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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Investigation of grid-based vorticity-velocity large eddy simulation off-body solvers for application to overset CFD

Accurately predicting unsteady wakes and vortex-dominated flows is essential to a wide range of engineering applications, including aircraft, rotorcraft, shipboard operations, bio-inspired unsteady flight and propulsion, wind turbines, and urban flows. While current CFD software can model the complete flow field and wake system, the computational costs incurred in high Reynolds number unsteady turbulent flow simulations often remain prohibitive for routine engineering use, particularly for applications involving moving components. Prior work has demonstrated that by adopting a vorticity-velocity formulation in a grid-based off-body flow solver (VorTran-M and VorTran-M2) one can lower these costs by several orders of magnitude when compared to conventional approaches. This paper describes the extensions made to VorTran-M2 to support turbulent flows, and associated benchmarking activity to assess its performance for problems involving strong stretching and diffusion processes, whose competing contributions to the vorticity field are core drivers of turbulent flow evolution. Predictions are presented for: (i) the Kida-Pelz problem whose inviscid form is of mathematical interest due to its apparent formation of singular flow in finite time; and (ii) the Taylor Green vortex arrangement, which has been extensively studied as a fundamental simulation challenge in the turbulent modeling community. Here, the results are used to evaluate the overall predictive ability and performance of two sub-grid scale models incorporated into VorTran-M2. Results indicate that the computational cost savings seen previously for inviscid and convection dominated problems extend to turbulent flow simulations supporting the viability of VorTran-M2 as a low cost means for accurately modeling the far-field and background flow, particularly when long duration vorticity evolution is of interest.

42 ENGINEERING↗
DOE OSTI2021

Localization of Nonblinking Point Sources Using Higher-Order-Mode Detection and Optical Heterodyning: Developing a Strategy for Extending the Scope of Molecular, Super-resolution Imaging

While the stochastic, “blinking” nature of fluorescent systems has enabled the super-resolution of their localization by the fitting of their point-spread functions (PSFs), this strategy cannot be exploited for similar resolution of “nonblinking” systems, such as those that might be encountered in a coherent Raman experiment. An alternative method for subdiffraction-limited imaging lies in the exploitation of optical heterodyning. For example, if a Gaussian PSF (a TEM00 mode) of a point emitter is displaced with respect to the origin of the optical system, photons in the higher-order TEM modes carry information about that displacement. Information concerning the displacement can be extracted from photons in these higher-order modes. These photons can be collected by optical heterodyning, which exploits the large gain in a detector’s response to an optical signal from an emitter coupled to a local oscillator, which is prepared in the TEM of interest, e.g., TEM10. We have generalized and developed the heterodyning technique to localize point emitters via the detection of higher-order spatial modes. We have developed a theoretical approach to find a practical estimation limit of the localization parameters using a realistic model that accounts for shot noise, background noise, and Gaussian noise. To demonstrate the applicability of the method, we designed experiments in which a laser is a surrogate for one and two point emitters. Using the Fisher information and its accompanying Cramér-Rao lower bound, we demonstrate super-resolution localization in these cases: we show that objects can be localized to roughly 2–3 orders of magnitude of their point-spread function’s size for a given optical system. Finally and most importantly, it is suggested that the results will ultimately be generalizable to multiple emitters and, most importantly, to “nonblinking” molecular systems, which will be essential for broadening the scope of super-resolution measurements beyond the limits of fluorescence-based techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Induced seismicity and geothermal energy production in the Salton Sea Geothermal Field, California

We analyze the relationship between geothermal energy production and seismic hazards in the Salton Sea Geothermal Field (SSGF) between 1972 and 2022. A clear increase in seismic activity accompanies geothermal energy production and is greatest to the east of the Brawley fault, where the amount of injection exceeds the amount of production. We estimate that, whereas there was a 2% chance of a M6.07 earthquake nucleating inside the SSGF within a fifty-year period prior to energy production (pre-production), there is an equal probability that a M6.70 earthquake nucleates there in a fifty-year period during which historically average energy production conditions persist (syn-production). Similarly, we estimate a 2% chance of a M7.15 and M6.92 occurring in the broader Brawley Seismic Zone (excluding the SSGF) within a fifty-year period during the pre- and syn-production eras, respectively. We find that linear regression models fail to reliably forecast the background seismicity rate as a function of fluid production and injection.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Modeling the differential rate for signal interactions in coincidence with noise fluctuations or large rate backgrounds

The characteristic energy of a relic dark matter interaction with a detector scales strongly with the putative dark matter mass. Consequently, experimental search sensitivity at the lightest masses will always come from interactions whose size is similar to noise fluctuations and low energy backgrounds in the detector. In this paper, we correctly calculate the net change in measured differential event rate due to low rate signal interactions that overlap in time with noise and backgrounds, accounting for both periods of time when the signal is coincident with noise/backgrounds and for the decreased amount of time in which only noise/backgrounds occur and we show that the introduction of random simulated signal events into the continuous raw data stream (a form of “salting”) provides a correct and practical implementation to estimate this net linear signal sensitivity. Unfortunately this does not apply to the situation with non negligible pileups as we show through explicit examples. Consequently, this exclusion technique should be complemented by less sensitive techniques that can separately exclude large rate, high pileup signal parameter space. An analysis threshold above the Gaussian-like noise component of the measured differential rate spectrum should also likely produce conservative limits. Though previous light mass dark matter searches did not correctly account for decreased background only live time effects in their signal sensitivity, conservative analysis choices likely protected their published limits from being nonconservative.

Li, Xinran↗
DOE OSTI2021

Prospects for detecting heavy WIMP dark matter with the Cherenkov Telescope Array: The Wino and Higgsino

TeV-scale particles that couple to the standard model through the weak force represent a compelling class of dark matter candidates. The search for such weakly interacting massive particles has already spanned multiple decades, and whilst it has yet to provide any definitive evidence for their existence, viable parameter space remains. In this paper, we show that the upcoming Cherenkov Telescope Array (CTA) has significant sensitivity to uncharted parameter space at the TeV mass scale. To do so, we focus on two prototypical dark matter candidates, the Wino and Higgsino. Additionally, sensitivity forecasts for both models are performed including the irreducible background from misidentified cosmic rays, as well as a range of estimates for the Galactic emissions at TeV energies. For each candidate, we find substantial expected improvements over existing bounds from current imaging atmospheric Cherenkov telescopes. In detail, for the Wino we find a sensitivity improvement of roughly an order of magnitude in <σ v>, whereas for the Higgsino we demonstrate that CTA has the potential to become the first experiment that has sensitivity to the thermal candidate. Taken together, these enhanced sensitivities demonstrate the discovery potential for dark matter at CTA in the 1–100 TeV mass range.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

ROI-Finder : machine learning to guide region-of-interest scanning for X-ray fluorescence microscopy

The microscopy research at the Bionanoprobe (currently at beamline 9-ID and later 2-ID after APS-U) of Argonne National Laboratory focuses on applying synchrotron X-ray fluorescence (XRF) techniques to obtain trace elemental mappings of cryogenic biological samples to gain insights about their role in critical biological activities. The elemental mappings and the morphological aspects of the biological samples, in this instance, the bacterium Escherichia coli ( E. Coli ), also serve as label-free biological fingerprints to identify E. coli cells that have been treated differently. The key limitations of achieving good identification performance are the extraction of cells from raw XRF measurements via binary conversion, definition of features, noise floor and proportion of cells treated differently in the measurement. Automating cell extraction from raw XRF measurements across different types of chemical treatment and the implementation of machine-learning models to distinguish cells from the background and their differing treatments are described. Principal components are calculated from domain knowledge specific features and clustered to distinguish healthy and poisoned cells from the background without manual annotation. The cells are ranked via fuzzy clustering to recommend regions of interest for automated experimentation. The effects of dwell time and the amount of data required on the usability of the software are also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an↗
DOE OSTI2022

Search for strongly interacting massive particles generating trackless jets in proton–proton collisions at $\sqrt{s} = 13\,\text {TeV}$

A search for dark matter in the form of strongly interacting massive particles (SIMPs) using the CMS detector at the LHC is presented. The SIMPs would be produced in pairs that manifest themselves as pairs of jets without tracks. The energy fraction of jets carried by charged particles is used as a key discriminator to suppress efficiently the large multijet background, and the remaining background is estimated directly from data. The search is performed using proton–proton collision data corresponding to an integrated luminosity of 16.1 fb -1 , collected with the CMS detector in 2016. No significant excess of events is observed above the expected background. For the simplified dark matter model under consideration, SIMPs with masses up to 100 GeV are excluded and further sensitivity is explored towards higher masses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

A search for new physics in central exclusive production using the missing mass technique with the CMS detector and the CMS-TOTEM precision proton spectrometer

A generic search is presented for the associated production of a Z boson or a photon with an additional unspecified massive particle X, pp → pp + Z/γ + X, in proton-tagged events from proton–proton collisions at $\sqrt{s}$ = 13 TeV, recorded in 2017 with the CMS detector and the CMS-TOTEM precision proton spectrometer. The missing mass spectrum is analysed in the 600–1600 GeV range and a fit is performed to search for possible deviations from the background expectation. No significant excess in data with respect to the background predictions has been observed. Model-independent upper limits on the visible pro duction cross section of pp → pp + Z/γ + X are set

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Neural simulation-based inference of the Higgs trilinear self-coupling via off-shell Higgs production

One of the forthcoming major challenges in particle physics is the experimental determination of the Higgs trilinear self-coupling. While efforts have largely focused on on-shell double- and single-Higgs production in proton-proton collisions, off-shell Higgs production has also been proposed as a valuable complementary probe. In this article, we design a hybrid neural simulation-based inference (NSBI) approach to construct a likelihood of the Higgs signal incorporating modifications from the Standard Model effective field theory (SMEFT), relevant background processes, and quantum interference effects. It leverages the training efficiency of matrix-element-enhanced techniques, which are vital for robust SMEFT applications, while also incorporating the practical advantages of classification-based methods for effective background estimates. We demonstrate that our NSBI approach achieves sensitivity close to the theoretical optimum and provide expected constraints for the high-luminosity upgrade of the Large Hadron Collider. While we primarily concentrate on the Higgs trilinear self-coupling, we also consider constraints on other SMEFT operators that affect off-shell Higgs production.

Ghosh, Aishik [Univ. of California, Irvine, CA (Un↗
DOE OSTI2024

Injection, confinement, and diagnosis of electrons and positrons in a permanent magnet dipole trap

Abstract Prerequisites for the goal of studying long-lived, magnetically confined, electron–positron pair plasmas in the laboratory include the injection of both species into the trap, long trapping times, and suitable diagnostic methods. Here we report recent progress on these tasks achieved in a simple dipole trap based on a supported permanent magnet. For the injection of electrons, both an $$\textbf{E}\times B$$ E × B drift technique (of a $$\sim $$ ∼ 2– $$\upmu $$ μ A, 6-eV beam) and “edge injection” (from a filament emitting a few mA and biased to some tens of volts) have been demonstrated; the former is suitable for low-density beams with smaller spatial and velocity spreads, while the latter employs fluctuations arising from collective behavior. To diagnose the edge-injected electrons, image potentials and currents induced on a wall probe, the magnet case, and wall electrodes were measured. Confinement of drift-injected positrons, measured experimentally, exhibited at least two well-separated timescales. Simulations reproduced this qualitatively, using a simple model of elastic collisions with residual background gas, and point to small adjustments for increasing trapping times. In a major upgrade to diagnostic capabilities, 25 bismuth germanate detectors, placed in three reentrant ports, are able to localize annihilation gammas, which will be used in future experiments to distinguish between different loss channels. Graphical abstract

von der Linden, J. (ORCID:0000000327477813)↗
DOE OSTI2023

The Optical Signatures of Stochastic Processes in Many-Body Exciton Scattering

We review our recent quantum stochastic model for spectroscopic lineshapes in the presence of a coevolving and nonstationary background population of excitations. Starting from a field theory description for interacting bosonic excitons, we derive a reduced model whereby optical excitons are coupled to an incoherent background via scattering as mediated by their screened Coulomb coupling. The Heisenberg equations of motion for the optical excitons are then driven by an auxiliary stochastic population variable, which we take to be the solution of an Ornstein–Uhlenbeck process. Here, we present an overview of the theoretical techniques we have developed as applied to predicting coherent nonlinear spectroscopic signals. We show how direct (Coulomb) and exchange coupling to the bath give rise to distinct spectral signatures and discuss mathematical limits on inverting spectral signatures to extract the background density of states.

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

AMR-Wind [SWR-20-85]

AMR-Wind is a massively parallel, block-structured adaptive-mesh, incompressible flow solver for wind turbine and wind farm simulations. The solver is built on top of the AMReX library. AMReX is developed at LBNL , NREL , and ANL as part of the Block-Structured AMR Co-Design Center in DOE's Exascale Computing Project. AMReX library provides the mesh data structures, mesh adaptivity, as well as the linear solvers used for solving the governing equations. The primary applications for AMR-Wind are: performing large-eddy simulations (LES) of atmospheric boundary layer (ABL) flows, simulating wind farm turbine-wake interactions using actuator disk or actuator line models for turbines, and as a background solver when coupled with a near-body solver with overset methodology to perform blade-resolved simulations of multiple wind turbines within a wind farm.

Ananthan, Shreyas↗
DOE OSTI2026

R&D GREET Battery Carbon Footprint Calculator

The Battery Carbon Footprint (CF) Calculator was developed to help U.S. battery manufacturers meet the carbon footprint reporting requirements of the EU Battery Regulation (EU) 2023/1542. The calculator incorporates several major battery carbon footprint frameworks, including the Joint Research Centre's Rules for the Calculation of the Carbon Footprint of Electric Vehicle Batteries (CFB-EV), RECHARGE's Product Environmental Footprint Category Rules for High Specific Energy Rechargeable Batteries for Mobile Applications (PEFCR), the Catena-X Product Carbon Footprint Rulebook (CX-PCF Rules), Battery Pass's Battery Carbon Footprint: Rules for Calculating the Carbon Footprint of the "Distribution" and "End-of-Life and Recycling" Life Cycle Stages, the Global Battery Alliance's Greenhouse Gas Rulebook: Generic Rules, Version 2.1, and the Ministry of Economy, Trade and Industry's draft Carbon Footprint Calculation Method for Automotive Batteries. The tool pairs these frameworks with foreground data from Argonne's R&D GREET models and integrates user-supplied background data covering battery manufacturing and supply chain activities. By bringing multiple international methodologies together in a single platform, the calculator enables manufacturers to evaluate product carbon footprints, improve data consistency, and prepare for evolving regulatory compliance and global market reporting requirements.

Zhang, Jingyi↗
DOE OSTI2020

Forward Physics Facility - Snowmass 2021 Letter of Interest

A rich physics program remains unexplored in the far-forward region at the LHC. The Forward Physics Facility (FPF) is a proposal to enlarge an existing cavern in the far-forward region of ATLAS to house a suite of experiments with groundbreaking new capabilities for neutrinos, long-lived particle searches, milli-charged particle searches, QCD, dark matter, dark sectors, and cosmic rays. The FPF will be located 500 m from the ATLAS interaction point. It is shielded from the ATLAS interaction point by 100 m of concrete and rock, creating an extremely low-background environment, ideal for many standard model studies and new physics searches. In this Letter of Interest, we describe the FPF’s location and general features, its physics potential in the HL-LHC era, and topics for further study.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1975

Evidence for X-ray emission from flare stars observed by ANS

Observations that detected the first X-ray emission from flare stars are described. An X-ray flare was detected from YZ CMi at 0.28 keV and approximately 1-7 keV, although no optical or radio coverage was available. During a very large optical flare from UV Ceti, X-ray emission at (only) 0.28 keV was detected. Upper limits for X-ray emission from several small optical flares of UV Ceti are presented. Implications for X-ray flare models, the diffuse X-ray background, and low-energy cosmic-ray flux are mentioned.

Heise, J.↗
NASA NTRS1975

Observations of X-rays from flare stars with ANS

Observations during which X-ray emission from flare stars was detected for the first time, are described. An X-ray flare was detected from YZ CMi at 0.28 keV and 1-7 keV, although no optical or radio coverage was available. During a very large optical flare from UV Ceti, X-ray emission at 0.28 keV only was detected. Upper limits for X-ray emission from several small optical flares of UV Ceti are obtained. Implications for X-ray flare models, the diffuse X-ray background, and low-energy cosmic-ray flux are examined.

Grindlay, J.↗