SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Analytical and experimental effort explores possibility of using charged particles as diagnostic tool in study of fluid flows. Test program involved right circular cylinder and airfoil located in large wind tunnel; ions were injected into flow and resulting currents at surfaces were monitored.
Results of the Low Energy Charged Particle (LECP) experiments on board the Voyager spacecraft, designed to measure the fluxes and compositions of ions of energies 28 keV or greater and electrons of energies 15 keV or greater, during Jupiter encounter are presented. Observations of intense particle bursts coming from Jupiter several weeks before Jovian magnetosphere entry, magnetopause crossings, a hot corotating outer magnetospheric plasma, decreases in particle fluxes at the orbits of the Galilean satellites 10-hr particle flux periodicities and a magnetospheric wind are discussed. A new model of the Jovian magnetosphere based on the Voyager results is presented, and areas of continuing LECP Jovian data analysis are indicated.
Aspects of charged particle transport theory have been studied by Earl (1973, 1974, 1976) in a number of investigations. The investigations were conducted under the assumption that particles propagate along a DC guiding field with negligible perpendicular transport and that pitch-angle scattering by random fields can be described by the Fokker-Planck formalism. The present study provides a generalized and simplified treatment of focused transport. The first step is taken with respect to a perturbation analysis by which the Boltzmann equation is solved in terms of successively improved approximations to its exact solution. The first approximation is the sum of isotropic pseudodiffusive and anisotropic supercoherent components whose coefficients must satisfy two coupled partial differential equations. The normalization constant K and the pseudodiffusive velocity, which appear in the first-order transport equations, are given by simple integrals over the pitch angle.
Recent studies of electron energy deposition in CO2 and CO based upon a large set of electron impact cross sections are utilized to estimate the telluric CO directly produced by various charged-particle deposition mechanisms. The mechanisms considered are (1) lightning, (2) cloud coronal discharges, (3) background radioactivity, (4) natural electrostatic discharges, (5) photoelectrons in the ionosphere, (6) auroral electrons, (7) auroral protons, (8) cosmic rays, and (9) solar wind. 'Ball park' estimates of the global CO production by each of these mechanisms are given. Apart from mechanisms 1, 2, and 5, all CO production mechanisms are estimated to be small compared to artificial sources. If, as appears to be the case, the hot oxygen atoms and ions and other atomic species immediately produced by these three charged-particle deposition mechanisms react rapidly with CO2 to produce CO, these mechanisms can readily lead to CO production levels in the multimegaton-per-year range.
The 2x2 Demonstrator is a prototype detector for the Deep Underground Neutrino Experiment (DUNE)'s Near Detector. Both the 2x2 Demonstrator and the Near Detector itself will have inactive regions wherein there is no sensitivity to charge deposition and light signals that arise from charged particle interactions with liquid argon. In the 2x2, these inactive regions are positioned in-between the active detector modules, which introduces the challenge of inferring what charge signals ought to look like in these regions. This study explores the use of a Sparse 3D Convolutional Neural Network (ConvNet) to infer missing regions in charged particle tracks. Hits corresponding to energy depositions are voxelized into a three-dimensional (3D) grid for each track. Inactive regions within the tracks are replaced with a dense, rectangular 3D grid of voxels, ensuring consistent step sizes in X, Y, and Z directions. Voxels in these dense regions are initialized with an energy value of -1, indicating nonphysical energy or charge. The model is trained to predict which voxels should activate as part of the track and which should not, with the goal of eventually inferring the missing charge or energy values in these voxels. Results indicate that the model accurately predicts track voxels within ±1 unit in X, Y, or Z directions and effectively identifies non-track voxels, despite some overprediction. The approach shows promise in prediction of missing track regions with some accuracy.
Integrated circuits manufactured in CMOS technology, have been developed as diffusion-based charged particle spectrometers for space applications. A four-chip spectrometer designed to count protons and heavier ions was flown on the Clementine spacecraft, and the spectrometer proton response is compared to GOES-6 proton data for the 21 Feb. 1994 solar proton event.
The 2x2 Demonstrator is a prototype detector for the Deep Underground Neutrino Experiment (DUNE)'s Near Detector. Both the 2x2 Demonstrator and the Near Detector itself will have inactive regions wherein there is no sensitivity to charge deposition and light signals that arise from charged particle interactions with liquid argon. In the 2x2, these inactive regions are positioned in-between the active detector modules, which introduces the challenge of inferring what charge signals ought to look like in these regions. This study explores the use of a Sparse 3D Convolutional Neural Network (ConvNet) to infer missing regions in charged particle tracks. Hits corresponding to energy depositions are voxelized into a three-dimensional (3D) grid for each track. Inactive regions within the tracks are replaced with a dense, rectangular 3D grid of voxels, ensuring consistent step sizes in X, Y, and Z directions. Voxels in these dense regions are initialized with an energy value of -1, indicating nonphysical energy or charge. The model is trained to predict which voxels should activate as part of the track and which should not, with the goal of eventually inferring the missing charge or energy values in these voxels. Results indicate that the model accurately predicts track voxels within 1 unit in X, Y, or Z directions and effectively identifies non-track voxels, despite some overprediction. The approach shows promise in prediction of missing track regions with some accuracy.
A scintillator-fiber charged-particle track-imaging detector has been developed using a bundle of square cross-section plastic scintillator fiber optics, proximity focused onto an image intensified Charge Injection Device (CID) camera. Detector to beams of 15 MeV protons and relativistic Neon, Manganese, and Gold nuclei have been exposed and images of their tracks are obtained. This paper presents details of the detector technique, properties of the tracks obtained, and range measurements of 15 MeV protons stopping in the fiber bundle.
The objectives of the Lunar Ejecta and Meteorites Experiment (LEAM) were to measure the long-term variations in cosmic dust influx rates and the extent and nature of the lunar ejecta. While analyzing these characteristics in the data, it was discovered that a majority of the events could not be associated with hypervelocity particle impacts of the type usually identified with cosmic dust, but could only be correlated with the lunar surface and local sun angle. The possibility that charged particles could be incident on the sensors led to an analysis of the electronics to determine if such signals could cause the large pulse height analysis (PHA) signals. A qualitative analysis of the PHA circuit showed that an alternative mode of operation existed if the input signal were composed of pulses with pulse durations very long compared to the durations for which it was designed. This alternative mode would give large PHA outputs even though the actual input amplitudes were small. This revelation led to the examination of the sensor and its response to charged particles to determine the type of signals that could be expected.
Density & intensity distribution of charged particles in stationary geomagnetic field
The 2x2 Demonstrator is a prototype of ND-LAr, the liquid argon time-projection chamber of the Deep Underground Neutrino Experiment’s Near Detector complex. Both the 2x2 Demonstrator and ND-LAr are modular detectors that will have pixelated charge readouts and inactive regions wherein there is no sensitivity to charge deposition and light signals that arise from charged particle interactions with liquid argon. In the 2x2, these inactive regions are located in between the active detector modules, which introduces the challenge of inferring what charge signals ought to look like in these regions. This study explores the use of a Sparse 3D Convolutional Neural Network (ConvNet) to infer missing regions in charged particle tracks. Hits corresponding to energy depositions are voxelized into a three-dimensional grid for each track. Voxels that fall into predefined inactive regions are removed to simulate the lack of detector output. The model is trained to infer the topology of the missing track voxels, with the ultimate goal of inferring the missing charge or energy values in these voxels as well. Results indicate that this approach shows promise in prediction of missing track regions with some accuracy.
Terrestrial radiation environment, and degradation to thermal protection surfaces from low energy charged particles
This work introduces an advanced technique optimized for detecting photons generated by charged particles, leveraging Skipper charge coupled device (Skipper-CCD) image sensors. By analyzing background sources and detection efficiencies, the technique achieves strong agreement between experimental results and Cherenkov-based simulations. It also provides a robust framework for investigating secondary photon production in environments with high fluxes of ionizing particles, such as those anticipated in space-based astronomical instruments. These secondary photons present a critical challenge as background noise for next-generation single-photon resolving imagers used to study faint celestial objects. Furthermore, the method exhibits significant potential for broader applications, including exploring photon generation in various substrate materials and examining their transport through multiple interfaces.
Measures of discrepancy between probability distributions (statistical distance) are widely used in the fields of artificial intelligence and machine learning. We describe how certain measures of statistical distance can be implemented as numerical diagnostics for simulations involving charged-particle beams. Related measures of statistical dependence are also described. The resulting diagnostics provide sensitive measures of dynamical processes important for beams in nonlinear or high-intensity systems, which are otherwise difficult to characterize. Here, the focus is on kernel-based methods such as maximum mean discrepancy, which have a well-developed mathematical foundation and reasonable computational complexity. Several benchmark problems and examples involving intense beams are discussed. While the focus is on charged-particle beams, these methods may also be applied to other many-body systems such as plasmas or gravitational systems.
Here we present a new implicit asymptotic preserving time integration scheme for charged-particle orbit computation in arbitrary electromagnetic fields. The scheme is built on the Crank-Nicolson integrator and continues to recover full-orbit motion in the small time-step limit, but also recovers all the first-order guiding center drifts as well as the correct gyroradius when stepping over the gyration time-scale. In contrast to previous efforts in this direction, the new scheme also features exact energy conservation. In the derivation of the scheme, we find that a new numerical time-scale is introduced. This scale is analyzed and the resulting restrictions on time-step are derived. Based on this analysis, we develop an adaptive time-stepping strategy the respects these constraints while stepping over the gyration scale when physically justified. It is shown through numerical tests on single-particle motion that the scheme's energy conservation property results in tremendous improvements in accuracy, and that the scheme is able to transition smoothly between magnetized and unmagnetized regimes as a result of the adaptive time-stepping.
Range and energy loss for ions tabulated from charged particle tracks in polymers
The design, fabrication techniques and first test results of a new type of micromachined energy analyzer for charged particles are presented.
A search for heavy long-lived multi-charged particles is performed using the ATLAS detector at the LHC. Data collected in 2015-2018 at $\sqrt{s}$ = 13 TeV from pp collisions corresponding to an integrated luminosity of 139 fb -1 are examined. Particles producing anomalously high ionization, consistent with long-lived spin-$\frac{1}{2}$ massive particles with electric charges from |q|=2e to |q|=7e are searched for. No statistically significant evidence of such particles is observed, and 95% confidence level cross-section upper limits are calculated and interpreted as the lower mass limits for a Drell-Yan plus photon-fusion production mode. The least stringent limit, 1060 GeV, is obtained for |q|=2e particles, and the most stringent one, 1600 GeV, is for |q|=6e particles.