spring canola but also including winter canola, which are grown as primary crops occupying the field for a full growing season. Using the Research and Development version of the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) model and the most up-to-date life cycle inventory data─field trial data for intermediate winter canola (>37,000 acres) and recent national survey data for spring canola─this life cycle analysis (LCA) estimates the direct emissions from canola cultivation and harvest, the conversion of canola into fuels, fuel transportation, and combustion. In addition, we account for market-mediated emissions associated with a scenario of 0.5 billion gallons per year of spring canola-based biofuels, including induced land use change (ILUC), induced other crop (nonfeedstock) production changes, and induced livestock production changes. For intermediate winter canola, these market-mediated effects were not modeled, as ILUC is expected to be negligible due to its integration into existing rotations, and data are currently insufficient to reliably quantify other market-mediated changes. The estimated life cycle direct emissions of RD/SAF derived from intermediate winter canola and main spring canola are about 32 and 33 g of CO2-equivalent per megajoule of fuel (g CO 2 e/MJ), respectively. Corresponding emissions for BD from intermediate winter canola and main spring canola are about 30 and 31 g of CO 2 e/MJ, respectively. Farming is the dominant emissions source for both canola systems, with intermediate winter canola and main spring canola emitting about 19 and 20 g of CO 2 e/MJ, respectively. ILUC and other induced changes increase emissions of main spring canola-derived RD/SAF and BD by about 18 and 17 g of CO 2 e/MJ, respectively. These results indicate that the GHG emissions of biofuels produced from the two canola systems may differ substantially due to the different land use dynamics of the systems.

biodiesel↗

DOE OSTI2026

Photoluminescence line shapes of nanocrystals: Contributions from first- and second-order vibronic couplings

Here, we present a microscopic, parameter-free approach for computing the photoluminescence spectra of a single semiconductor nanocrystal. The method derives exciton–phonon coupling directly from the semi-empirical pseudopotential framework and systematically incorporates both diagonal and off-diagonal exciton-phonon interactions, expanded to second-order in the phonon coordinates. The dipole–dipole correlation function was calculated using a Dyson expansion within the Kubo–Toyozawa formalism, enabling a consistent description of the role of pure dephasing and population transfer on the photoluminescence spectral features. Applied to CdSe/CdS core–shell nanocrystals, the approach quantitatively reproduces experimental photoluminescence spectra over a wide temperature range, revealing that quadratic phonon couplings account for nearly half of the homogeneous linewidth above ≈ 100−150 K, while off-diagonal couplings leading to exciton thermalization play only a minor role and only as T → 300 K.

Dephasing Rate↗

DOE OSTI2026

Fast and accurate calculation of EXAFS Debye-Waller factors in U⁢O2 using the dynamical matrix method

Theoretical modeling of bonding dynamics in metal oxides is required for predicting their thermal conductivity, catalytic activity, and mechanical properties. A primary challenge is the scarcity of experimental methods for validating theoretical predictions of these atomic-scale dynamics. This work presents a workflow that uses experimental extended x-ray absorption fine structure (EXAFS) data collected at high temperatures to validate an interatomic force field for uranium dioxide (UO2), an important model material. The validated force field is then used to drive computationally intensive molecular dynamics (MD) simulations and as input for the much faster dynamical matrix Debye-Waller (DMDW) method. The predicted values of the Debye-Waller factors from the DMDW calculations are in good agreement with those obtained from the MD simulations, with residual pair-specific differences attributable to quantum zero-point motion at low temperatures and lattice anharmonicity at high temperatures. We further show that theoretical EXAFS spectra constructed directly from DMDW-derived Debye-Waller factors reproduce the experimental data (at relatively low temperatures) with accuracy comparable to full MD-EXAFS, providing an additional validation of the choice of the potential. This study establishes a validated, rapid computational pathway for modeling bond dynamics, naturally incorporating quantum nuclear\\\\r\\\\nstatistics absent in classical simulations, which are essential for the mechanistic understanding of complex oxide materials.

58 GEOSCIENCES↗

DOE OSTI2026

SENTRA: A Modular Computational Graph Framework for Critical Mineral and Materials Supply Chains: Part I: Network Construction Latent-Quantity Estimation, and Temporal Graph Forecasting

Global supply chains for critical minerals and materials are complex, evolving networks of countries, products, production stages, and trade relationships. Existing analytical approaches are limited by fragmented data and static network representations that do not capture the dynamic production dependencies linking raw materials, intermediate products, and final goods across multiple countries. Trade and production statistics provide only a partial view of domestic production, inventories, and material flows, making it difficult to identify indirect sourcing pathways, hidden dependencies, and embedded foreign exposures. This paper introduces the Supply Chain Exposure Network Tracking and Risk Assessment (SENTRA) framework, a modular graph-based computational framework for constructing, analyzing, and forecasting dynamic supply chain networks. As the first paper in a three-part methodological series, it establishes the computational foundation of SENTRA by constructing a temporal attributed multi-relational graph whose nodes represent product–country pairs and whose edges encode observed trade and within-country value-chain relationships. Statistical estimation and constrained optimization recover latent production, final demand, and product input dependency coefficients while enforcing economic accounting constraints. Graph-derived exposure measures quantify direct, transshipment, value-chain, and multi-hop supply chain dependencies independently of the forecasting model. A temporal graph forecasting architecture based on a relational graph neural network then forecasts the evolution of the graph under mass-balance constraints with distribution-free conformal uncertainty quantification. Validation on the global aluminum supply chain shows that the learned graph representations recover economically meaningful supply chain structure, accurately forecast out-of-sample trade relationships, and produce well-calibrated prediction intervals. Subsequent papers apply this computational foundation to exposure assessment, disruption analysis, and scenario-based policy analysis, and extend the framework to multimaterial supply chain modeling and decision support.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Determining Magnetic Field Directions and Omni-directional Fluxes of Particles from STPSat-6 ZPS Plasma Measurements

This report summarizes our recent data derivation efforts on STPSat-6 ZPS plasma measurements, presenting final outcomes. We begin by outlining the methodology developed to determine local magnetic field directions from measured directional intensities of ~20 keV ions, leveraging symmetry in particles’ pitch-angle distributions, and the determined field directions over a storm period are shown with errors analyzed through comparison with NOAA GOES measurements. Next, we further assess the validity of the method and quantify its overall high performance while acknowledging certain caveats. Finally, given local magnetic field directions and ZPS data, we explain how omni-directional fluxes of particles can be derived from ZPS measurements with limited directional coverage, and estimate the related errors under several theoretical scenarios. The methods developed in this study can be applied for processing and augmenting ZPS data for the next, and the insights gained here can also inform instrument design in the future.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Global River Topology (GRIT): A Bifurcating River Hydrography

Existing global river networks underpin a wide range of hydrological applications but do not represent channels with divergent river flows (bifurcations, multi‐threaded channels, canals), as these features defy the convergent flow assumption that elevation‐derived networks (e.g., HydroSHEDS, MERIT Hydro) are based on. Yet, bifurcations are important features of the global river drainage system, especially on large floodplains and river deltas, and are also often found in densely populated regions. Here we developed the first raster and vector‐based Global RIver Topology that not only represents the tributaries of the global drainage network but also the distributaries, including multi‐threaded rivers, canals and deltas. We achieve this by merging a 30 m Landsat‐based river mask with elevation‐generated streams to ensure a homogeneous drainage density outside of the river mask for rivers narrower than approximately 30 m. Crucially, we employ the new 30 m digital terrain model, FABDEM, based on TanDEM‐X, which shows greater accuracy over the traditionally used SRTM derivatives. After vectorization and pruning, directionality is assigned by a series of elevation, flow angle and continuity approaches. The new global network and its attributes are validated using gauging stations, comparison with existing networks, and randomized manual checks. The new network represents 19.6 million km of streams and rivers with drainage areas greater than 50 km 2 and includes 67,495 bifurcations. With the advent of hyper‐resolution modeling and artificial intelligence, GRIT is expected to greatly improve the accuracy of many river‐based applications such as flood forecasting, water availability and quality simulations, or riverine habitat mapping.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Chemical imaging of individual stratospheric particles sampled over North America

The increasing size, severity, and frequency of wildfires have led to dramatic increases in particulate matter concentrations in the troposphere. Severe wildfires can generate intense convective systems capable of transporting large quantities of biomass burning organic aerosols (BBOA) to the upper troposphere and lower stratosphere (UTLS). Chemically complex organic matter and light-absorbing carbonaceous material is introduced into stratospheric regions that were historically isolated from direct surface emissions. In this study, stratospheric particles were sampled over North America during the Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) campaign, an aircraft-based research project designed to characterize convective perturbation in the UTLS. Particle samples collected from six research flights during summer 2022 were analyzed using Computer-Controlled Scanning Electron Microscopy and Scanning Transmission X-ray Microscopy to investigate particle size distributions, morphology, chemical composition, and mixing state of stratospheric particles along transects across the continental United States and adjacent Pacific Ocean airspace. Analysis revealed that all sampled particles contained detectable levels of carbon, with most exhibiting organic volume fractions of 0.37 ± 0.20. Notably, about 5% of the particles also contained soot inclusions, which indicates the presence of refractory black carbon transported to stratospheric altitudes and provides direct evidence of wildfire-derived black carbon reaching the UTLS. Typical particle morphology exhibits organic shells over soot and inorganic cores and suggests secondary processing and aging of BBOA during transport to and within the UTLS. These findings provide compelling evidence that wildfire emissions play a critical role in affecting the long-term composition and radiative properties of stratospheric particles.

Sharpe, Steven [Purdue Univ., West Lafayette, IN (↗

DOE OSTI2025

Phase-based velocity extraction method for photonic Doppler velocimetry with potential higher time resolution

We present an extension of the [Takeda et al., J. Opt. Soc. Am. 72, 156 (1982)] phase extraction method to heterodyne photonic Doppler velocimetry applications. The method yields results equivalent to those obtained by the short-time Fourier transform (STFT), while offering potential improvements in time resolution. Unlike STFT, which relies on window functions, such as the Hamming window, that emphasize central data points and diminish the influence of edges, the extended Takeda method utilizes all data uniformly. This uniform treatment allows for the derivation of empirical equations that directly relate velocity error to the actual time resolution rather than to the local analysis duration. The established equation provides a useful metric for both optimizing hardware configuration and guiding data analysis. Simulation and experimental results confirm that, for a given dataset, specifying a target time resolution yields consistent velocity errors for both methods. These findings underscore the Takeda method’s advantages, particularly its potential higher time resolution and reduced computational burden, making it a valuable tool for high-throughput applications such as laser dynamic compression experiments.

Computer simulation↗

DOE OSTI2025

Fermionic sub-GeV dark matter from evaporating primordial black holes at DarkSide-50

We present a search for boosted dark matter from primordial black hole (PBH) evaporation using the DarkSide-50 ionization-signal-only dataset corresponding to the experiment’s ( 12202 ± 180 ) kg d exposure. We focus on evaporation of PBHs with masses in the range [ 10 14 , 10 16 ] g producing Dirac fermionic dark matter particles with sub-GeV kinetic energy. These relativistic particles, with energies up to hundreds of MeV, can generate detectable signals for masses below O ( 100 ) MeV . The absence of a signal enables setting complementary limits to those derived from cosmological observations and direct detection searches for cosmic-ray-boosted dark matter.

Agnes, P. [Gran Sasso; GSSI, Aquila]↗

NASA NTRSDate not supplied

A Parametric Battery Model for the Conceptual Design of Electric Aircraft

Electric aircraft conceptual designs usually have an assumed specific power and specific energy for the aircraft’s energy storage system that dictates the total capacity and the peak power available. The specific energy and power are inherently linked to the state-of-charge and discharge rate from which they were derived; therefore, they will not directly correspond to the diverse circumstances encountered in various aircraft missions and flight segments. These parameters turn the battery system into a black box, disregard potential electrical restrictions, and disallow the aircraft and battery to be optimized as a system. Peering into this box, this study highlights the importance of incorporating a parametric battery model into the conceptual design workflow by splitting high-level terms such as power into voltage and current and investigating their variability during the discharge process. Through the modeling of these more detailed parameters, this methodology shows the feasibility of using low states-of-charge for contingency operations, including the end of the reserve mission, expanding the amount of usable capacity for electric aircraft. Stark differences in aircraft capabilities can arise between varying fidelity battery models due to late-mission, high-power flight operations. This parametric battery model effectively captures these differences by evaluating the limitations that arise within the individual battery cells and the aircraft powertrain. This paper shows that the unusable charge of a battery is set by the balked landing power requirement and can realistically range from 5% to 44% based on assumptions. This sets the analog to unusable fuel capacity in aircraft with liquid fuel systems. Needing only aircraft- and mission-level inputs and only seconds of run time, this model is a prime fit for the fast, accurate exploration of the electric aircraft conceptual design space.

Battery↗

DOE OSTI2025

Using Calibrated Sodium Data for Preliminary Validation of the SRT Code for Advanced Reactors

Various types of non-light water reactors are currently engaged in the U.S. licensing process. Because of inherent differences compared with well-established large light water reactors, appropriate assessment tools are needed. Specifically, source term analysis, which determines environmental dose impacts from potential accident scenarios, is a crucial part of design and licensing. The U.S. Nuclear Regulatory Commission has emphasized the importance of mechanistic source term analysis for advanced reactor deployments. To align with these needs, Argonne National Laboratory has developed the Simplified Radionuclide Transport (SRT) source term analysis code for metal fuel Sodium-cooled Fast Reactors (SFRs) and microreactors. SRT conducts time-dependent radionuclide transport and retention in SFRs for core and ex-core radionuclide source accident sequences. The main objective of SRT is to provide rapid sensitivity and uncertainty analyses, incorporating parametric uncertainties and summarizing probabilistic results. As part of the code validation process, a study focused on the bubble scrubbing module was performed using an experiment recently carried out by the University of Wisconsin-Madison. Based on the analysis, the modeling approach in SRT provides accurate results for small and large aerosols, while slight underprediction of radionuclide aerosol removal are observed for medium sized aerosols. However, the deviation is minor, considering the highly uncertain phenomenon and range of results, and is in the conservative direction. In addition, uncertainty information derived from the experiments is further implemented, reflecting the actual span of parameters, which leads to enhanced agreement with code predictions. The results demonstrate that SRT provides reasonable predictions for the bubble scrubbing process in sodium pool.

Kam, Dong Hoon↗

DOE OSTI2026

A funnel approach to enable analyses of epitope-specific human CD4 T cells specific for influenza and SARS-CoV-2

Protection against pathogens relies heavily on the adaptive immune response, whose key regulators are CD4 T cells. CD4 T cells, notable for their complex repertoire and functional potential, can most easily be dissected by identifying, quantifying, characterizing, and isolating epitope-specific cells. In the study reported here, we present a systematic and unbiased strategy that has enabled the identification of highly immunogenic peptide epitopes derived from influenza virus and SARS-CoV-2, presented by human HLA-DR proteins. Coupling the use of HLA-DR transgenic mice with infection and vaccination and highly sensitive epitope-specific cytokine ELISpot assays, we have narrowed the potential epitopes from 450 to 600 peptides to 5–15 peptides for each allele by an iterative process of elimination and selection, which we have termed a funnel approach. These epitopes have been validated in HLA-DR-typed human CD4 T cells directly ex vivo and enabled the derivation and implementation of HLA-DR peptide tetramers. Tetramer staining of human PBMCs enriched for CD4 T memory populations from healthy adult subjects, highlighted this approach as a sensitive and specific method for identifying novel epitopes, and subsequent CD4 T-cell responses to human viral infections.

CD4 T cell↗