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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Sea Ice Collision Risk Assessment for Tidal Turbine Siting in Cook Inlet, Alaska

Cook Inlet has great potential for tidal stream energy development. However, the presence of drifting sea ice could create hazardous collision risks for tidal turbine farms. Before turbines can be installed in Cook Inlet, sites must be surveyed to determine how often sea ice is present, how fast it will be moved by the current, and where the trajectories of drifting sea ice will be concentrated. In this study, we use remotely sensed data to characterize the seasonal sea ice conditions in Cook Inlet, a hydrodynamic model to map the water velocities, and a particle trajectory tracking model to calculate collision risks. The resulting sea ice coverage and collision risk maps will enable tidal energy developers to choose the best locations for the deployment of tidal turbines and other offshore platforms in Cook Inlet.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

GEANT4 Simulations on Faraday Cup Design for PIP-II Laser Wire Scanner System

The PIP-II accelerator upgrade at Fermilab represents a groundbreaking leap forward in high-energy physics research. This ambitious initiative involves enhancing Fermilab's accelerator complex by replacing the current linear accelerator with a warm front end (WFE) capable of accelerating H- beams up to 2.1 MeV. Subsequently, a superconducting linac further accelerates these beams up to 800 MeV. To precisely measure the transverse beam profile, a combination of traditional wire scanners at the WFE section and Laser wire scanners along the superconducting linac are planned for implementation. This investigation centers on refining the Faraday cup design for the PIP-II Laser wire scanners by utilizing GEANT4, a Monte Carlo simulation toolkit. Leveraging this method enables a comprehensive analysis of particle trajectories, energy deposition, secondary electron emission, backscattering, etc., facilitating optimization through adjustments to cup geometries, materials, and placement to maximize its efficiency.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Block segmentation in feature space for realtime object detection in high granularity images

Computer vision has applications in object detection, image recognition and classification, and object tracking. One of the challenges of computer vision is the presence of useful information at multiple distance scales. Filtering techniques may sacrifice details at small scales in order to prioritize the analysis of large-scale features of the image. We present a strategy for coarse-graining multidimensional data while maintaining fine-grained detail for subsequent analysis. The algorithm is based on fixed-size block segmentation in the feature space. We apply this strategy to solve the long-standing challenge of detecting particle trajectories at the Large Hadron Collider in real time.

Computer vision↗
DOE OSTI2023

Strong-field nonsequential double photoionization using virtual-detector theory with path summation

We present an ab initio study of the nonsequential strong-field ionization dynamics of a model two-electron atom with helium character. Single- and double-ionization events are characterized and displayed using detector signals extracted at different points in the two-electron two-dimensional space. The double photoelectron momentum distribution is calculated via coherent path-summation over virtual-particle trajectories. A comparison is made between the momentum distributions obtained with the virtual-detector method, the Schrödinger wave function, and the time-dependent surface flux method developed by Tao and Scrinzi [New J. Phys. 14, 013021 (2012)]. Insights into different ionization and electron recollision pathways are gained from detailed virtual-particle tracking and energy-time readouts. Furthermore, this study demonstrates the extension of virtual-detector theory to strong-field multielectron quantum dynamics and highlights the importance of the evolving quantum phase in quasiclassical electron propagation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Assessing the link between aerosol mixing state, structure and composition and their optical properties: Ascension Island as a testbed for the South‐East Atlantic aerosol regimes

Forest and savanna fires are a major source of pollution over the globe. Such fire events emit to the atmosphere a considerable amount of “fluffy” fractal black looking particles that are often referred to as black carbon (BC) or soot aerosols. In fact, BC particles (aerosols) emitted from savanna and agricultural fires over the African continent play an important role in the region’s and the global climate. These fires occur each year between July and October, which is referred to as the biomass burning (BB) season and are considered among the globe's largest man-made emission sources of BC particles. However, during these fire events, not only BC particles are emitted, but also other types of particles and gases that can interact with each other to create new particles, generating a slew of particles often generally referred to as BB aerosols. Although the majority of the fire emissions occur inland in the sub-Saharan part of Africa, their effect reaches far beyond the continent due to the prevailing easterly winds, which transport those aerosols over the South-East Atlantic (SEA) ocean, off the west-coast of Africa. The reason why these particles are so important to the regional and global climate is that they absorb sunlight radiation, which overall warms the climate. However, the magnitude of this warming effect is highly uncertain and depends upon a multitude of aspects. Our overarching goal for this project was to better understand the changes in the aerosol properties as they transport from fire sources downstream toward the ocean and how this can eventually affect the earth's radiative budget in terms of warming or cooling. Following the above, our work here was focused on the investigation of the African BB aerosol plumes mixing state (mixing of BB aerosols and other aerosol types), composition and size distribution as they transport from the African continent towards the SEA ocean, and their link with some of the commonly measurable bulk optical properties such as mass absorption coefficient (MAC) and single scattering albedo (SSA). We utilized three field missions that were conducted over the SEA ocean between 2016 and 2018. Specifically, we used (1) ground-based measurements from the DOE ARM Mobile Facility (AMF1), which was deployed at Ascension Island (ASI) for the LASIC (Layered Atlantic Smoke Interactions with Clouds) campaign between June 2016 and October 2017, (2) airborne measurements from the UK CLARIFY (Clouds and Aerosol Radiative impacts and Forcing) campaign during Aug-Sep-2017, and (3) airborne measurements from the ORACLES (Observations of Aerosols above Clouds and their interactions) campaign during Aug-2017, and Sep-Oct-2018. The three campaigns cover a relatively large region, from the western African coast on the east towards Ascension Island in the middle of the SEA to the west. We used the data gathered by these campaigns to find how BB properties and composition change from near emission sources (the ORACLES campaign flights) downstream (the CLARIFY flights and the ground based LASIC measurements). We used particle trajectory following methodologies to connect the measurements from the different campaigns, which allowed us to follow a certain aerosol plume (airmass) from near-source towards Ascension Island. We found out that atmospheric aging processes governed by the UV light from the sun (photochemistry) and cloud processes (aqueous chemistry) govern the changes seen in the particle composition during the transport were more dominant in dictating aerosol composition than specific emission composition or source types. We assessed how aerosol optical properties change during the BB season and what are the main drivers of this change. We found that the enhanced ratio of BC to CO is well correlated with single scattering albedo (SSA) and mass absorption coefficient (MACBC), providing a simple way to estimate the aerosol optical characteristics in the south-eastern Atlantic Ocean. From the analysis of the location of BB, the primary source fuel, the water content in the fuel, combined with the mean cloud cover and precipitation in the transport areas of the BB plume, we conclude that the increase in BC/CO from June to August is likely to be caused by burning becoming more flaming (hot fires), and the decrease in BC/CO in September and October may be caused by smoldering (colder) fires. We found that aerosol hygroscopicity increases with decreasing altitude below 2km, and that enhanced BB hygroscopicity at lower altitudes is mainly due to a lower organic aerosol (OA) fraction, increased sulfate fraction, and greater hygroscopicity parameter of OA at lower altitudes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A data-driven method to estimate the antiproton background in Mu2e

The Mu2e experiment at Fermilab will search for the Charged Lepton Flavour Violating (CLFV) process of neutrinoless conversion of muon to electron in the field of an Al nucleus. The experimental signature is a monochromatic 104.97 MeV conversion electron. One of the expected backgrounds to the conversion electron search is antiprotons produced by the proton beam at the Production Target and annihilating in the Stopping Target (ST). The background expected from antiprotons is low but highly uncertain due to the uncertainty in the antiproton production cross section for the Mu2e beam energy in the relevant angular region. Antiprotons are significantly slower than the other beam particles, so they cannot be efficiently suppressed by the time window cut used to reduce the prompt background. At Mu2e energies, antiproton annihilation at rest in the ST is the only source of events with multiple, simultaneous particle trajectories. We utilized this unique feature and developed a novel way to reconstruct the multi-track events and estimate the antiproton background in situ.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

The hidden structure of hydrodynamic transport in random fracture networks

We study the large-scale dynamics and prediction of hydrodynamic transport in random fracture networks. The flow and transport behaviour is characterized by first passage times and displacement statistics, which show heavy tails and anomalous dispersion with a strong dependence on the injection condition. The origin of these behaviours is investigated in terms of Lagrangian velocities sampled equidistantly along particle trajectories, unlike classical sampling strategies at a constant rate. The velocity series are analysed by their copula density, the joint distribution of the velocity unit scores, which reveals a simple, albeit hidden, correlation structure that can be described by a Gaussian copula. Based on this insight, we derive a Langevin equation for the evolution of equidistant particle speeds. In this framework, particle motion is quantified by a stochastic time-domain random walk, the joint density of particle position, and speed satisfies a Klein–Kramers equation. The upscaled theory quantifies particle motion in terms of the characteristic fracture length scale and the distribution of Eulerian flow velocities. That is, it is predictive in the sense that it does not require the a priori knowledge of transport attributes. The upscaled model captures non-Fickian transport features, and their dependence on the injection conditions in terms of the velocity point statistics and average fracture length. It shows that the first passage times and displacement moments are dominated by extremes occurring at the first step. The presented approach integrates the interaction of flow and structure into a predictive model for large-scale transport in random fracture networks.

42 ENGINEERING↗
DOE OSTI2026

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems are coarse-grained into low-dimensional models, the entropic loss of information leads to emergent physics which are dissipative, history-dependent, and stochastic. To machine learn coarse-grained dynamics from time-series observations of particle trajectories, we propose a framework using the metriplectic bracket formalism that preserves these properties by construction; most notably, the framework guarantees discrete notions of the first and second laws of thermodynamics, conservation of momentum, and a discrete fluctuation-dissipation balance crucial for capturing non-equilibrium statistics. We introduce the mathematical framework abstractly before specializing to a particle discretization. As labels are generally unavailable for entropic state variables, we introduce a novel self-supervised learning strategy to identify emergent structural variables. We validate the method on benchmark systems and demonstrate its utility on two challenging examples: (1) coarse-graining star polymers at challenging levels of coarse-graining while preserving non-equilibrium statistics, and (2) learning models from high-speed video of colloidal suspensions that capture coupling between local rearrangement events and emergent stochastic dynamics. We provide open-source implementations in both PyTorch and LAMMPS, enabling large-scale inference and extensibility to diverse particle-based systems.

Computational Engineering, Finance, and Science (c↗
DOE OSTI2022

Nonresonant particle acceleration in strong turbulence: Comparison to kinetic and MHD simulations

Collisionless, magnetized turbulence offers a promising framework for the generation of nonthermal high-energy particles in various astrophysical sites. Yet, the detailed mechanism that governs particle acceleration has remained subject to debate. By means of 2D and 3D particle-in-cell, as well as 3D (incompressible) magnetohydrodynamic (MHD) simulations, we test here a recent model of nonresonant particle acceleration in strongly magnetized turbulence, which ascribes the energization of particles to their continuous interaction with the random velocity flow of the turbulence, in the spirit of the original Fermi model. To do so, we compare, for a large number of particles that were tracked in the simulations, the predicted and the observed histories of particles momenta. The predicted history is that derived from the model, after extracting from the simulations, at each point along the particle trajectory, the three force terms that control acceleration: the acceleration of the field line velocity projected along the field line direction, its shear projected along the same direction, and its transverse compressive part. Overall, we find a clear correlation between the model predictions and the numerical experiments, indicating that this nonresonant model can successfully account for the bulk of particle energization through Fermi-type processes in strongly magnetized turbulence. Additionally we also observe that the parallel shear contribution tends to dominate the physics of energization in the particle-in-cell simulations, while in the magnetohydrodynamic incompressible simulation, both the parallel shear and the transverse compressive term provide about equal contributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

The Heavy Photon Search (HPS) Software Environment

The Heavy Photon Search (HPS) is an experiment at the Thomas Jefferson National Accelerator Facility (JLab) designed to search for a hidden sector photon (A’) in fixed-target electro-production. It uses a silicon microstrip tracking and vertexing detector placed inside a dipole magnet to measure charged particle trajectories and a fast lead-tungstate crystal calorimeter located just downstream of the magnet to provide a trigger and to identify electromagnetic showers. The HPS experiment uses both invariant mass and secondary vertex signatures to search for the A’. The experimental collaboration is small and quite heterogeneous: it is composed of members of the nuclear physics as well as particle physics communities, from universities and national labs from around the US and Europe. Enabling such a disparate group to concentrate on the physics aspects of the experiment required that the software be easy to install and use, and having such limited manpower meant that existing solutions had to be exploited. HPS has successfully completed two engineering runs and completed its first physics run in the summer of 2019. We begin with an overview of the physics goals of the experiment followed by a short description of the detector design. We then describe the software tools used to design the detector layout and simulate the expected detector performance. Event reconstruction involving track, cluster and vertex finding and fitting for both simulated and real data was, to first order, adopted from existing software originally developed for Linear Collider studies. Bringing it all together into a cohesive whole involved the use of multiple software solutions with common interfaces.

Graf, Norman↗
DOE OSTI2021

Modeling Induction Stirring and Particle Tracking in Molten Uranium

Two independent numerical models have been developed to simulate the behavior of carbon impurities in molten uranium metal. Informed by experimental parameters, one model was created using the commercial software Star-CCM+ and compared with another developed using open-source codes, including OpenFOAM, Finite Element Method Magnetics (FEMM) and a First Passage Kinetic Monte Carlo (FPKMC) approach. The target experimental system features a 404g uranium metal charge containing an average carbon concentration of 139 ppm which was melted in a vacuum induction furnace at 1400° C then resolidified. The microstructures of the uranium and its impurities before and after melting have been characterized and reported separately. Prior to simulating the uranium-carbon system described, the numerical models were validated using a previously published nonradioactive experimental system to ensure agreement with expected output values. Focus has been placed on modeling velocity fields under induction stirring and impurity particle trajectories.

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

Geant4 Visualization

Geant4 offers versatile visualization tools to study detector geometry, particle trajectories, and hits. These tools support both interactive and batch modes (e.g., vis.mac). With a unified interface, Geant4 integrates various graphics systems such as G4VisExecutive, OpenGL, Qt, HepRApp, DAWN, VTK, and ToolsSG. Advanced examples, including the ICRP145 Human Phantoms and the gMocren tool, highlight its applications in medical research and simulation and as well as radiation protection and shielding studies. These features make Geant4 a robust framework for exploring particle interactions and supporting domain-specific use cases.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Tomographic X-ray particle tracking velocimetry

We investigate the feasibility of in-laboratory tomographic X-ray particle tracking velocimetry (TXPTV) and consider creeping flows with nearly density matched flow tracers. Specifically, in these proof-of-concept experiments we examined a Poiseuille flow, flow through porous media and a multiphase flow with a Taylor bubble. For a full 360° computed tomography (CT) scan we show that the specially selected 60 micron tracer particles could be imaged in less than 3 seconds with a signal-to-noise ratio between the tracers and the fluid of 2.5, sufficient to achieve proper volumetric segmentation at each time step. In the pipe flow, continuous Lagrangian particle trajectories were obtained, after which all the standard techniques used for PTV or PIV (taken at visible wave lengths) could also be employed for TXPTV data. And, with TXPTV we can examine flows inaccessible with visible wave lengths due to opaque media or numerous refractive interfaces. In the case of opaque porous media we were able to observe material accumulation and pore clogging, and for flow with Taylor bubble we can trace the particles and hence obtain velocities in the liquid film between the wall and bubble, with thickness of liquid film itself also simultaneously obtained from the volumetric reconstruction after segmentation. While improvements in scan speed are anticipated due to continuing improvements in CT system components, we show that for the flows examined even the presently available CT systems could yield quantitative flow data with the primary limitation being the quality of available flow tracers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Measurement of space charge effects and energy calibration in ProtoDUNE-SP

The single-phase liquid argon prototype at CERN (ProtoDUNE-SP) acts as a validation of the design for the DUNE single-phase far detector. With a total mass of 770 tons, it is the largest monolithic liquid argon single-phase time projection chamber in the world. ProtoDUNE-SP collected test-beam in autumn of 2018 and has been collecting cosmic and special calibration data since the end of 2018.The accumulation of positive ions in a LArTPC located on the surface can distort the electric field and the reconstructed particle trajectories. It is critical to understand and correct for the space charge effects in order to achieve the desired spatial and calorimetric resolutions in the LArTPC. This talk will present the measurement of space charge effects and the calorimetric measurements of the detector in ProtoDUNE-SP.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Extreme radiation emission regime for electron beams in strong focusing ion channels and undulators

A fundamental comparison between a magnetic undulator and an ion channel, or betatron, radiation from relativistic electrons is presented. While conventional theories nominally range from the undulator (𝐾 <1) to the wiggler (𝐾 >1) regime, they are only applicable for sufficiently large Lorentz factors (𝛾 0 ≫𝐾). They therefore do not account for high 𝐾/𝛾 0 cases, for which we show that particle trajectories and radiation characteristics strongly deviate from the linear predictions in both magnetic undulators and ion channels. This problem arises from the fundamental differences between a magnetostatically and electrostatically induced oscillation. A reformulation of both the ion channel betatron wavelength and amplitude, as well as the same parameters in a magnetic undulator, permits us to compare cases with equivalent oscillation period and amplitude in the two different scenarios. The notable differences in spectral features of the two radiation mechanisms can then be addressed via numerical simulations of single particle as well as full beam dynamics. Additionally, we identify and quantify a novel transverse orbit precession effect in ion channels for particles with initial angular momentum relative to the device axis. This effect, which is significant in cases of strong transverse kinetic energy oscillations, alters both the radiation divergence and the beam emittance. In this paper, we present this new theoretical framework and compare its results with numerical simulation applied to realizable experimental tests of such radiation sources.

Frazzitta, Andrea [University of Rome “La Sapienza↗
DOE OSTI2022

Evolution of the marker distribution in gyrokinetic $δf$ particle-in-cell simulations

The evolution of the particle weight in a δf particle-in-cell simulation depends on the marker distribution that can evolve in a turbulent field due to turbulent diffusion. When Monte Carlo methods are used to implement the test particle collision operator, or when the particle motion is not strictly Hamiltonian in a collisionless simulation, the marker distribution will evolve along the particle trajectory and, in general, cannot be known exactly. A two-dimensional numerical marker distribution is proposed as an approximation. It is shown to be advantageous over other common methods for evaluating the marker distribution in long-time turbulence simulations. A generalized two-weight δf-method is proposed to mitigate the marker evolution problem.

, Monte Carlo methods↗
DOE OSTI2025

Velocity-space signatures of shock-drift acceleration at quasi-perpendicular collisionless shocks

The shock-drift acceleration of ions at quasi-perpendicular shocks is a well-known kinetic mechanism for the acceleration of a small fraction of incoming ions to high energy. Here, we use a suite of sixteen hybrid simulations of quasi-perpendicular collisionless shocks over the range of Alfvén Mach number 4.3 ≤ M A ≤ 15.8 (corresponding to a range of fast magnetosonic Mach numbers 2.6 ≤ M f ≤ 9.4) and shock-normal angle 45°≤ θ Bn ≤ 90° to identify the velocity-space signature of shock-drift acceleration using the field-particle correlation technique. We show that the features of the ion velocity distribution in the shock foot and ramp regions can be clearly interpreted by analysis of the single-particle trajectory of a reflected ion through the full 3D-3V phase space. The characteristic features of the velocity-space signature of shock-drift acceleration remain qualitatively robust over the full parameter range of our simulations, providing a potential means for its identification using single-point spacecraft measurements. At higher Alfvén Mach numbers M A ≳8 (M f ≳5), kinetic instabilities generate fluctuations of the electromagnetic fields within the shock transition region, leading to fluctuations in and smearing out of the resulting velocity-space signatures, but the signature remains generally robust and identifiable. The results on the shock-drift acceleration of ions presented here represent a novel means to determine more completely the partitioning of upstream bulk flow kinetic energy into plasma heating, particle acceleration, and electromagnetic fields in collisionless shocks.

Howes, Gregory G. [Univ. of Iowa, Iowa City, IA (U↗
DOE OSTI2022

Graph Neural Networks for Charged Particle Tracking on FPGAs

The determination of charged particle trajectories in collisions at the CERN Large Hadron Collider (LHC) is an important but challenging problem, especially in the high interaction density conditions expected during the future high-luminosity phase of the LHC (HL-LHC). Graph neural networks (GNNs) are a type of geometric deep learning algorithm that has successfully been applied to this task by embedding tracker data as a graph—nodes represent hits, while edges represent possible track segments—and classifying the edges as true or fake track segments. However, their study in hardware- or software-based trigger applications has been limited due to their large computational cost. In this paper, we introduce an automated translation workflow, integrated into a broader tool called hls4ml , for converting GNNs into firmware for field-programmable gate arrays (FPGAs). We use this translation tool to implement GNNs for charged particle tracking, trained using the TrackML challenge dataset, on FPGAs with designs targeting different graph sizes, task complexites, and latency/throughput requirements. This work could enable the inclusion of charged particle tracking GNNs at the trigger level for HL-LHC experiments.

Elabd, Abdelrahman↗