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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evaluating the impact of air terminal geometry on lightning intercept efficacy under a strong background electric field

A comparative analysis of the attachment efficacy of sharpened vs blunted air terminals under a strong background DC electric field, similar to conditions found in naturally occurring lightning events, is presented. Testing was conducted using an oil-free, 17-stage, 1.4 MV bipolar Marx generator with a biased discharge plane that emulated the conditions found prior to the lightning return stroke. The biased discharge plane allowed the introduction of a strong DC electric field and subsequent corona formation on a time scale much longer than the brief duration over which the downward leader propagates. Initial observations indicate that despite a higher background electric field at the sharpened terminals, leading to pre-discharge corona formation where none is seen on the blunt terminal, both the sharpened and blunted terminals exhibit similar attachment probabilities during discharge events, with some discharge events attaching to both terminals.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Enhancing Nanoparticle Detection in Interferometric Scattering (iSCAT) Microscopy Using a Mask R-CNN

Interferometric scattering microscopy (iSCAT) is a label-free optical microscopy technique that enables imaging of individual nano-objects such as nanoparticles, viruses, and proteins. Essential to this technique is the suppression of background scattering and identification of signals from nano-objects. In the presence of substrates with high roughness, scattering heterogeneities in the background, when coupled with tiny stage movements, cause features in the background to be manifested in background-suppressed iSCAT images. Traditional computer vision algorithms detect these background features as particles, limiting the accuracy of object detection in iSCAT experiments. Here, in this paper, we present a pathway to improve particle detection in such situations using supervised machine learning via a mask region-based convolutional neural network (mask R-CNN). Using a model iSCAT experiment of 19.2 nm gold nanoparticles adsorbing to a rough layer-by-layer polyelectrolyte film, we develop a method to generate labeled datasets using experimental background images and simulated particle signals and train the mask R-CNN using limited computational resources via transfer learning. We then compare the performance of the mask R-CNN trained with and without inclusion of experimental backgrounds in the dataset against that of a traditional computer vision object detection algorithm, Haar-like feature detection, by analyzing data from the model experiment. Results demonstrate that including representative backgrounds in training datasets improved the mask R-CNN in differentiating between background and particle signals and elevated performance by markedly reducing false positives. The methodology for creating a labeled dataset with representative experimental backgrounds and simulated signals facilitates the application of machine learning in iSCAT experiments with strong background scattering and thus provides a useful workflow for future researchers to improve their image processing capabilities.

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

Spectra of Magnetic Turbulence in a Relativistic Plasma

Abstract We present a phenomenological and numerical study of strong Alfvénic turbulence in a magnetically dominated collisionless relativistic plasma with a strong background magnetic field. In contrast with the nonrelativistic case, the energy in such turbulence is contained in magnetic and electric fluctuations. We argue that such turbulence is analogous to turbulence in a strongly magnetized nonrelativistic plasma in the regime of broken quasi-neutrality. Our 2D particle-in-cell numerical simulations of turbulence in a relativistic pair plasma find that the spectrum of the total energy has the scaling k −3/2 , while the difference between the magnetic and electric energies, the so-called residual energy, has the scaling k −2.4 . The electric and magnetic fluctuations at scale ℓ exhibit dynamic alignment with the alignment angle scaling close to cos ϕ ℓ ∝ ℓ 1 / 4 . At scales smaller than the (relativistic) plasma inertial scale, the energy spectrum of relativistic inertial Alfvén turbulence steepens to k −3.5 .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Quantum simulations for strong-field QED

Quantum field theory in the presence of strong background fields contains interesting problems where quantum computers may someday provide a valuable computational resource. In the noisy intermediate-scale quantum era it is useful to consider simpler benchmark problems in order to develop feasible approaches, identify critical limitations of current hardware, and build new simulation tools. Here we perform quantum simulations of strong-field QED (SFQED) in 3 + 1 dimensions, using real-time nonlinear Breit-Wheeler pair production as a prototypical process. The strong-field QED Hamiltonian is derived and truncated in the Furry-Volkov mode expansion, and the interactions relevant for Breit-Wheeler are transformed into a quantum circuit. Quantum simulations of a “null double slit” experiment are found to agree well with classical simulations following the application of various error mitigation strategies, including an asymmetric depolarization algorithm which we develop and adapt to the case of Trotterization with a time-dependent Hamiltonian. We also discuss longer-term goals for the quantum simulation of SFQED. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2025

Sensitivity of nEXO to 136 Xe charged-current interactions: Background-free searches for solar neutrinos and fermionic dark matter

We study the sensitivity of nEXO to solar neutrino charged-current interactions, 𝜈 𝑒 + 136 Xe → 136 Cs*+𝑒 − , as well as analogous interactions predicted by models of fermionic dark matter. Due to the recently observed low-lying isomeric states of 136 Cs, these interactions will create a time-delayed coincident signal observable in the scintillation channel. Here we develop a detailed Monte Carlo simulation of scintillation emission, propagation, and detection in the nEXO detector to model these signals under different assumptions about the timing resolution of the photosensor readout. We show this correlated signal can be used to achieve background discrimination on the order of 10 −9 , enabling nEXO to make background-free measurements of solar neutrinos above the reaction threshold of 0.668 MeV. We project that nEXO could measure the flux of neutrinos from the carbon-nitrogen-oxygen cycle with a statistical uncertainty of 25%, thus contributing a novel and competitive measurement toward addressing the solar metallicity problem. Additionally, nEXO could measure the mean energy of the 7 Be neutrinos with a precision of 𝜎 ≤ 1.5 keV and could determine the survival probability of 7 Be and pep solar 𝜈𝑒 with precision comparable to the state of the art. These quantities are sensitive to the Sun’s core temperature and to nonstandard neutrino interactions, respectively. Here, the strong background suppression would allow nEXO to search for charged-current interactions of fermionic dark matter in the mass range 𝑚 𝜒 = 0.668–7 MeV with a sensitivity up to three orders of magnitude better than current limits.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Machine-Learning Analysis of Radiative Decays to Dark Matter at the LHC

The search for weakly interacting matter particles (WIMPs) is one of the main objectives of the High Luminosity Large Hadron Collider (HL-LHC). In this work we use Machine-Learning (ML) techniques to explore WIMP radiative decays into a Dark Matter (DM) candidate in a supersymmetric framework. The minimal supersymmetric WIMP sector includes the lightest neutralino that can provide the observed DM relic density through its co-annihilation with the second lightest neutralino and lightest chargino. Moreover, the direct DM detection cross section rates fulfill current experimental bounds and provide discovery targets for the same region of model parameters in which the radiative decay of the second lightest neutralino into a photon and the lightest neutralino is enhanced. This strongly motivates the search for radiatively decaying neutralinos which, however, suffers from strong backgrounds. We investigate the LHC reach in the search for these radiatively decaying particles by means of cut-based and ML methods and estimate its discovery potential in this well-motivated, new physics scenario. We demonstrate that using ML techniques would enable access to most of the parameter space unexplored by other searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

RF-transpond: A 1D coupled cold plasma wave and plasma transport model for ponderomotive force driven density modification parallel to B

The RF-Transpond code couples a fluid plasma transport solver with a frequency domain cold plasma RF wave solver in a 1D domain parallel to a strong background magnetic field. A ponderomotive force term proportional to parallel gradients in the electric field strength is included in the transport model in order to describe ponderomotive effects in the scrape-off layer (SOL) of fusion plasmas. The transport and wave codes are verified independently and a coupled case corresponding to experimental parameters from the LArge Plasma Device (LAPD) is presented. The density perturbation ratio R n , calculated to describe ponderomotive force driven modifications, is up to 20% for the simulation inputs used.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Assessment of the associated particle technique with high-resolution gamma-ray spectroscopy for in-field identification of chemical warfare agents and explosives

In this work, high-resolution prompt γ-ray neutron activation analysis (PGNAA) is performed using the associated particle (AP) technique with a deuterium-tritium neutron generator and high-purity germanium detector. Although the time resolution is inferior compared to similar systems employing fast scintillation γ-ray detectors, the strong background suppression combined with the high γ-ray energy resolution provides an important boost in sensitivity to certain key elements, especially relevant to field measurements of complex chemicals encased within thick layers of metal, such as in the case of recovered chemical warfare (CW) munitions. Results for various CW and explosive simulants contained within mock munitions are presented and compared with results obtained from traditional PGNAA measurements without the aid of the AP technique. Significant improvements in identification and discrimination between certain chemicals are achieved with the high energy resolution AP technique.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Experimental observation and numerical investigation of filamentary structures in magnetized plasmas

Filamentary structures in low-pressure, low-temperature plasmas are produced when strong magnetic fields are applied parallel to the electric field defined by parallel electrodes. Filamentary structures are regions within the plasma that have distinct properties such as optical brightness and extend along the magnetic field lines. In our experiments, an argon, radio frequency discharge is exposed to a strong background magnetic field in the magnetized dusty plasma experiment at Auburn University. Different forms of filamentary structures emerge in the plasma such as columns, target, or spiral-like structures. To investigate the origin and the characteristics of these patterns, we have developed a three-dimensional fluid model that can reproduce the experimental observations which enables us to investigate the underlying mechanisms of the filamentation process.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Validation of gyrokinetic simulations in NSTX and projections for high-k turbulence measurements in NSTX-U

An extensive validation effort performed for a modest-beta NSTX NBI-heated H-mode discharge predicts that electron thermal transport can be entirely explained by electron-scale turbulence fluctuations driven by the electron temperature gradient mode (ETG), both in conditions of strong and weak ETG turbulence drive. Thermal power-balance estimates computed by TRANSP as well as the shape of the high-k density fluctuation wavenumber spectrum and the fluctuation level ratio between strongly driven and weakly driven ETG-turbulence conditions can be matched by nonlinear gyrokinetic simulations and a synthetic diagnostic for high-k scattering. Linear gyrokinetic simulations suggest that the ion-scale instability in the weak ETG condition is close to the critical threshold for the kinetic ballooning mode instability, and nonlinear ion-scale gyrokinetic simulations show that turbulence might be in a state reminiscent of a Dimits' shift regime, opening speculation on the role that ion-scale turbulence might play for the weak ETG condition. A simulation that matched all experimental constraints is chosen to project high-k turbulence spectra in NSTX-U, revealing that the new high-k system [R. Barchfeld et al., Rev. Sci. Instrum. 89, 10C114 (2018)] should be sensitive to density fluctuations from radially elongated streamer structures. In this study, two schemes are designed to characterize the radial and poloidal wavenumber dependence of the density fluctuation wavenumber power spectrum around the streamer peak, suggesting future high-k fluctuation measurements could be sensitive to an asymmetry in the k r spectrum introduced due to the presence of strong background flow shear.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Femtosecond stimulated Raman spectro-microscopy for probing chemical reaction dynamics in solid-state materials

Femtosecond stimulated Raman spectroscopy (FSRS) is a chemically specific vibrational technique that has the ability to follow structural dynamics during photoinduced processes such as charge transfer on the ultrafast timescale. FSRS has a strong background in following structural dynamics and elucidating chemical mechanisms; however, its use with solid-state materials has been limited. As photovoltaic and electronic devices rely on solid-state materials, having the ability to track the evolving dynamics during their charge transfer and transport processes is crucial. Following the structural dynamics in these solid-state materials will lead to the identification of specific chemical structures responsible for various photoinduced charge transfer reactions, leading to a greater understanding of the structure–function relationships needed to improve upon current technologies. Furthermore, isolating the specific nuclear motions and molecular structures that drive a desired physical process will provide a chemical blueprint, leading to the rational design and fabrication of efficient electronic and photovoltaic devices. In this perspective, we discuss technical challenges and experimental developments that have facilitated the use of FSRS with solid-state samples, explore previous studies that have identified structure–function relationships in charge transfer reactions, and analyze the future developments that will broaden and advance the field.

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

Development of a tomographic reconstruction method for axisymmetric D α emission profiles in the ITER plasma boundary

A tomographic method for reconstructing the axially symmetric D α emission profile in the ITER scrape-off layer and divertor from D α intensity measurements in the fields of view (FoV) of Vis/IR TV and Divertor Impurity Monitor diagnostics is under development. The method takes into account the strong background signal due to stray light from divertor produced by reflections from the metal wall of the vacuum chamber. The method allows to filter out the reflections in D α signals measured in the main chamber. Here, the accuracy of this method is tested within the framework of a synthetic diagnostic, which uses the Raysect and Cherab numerical codes for ray-tracing simulations. The D α emission profiles, simulated with the SOLPS and OEDGE codes, are used as synthetic experimental data. Uncertainty in light reflection properties of the first wall (FW) is the major factor affecting the accuracy of the D α emission reconstruction. The dependence on the uncertainty in the FW surface roughness and on the ratio of diffusive to specular reflection of the error in recovering useful D α signals (the direct light without reflections) in the FoV of the ITER main chamber H-alpha and Visible Spectroscopy Diagnostic is obtained.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Neutrino identification with scintillation light in MicroBooNE

MicroBooNE is a neutrino experiment which employs a liquid argon (LAr) time projection chamber (TPC) to record neutrino interactions from Fermilab's neutrino beamlines. The experiment's primary objective is to study low-energy νe interactions from the Booster Neutrino Beamline (BNB). Located on the surface, the detector is affected by a continuous rate of cosmic-rays. This leads to one neutrino interaction for every 104 cosmic rays observed in the TPC, making it difficult to isolate neutrino interactions in the detector using charge alone. MicroBooNE's trigger makes use of prompt scintillation light and plays an essential role in both performing strong background rejection and significantly reducing data-rates. Furthermore, a series of novel techniques relying on scintillation light are used to isolate beam-induced activity. This document briefly presents MicroBooNE's scintillation-light based trigger and novel Flash-Matching pattern recognition techniques for cosmic-rejection. This work serves as the foundation of neutrino analyses in LArTPC detectors and is therefore of interest to the broader short- and long-baseline neutrino programs being launched at Fermilab.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Automatic microseismic event picking via unsupervised machine learning

SUMMARY Effective and efficient arrival picking plays an important role in microseismic and earthquake data processing and imaging. Widely used short-term-average long-term-average ratio (STA/LTA) based arrival picking algorithms suffer from the sensitivity to moderate-to-strong random ambient noise. To make the state-of-the-art arrival picking approaches effective, microseismic data need to be first pre-processed, for example, removing sufficient amount of noise, and second analysed by arrival pickers. To conquer the noise issue in arrival picking for weak microseismic or earthquake event, I leverage the machine learning techniques to help recognizing seismic waveforms in microseismic or earthquake data. Because of the dependency of supervised machine learning algorithm on large volume of well-designed training data, I utilize an unsupervised machine learning algorithm to help cluster the time samples into two groups, that is, waveform points and non-waveform points. The fuzzy clustering algorithm has been demonstrated to be effective for such purpose. A group of synthetic, real microseismic and earthquake data sets with different levels of complexity show that the proposed method is much more robust than the state-of-the-art STA/LTA method in picking microseismic events, even in the case of moderately strong background noise.

Chen, Yangkang↗
DOE OSTI2023

Spectrum of kinetic-Alfvén-wave turbulence: intermittency or tearing mediation?

We investigate the spectral properties of the electromagnetic fluctuations of sub-ion scale turbulence in weakly collisional, low-beta plasmas using a two-field isothermal gyrofluid model. The numerical results strongly support a description of the turbulence as a critically balanced Kolmogorov-like cascade of kinetic Alfvén wave fluctuations, as amended by previous studies to include intermittency effects. The measured universal index of the energy spectra from systems with different flux-unfreezing mechanisms excludes the role of tearing mediation in determining the spectra. The fluctuations remain isotropic in the plane perpendicular to the strong background magnetic fields as they cascade to smaller scales, which explains the absence of tearing mediation. The calculation of high-order, multipoint structure functions of magnetic fluctuations suggests that the intermittent structures have a quasi-2D, sheet-type morphology. In conclusion, these results are useful for explaining recent observations of the spectrum and structure of magnetic and density fluctuations in the solar wind at sub-proton scales, and are relevant for modelling the energy dissipation in a broad range of astrophysical systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Photon Doppler Velocimetry to Spatially Resolve Plasma Density in a Power Flow Gap

The understanding of power flow plasmas is important as we look towards next generation pulsed power (NGPP) as current losses could prohibit the goals of that facility. Therefore, it is important to have accurate diagnostics of the plasma parameters on the current machines, which can be used to help inform and improve simulations. Having these plasma parameters will help validate models and simulations to provide confidence when they are expanded to conditions relevant to NGPP. One important plasma parameter that can be measured is the electron density, which can be measured by photonic Doppler velocimetry (PDV). A PDV system has several key advantages over other interferometers by measuring relatively low densities (> 1 × 10 15 cm -2 ) with both spatial and temporal resolution. Experiments were performed on the Mykonos pulsed power machine, which is a 1 MA sub scale machine in which recent platforms have been developed to explore current densities relevant to the inner magnetically insulated transmission line (MITL) on the Z machine. Experiments were performed on two different platforms, the thin foil platform and the Mykonos parallel plate platform (MP3). In addition, a combination of both single-point and multi-point measurements were used. The single-point measurements proved to be very promising, providing a clear increase in density at about 70 ns into the current rise on thin foil experiments up to about 5 × 10 17 cm -3 before the probe stopped providing signal. While we did also see returns from multi-point measurements on both platforms, the signals were not as easy to interpret due to strong background effects. However, they do show initial promise for this diagnostic to measure density at several points across a 1 mm gap. These measurements provide insights in how to improve the diagnostic so that it can provide useful information on power flow relevant experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Automated Credibility Assessments of User Features in Scientific Software

Scientific software (SciSoft) is complex, often containing a mixture of production capabilities co-mingled with features under active research and development. Furthermore, SciSoft is often developed over decades by non-computer scientists who may not have a strong background in or prioritize software architecture design, testing, and quality (e.g., test coverage). These conditions lead to difficulty in understanding which software components or functions implement what user-facing features and therefore those features’ software quality pedigree. This lack of understanding poses challenges in assessing readiness and credibility of user features, and often relies on a SciSoft subject matter expert’s (SME) laborious investigation and assertion. This final report of a one-year Computing and Information Sciences Lab Directed Research and Development project presents a general framework for modeling SciSoft architecture as a direct relationship between user features and the software components/functions that implement them. Our approach leverages automated labeling of the SciSoft’s regression test suite and employs machine learning algorithms to construct the architecture model. We demonstrate this framework on the Solid Mechanics component of the SIERRA multi-physics engineering analysis suite developed at Sandia National Laboratories.

97 MATHEMATICS AND COMPUTING↗