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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Effect of particle size and moisture on flow performance of loblolly pine anatomical fractions: Experimental findings and model predictions

The rising energy demand has highlighted biomass as a promising next-generation energy source. However, commercializing biomass-derived energy faces challenges, particularly in handling biomass feedstock. Factors like particle size, shape, moisture content, and surface roughness significantly impact biomass flowability. This study addresses a crucial knowledge gap by examining the effects of particle size and moisture content on the flow behavior and shear properties of different anatomical fractions of loblolly pine (Pinus taeda). The bulk shear behavior was examined using a Schulze ring shear tester, while flow performance was tested through gravity-driven flow experiments in a variable wedge-shape hopper. Results were incorporated into empirical and machine learning-based flow prediction models to evaluate their accuracy and limitations. The study found that samples with higher moisture content show higher unconfined yield strength. The critical arching distance increased with particle size, e.g., from approximately 13 and 33 mm for 2- and 6-mm whole chips, respectively at a 32-degree inclination angle. Conversely, the flow rate decreased for a given hopper opening as particle size increased. For instance, at a 60-mm hopper opening and a 32-degree inclination angle, the mass flow rates for 2- and 6-mm whole chips were 7.83 and 6.42 tonne/h, respectively. The empirical model consistently overpredicted the mass flow rate for all anatomical fractions, while the machine learning model more accurately predicted the central tendency of flow rate but was insensitive to varying tissue proportions. These novel findings provide comprehensive characterization of anatomical fractions, reveal significant combined effects of particle size and moisture content on biomass flow behavior, and demonstrate a better predictive accuracy of a machine learning model, all of which are useful for optimizing material handling strategies and biomass utilization technologies in the industry.

09 - BIOMASS FUELS↗
NASA NTRS1982

Nonlinear longitudinal resonance interaction of energetic charged particles and VLF waves in the magnetosphere

The longitudinal resonance of waves and energetic electrons in the Earth's magnetosphere, and the possible role this resonance may play in generating various magnetospheric phenomena are studied. The derivation of time-averaged nonlinear equations of motion for energetic particles longitudinally resonant with a whistler mode wave propagating with nonzero wave normal is considered. It is shown that the wave magnetic forces can be neglected at lower particle pitch angles, while they become equal to or larger than the wave electric forces for alpha 20 deg. The time-averaged equations of motion were used in test particle simulation which were done for a wide range of wave amplitudes, wave normals, particle pitch angles, particle parallel velocities, and in an inhomogeneous medium such as the magnetosphere. It was found that there are two classes of particles, trapped and untrapped, and that the scattering and energy exchange for those two groups exhibit significantly different behavior.

Tkalcevic, S.↗
NASA NTRS2003

Magnetic Microspheres and Tissue Model Studies for Therapeutical Applications

Hyperthermia is a well known cancer therapy and consists of heating a tumor region to the elevated temperatures in the range of 40-45 C for an extended period of time (2-8 hours). This leads to thermal inactivation of cell regulatory and growth processes with resulting widespread necrosis, carbonization and coagulation. Moreover, heat boosts the tumor response to other treatments such as radiation, chemotherapy or immunotherapy. Of particular importance is careful control of generated heat in the treated region and keeping it localized. Higher heating, to about 56 C can lead to tissue thermo-ablation. With accurate temperature control, hyperthermia has the advantage of having minimal side effects. Several heating techniques are utilized for this purpose, such as whole body hyperthermia, radio-frequency (RF) hyperthermia, ultrasound technique, inductive microwave antenna hyperthermia, inductive needles (thermoseeds), and magnetic fluid hyperthermia (MFH).MFH offers many advantages as targeting capability by applying magnets. However, this technology still suffers significant inefficiencies due to lack of thermal control. This paper will provide a review of the topic and outline the ongoing work in this area. The main emphasis is in devising ways to overcome the technical difficulty in hyperthermia breast therapy of achieving a uniform therapeutic temperature over the required region of the body and holding it steady for an extended period (2-3 hours). The basic shortcomings of the presently utilized heating methods stem from the non-uniform thermal properties of the tissue and the point heating characteristics of the techniques without any thermal control. Our approach is to develop a novel class of magnetic fluids, which have inherent thermoregulating properties. We have identified a few magnetic alloys which can serve as suitable nano to micron-size particle material. The objective is to synthesize, characterize and evaluate the efficacy of Thermo Regulating Magnetic Fluids (TRMF) for hyperthermia therapy. The development of a tissue model and testing the fluid dynamics of particle motion, settling, distribution in the tissue matrix and heat generation will be discussed.

Ramachandran, N.↗
NASA NTRS2018

Radiation Testing Electronics with Heavy Ions-The Best Way to Hit a Target Moving Ever Exponentially Faster

In 1972, when engineers at Hughes Aircraft Corporation discovered that errors in their satellite avionics were being caused by cosmic rays (so-called single-event effects, or SEE), Moore's Law was only 7 years old. Now, more than 45 years on, the scaling that drove Moore's Law for its first 35 years has reached its limits. However, electronics technology continues to evolve exponentially and SEE remain a formidable issue for use of electronics in space. SEE occur when a single ionizing particle passes through a sensitive volume in an active semiconductor device and generates sufficient charge to cause anomalous behavior or failure in the device. Because SEE can occur at any time during the mission, the emphasis of SEE risk management methodologies is ensuring that all SEE modes in a device under test are detected by the test. Because a particle's probability of causing an SEE generally increases as the particle becomes more ionizing, heavy-ion beams have been and remain the preferred tools for elucidating SEE vulnerabilities. In this talk we briefly discuss space radiation environments and SEE mechanisms, describe SEE test methodologies and discuss current and future challenges for use of heavy-ion beams for SEE testing in an era when the continued validity of Moore's law depends on innovation rather than CMOS scaling.

space radiation environments↗
DOE OSTI2025

Fully plasma-based electron injector for a linear collider or XFEL

We demonstrate through high-fidelity particle-in-cell (PIC) simulations a simple approach for efficiently generating 20 + GeV electron beams with the necessary charge, energy spread, and emittance for use as an injector in a future linear collider or a next generation XFEL. A high quality injected bunch is generated by self-focusing an unmatched electron driver in a nonlinear plasma wakefield. Over pump depletion distances, the drive beam dynamics and self-loading effects lead to high energy, low-energy spread output beams. For plasma densities of 10 18 c⁢m −3 , PIC simulation results indicate that self-injected beams with 0.52 n⁢C charge can be accelerated to 20 GeV with projected core energy spreads of ≲ 1%, normalized slice emittances of 110n⁢m, peak normalized brightness of ≳ 10 19 A/m 2 /rad 2 , and transfer efficiencies of ≳ 44%.

Particle acceleration in plasmas↗
DOE OSTI2022

Low energy neutrino detection with a compact water-based liquid scintillator detector

In this study, the conceptual design and physics simulations of a near-field Water-based Liquid Scintillator (WbLS) detector placed 100 m from the Akkuyu Nuclear Power Plant (ANPP), currently under construction and aiming at being Turkey’s first nuclear power plant, is presented. The ANPP is an excellent opportunity for neutrino studies and the development of an R &D program for neutrino detectors in Turkey. The Reactor Neutrino Experiments of Turkey (RNET) program includes a compact detector with a 2.5-ton volume of WbLS and a ~ 30% photo-coverage, and the program is planned to be expanded with a medium-size 30-ton detector that will be an international testbed for WbLS and new detector technologies through low energy neutrino studies. In the following, the focus will be on the smaller ~2.5 ton detector, instrumented with 8-in. high quantum efficiency PMTs and two layers of cosmic veto paddles, covering all sides of the detector, to track and veto cosmic particles. Inverse Beta Decay (IBD) events from electron anti-neutrinos generated in the reactor core are simulated using the RAT-PAC simulation package and several liquids with different percentages of Liquid Scintillator (LS) and Gadolinium (Gd) are investigated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Uncertainty-aware particle segmentation for electron microscopy at varied length scales

Electron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron scale. To study the powder samples that are widely used in materials development, scanning electron microscopes (SEMs) are increasingly used at the laboratory scale to generate large datasets with hundreds of images. Parsing these images to identify distinct particles and determine their morphology requires careful analysis, and automating this process remains challenging. In this work, we enhance the Mask R-CNN architecture to develop a method for automated segmentation of particles in SEM images. We address several challenges inherent to measurements, such as image blur and particle agglomeration. Moreover, our method accounts for prediction uncertainty when such issues prevent accurate segmentation of a particle. Recognizing that disparate length scales are often present in large datasets, we use this framework to create two models that are separately trained to handle images obtained at low or high magnification. By testing these models on a variety of inorganic samples, our approach to particle segmentation surpasses an established automated segmentation method and yields comparable results to the predictions of three domain experts, revealing comparable accuracy while requiring a fraction of the time. These findings highlight the potential of deep learning in advancing autonomous workflows for materials characterization.

36 MATERIALS SCIENCE↗
NASA NTRS2011

Linearized T-Matrix and Mie Scattering Computations

We present a new linearization of T-Matrix and Mie computations for light scattering by non-spherical and spherical particles, respectively. In addition to the usual extinction and scattering cross-sections and the scattering matrix outputs, the linearized models will generate analytical derivatives of these optical properties with respect to the real and imaginary parts of the particle refractive index, and (for non-spherical scatterers) with respect to the ''shape'' parameter (the spheroid aspect ratio, cylinder diameter/height ratio, Chebyshev particle deformation factor). These derivatives are based on the essential linearity of Maxwell's theory. Analytical derivatives are also available for polydisperse particle size distribution parameters such as the mode radius. The T-matrix formulation is based on the NASA Goddard Institute for Space Studies FORTRAN 77 code developed in the 1990s. The linearized scattering codes presented here are in FORTRAN 90 and will be made publicly available.

Analytic linearization↗
DOE OSTI2025

Ponderomotive barriers in rotating mirror devices using static fields

Particularly for aneutronic fusion schemes, it is advantageous to manipulate the fuel species differently from one another and to expel ash promptly. The ponderomotive effect can be used to selectively manipulate particles. It is commonly a result of particle–wave interactions and has a complex dependence on the particle charge and mass, enabling species selectivity. If the plasma is rotating, e.g., due to E x B motion, the ponderomotive effect can be generated using static (i.e., time-independent) perturbations to the electric and magnetic fields, which can be significantly cheaper to produce than time-dependent waves. We propose that this feature can be particularly useful in rotating mirror machines where mirror confinement can be enhanced by rotation, both through centrifugal confinement and additionally through a ponderomotive interaction with a static azimuthal perturbation. We identify specific static perturbations that generate a ponderomotive barrier and other perturbations that can generate either a repulsive barrier or an attractive ponderomotive well, which can be used to attract particles of a certain species while repelling another. We identify the regimes in which the ponderomotive potential can enhance net plasma confinement and the regime in which plasma confinement is not enhanced. The viability of each of these effects is found to be dependent on the specifics of the rotation profile and the resultant dispersion relation in the rotating plasma.

Aneutronic fusion↗
DOE OSTI2025

Discriminative versus generative approaches to simulation-based inference

Most of the fundamental, emergent, and phenomenological parameters of particle and nuclear physics are determined through parametric template fits. Simulations are used to populate histograms which are then matched to data. This approach is inherently lossy, since histograms are binned and low-dimensional. Deep learning has enabled unbinned and high-dimensional parameter estimation through neural likelihood(-ratio) estimation. We compare two approaches for neural simulation-based inference (NSBI): one based on discriminative learning (classification) and one based on generative modeling. These two approaches are directly evaluated on the same datasets, with a similar level of hyperparameter optimization in both cases. In addition to a Gaussian dataset, we study NSBI using a Higgs boson dataset from the FAIR Universe Challenge. We find that both the direct likelihood and likelihood ratio estimation are able to effectively extract parameters with reasonable uncertainties. For the numerical examples and within the set of hyperparameters studied, we found that the likelihood ratio method is more accurate and/or precise. Both methods have a significant spread from the network training and would require ensembling or other mitigation strategies in practice.

high energy physics↗
DOE OSTI2025

An open-source hybrid unstructured mesh - CAD fusion multiphysics analysis workflow in SALAMANDER

Plasma facing components in fusion devices will endure extreme neutron and heat fluxes. To facilitate their design using simulation tools, the open-source Fusion Module, Fusion ENergy Integrated multiphys-X (FENIX) framework is being developed to model these components with a high-fidelity multi-physics multi-dimensional approach. It can iteratively resolve couplings between all the physics at play, from neutron radiation, to thermomechanics, to near-wall plasma dynamics. This framework is based on the Multiphysics Object Oriented Simulation Environment (MOOSE), which is developed by a collaboration of US National Laboratories since 2008, for advanced nuclear, geomechanics simulations and other applications. FENIX couples numerous simulation tools, including OpenMC, the Tritium Migration Analysis Program v8, the NekRS CFD software, and most MOOSE modules. For the coupling of radiation transport and other physics, FENIX supports a hybrid workflow between Computer Assisted Design (CAD) and unstructured mesh geometries. The CAD can be generated from skinning the unstructured mesh, to enable a coarse geometry for efficient particle transport, but still resolving the local material compositions and temperature gradients. Neutron transport is performed using DAGMC on the CAD, and Cardinal, integrated in FENIX, maps tallied quantities, such as the heat deposition or the tritium generation rates, from a tally volumetric mesh to the other physics’ unstructured mesh. This coupling was exercised on a simplified tokamak geometry, coupling neutron transport with the heat conduction equation, and on a monoblock divertor problem, coupling additionally with tritium migration. Mesh convergence studies highlight the importance of the mapping conservativeness. Coupling with thermo-mechanics is further enabled by the generalization of the approach to moving meshes. The presentation will include these coupled analysis as well as an update on status of the FENIX framework.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1994

Evidence for particle acceleration during magnetospheric substorms

Magnetospheric substorms represent the episodic dissipation of energy stored in the geomagnetic tail that was previously extracted from the solar wind. This energy release produces activity throughout the entire magnetosphere-ionosphere system, and it results in a wide variety of phenomena such as auroral intensifications and the generation of new current systems. All of these phenomena involve the acceleration of particles, sometimes up to several MeV. We present a brief overview of substorm phenomenology. We then review some of the evidence for particle acceleration in Earth's magnetosphere during substorms. Such in-situ observations in this most accessible of all cosmic plasma domains may hold important clues to understanding acceleration processes in more distant astrophysical systems.

Lopez, Ramon E.↗
NASA NTRS1995

Orbits Close to Asteroid 4769 Castalia

We use a radar-derived physical model of the kilometer sized, uniformly rotating asteroid 4769 Castalia (1989 PB) to investigate close orbit dynamics. We establish that a Jacobi integral exists for particles orbiting this asteroid, and the attendant zero-velocity surfaces are generated and examined. We find families of periodic orbits and determine their stability. We find that all synchronous orbits and direct orbits within 3 mean radii of Castalia are unstable and are subject to impact or escape from Castalia. We find that retrograde orbits are mostly stable and allow particles to orbit closely to the asteroid surface.

Asteroid↗
DOE OSTI2023

Simulation of radioactive plume transport in the atmosphere including dynamics of particle aggregation and breakup

Accurate prediction of the atmospheric transport of debris particles relies heavily on our knowledge of the size distribution of the particles within a debris cloud. Assuming a fixed particle size during simulations is not always viable since the size distribution of the debris can change during transport. Various microphysical processes, such as aggregation and breakup, influence debris particles and dictate any changes to the size distribution. To track those changes that can occur, a population balance model can be adopted and instituted within a model framework. Nonetheless, many of the models that simulate the transport of radioactive debris following a device-driven fission incident have historically neglected to consider these processes. As such, this work describes our effort to develop a modeling framework capable of simulating the transport and deposition of a radioactive plume generated from a fission incident with a dynamic population balance including particle aggregation and breakup. Herein the impact of aggregation and breakup, individually and collectively, on the particle size distribution is explored using the developed framework. When simulating aggregation, for example, six mechanisms, including Brownian coagulation, the convective enhancement to Brownian coagulation, van der Waals-viscous force correction for Brownian coagulation, gravitational collection, turbulent inertial motion, and turbulent shear, are considered. Brownian coagulation and its corrections have, as one would expect, a large impact on relatively small aggregates. Aggregates with a diameter that is less than or equal to 1.0 μm, for instance, comprise 50.6 vol % of all aggregates in the absence of aggregation and 31.2 vol % when Brownian coagulation and its corrections are considered. Gravitational collection and, to a much lesser extent, turbulent shear and turbulent inertial motion are, conversely, of great importance to relatively large aggregates (i.e., diameter greater than 3.0 μm). Additionally, the individual effects of atmospheric and particle parameters, such as wind speed and particle density, are examined. Of the parameters examined, turbulent energy dissipation and aggregate fractal dimension (i.e., aggregate shape with lower values representing more irregular particles) were of substantial importance since both terms directly impact aggregate stability and, by extension, the breakup rate. Large-scale transport and deposition simulations in a dry atmosphere are also presented and discussed as a proof of concept.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

Evaluation of radiation hardness of semiconductor materials against alpha particles for an API detector

An Associated Particle Imaging (API) system consists of a high vacuum chamber where deuterium ions are accelerated on a tritium-loaded target, resulting in alpha particles and neutrons emitted back-to-back, the latter escaping the chamber and used, for example, for tomography of a high-Z sample. An accurate determination of the alpha position is crucial to determine the trajectory of the neutron. Existing API systems have several limitations which a semiconductor-based API detector placed inside the vacuum chamber should not present. The semiconductor material can be either silicon or diamond. In particular, large and fast signals are generated by the alpha interactions in these materials. A pixelated API detector will measure the time and hit position of the alphas produced in the reaction. However, during the lifetime of the generator, the semiconductor detector will be exposed to an intense flux of alpha particles that will degrade its performance over time. To assess the radiation hardness of silicon and diamond against the alpha particles, we exposed single diodes made of either of the two materials to a 5 MeV alpha flux generated by an 241Am radioactive source. During irradiation, the diodes were biased and mounted on current-sensitive preamplifier boards. We have therefore been able to measure insitu the evolution of the waveforms as the damage was accumulating in their substrates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Metal oxide candidates for thermochemical water splitting obtained with a generative diffusion model

Generative diffusion models (DMs) for inorganic crystalline materials are being actively investigated for their potential to expand the chemical and structural design spaces for known functional materials. Generative candidates are particularly useful for applications where few functional, let alone commercially viable, materials currently exist, such as metal oxides for thermochemical water-splitting, which have strict requirements for defect thermodynamics and host stability. Here, we critically examine generated metal oxides from the M ATTER G EN DM conditioned on select chemical systems for thermochemical water splitting applications. Perhaps most notably, we find that M ATTER G EN predicts a novel, thermodynamically stable, quinary metal oxide, Ba 2 SrInFeO 6 , although this compound represents an ordered and layered substitution within the same A 3 B 2 O 6 structural prototype as its two ternary end members. Detailed density functional theory calculations and spin configuration sampling for this material and its possible decomposition products—beyond what existed in M ATTER G EN training data—are required to quantitatively validate hull energy predictions and conclusions of stability. Furthermore, the material exhibits oxygen defect formation energies appropriate for thermochemical water splitting, warranting targeted investigation in an experimental validation campaign, along with other future M ATTER G EN candidates in this application space.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Muon Decay Study at NSRL

A muon is an unstable subatomic particle, classified as a lepton according to the Standard Model. Muons are charged leptons with 1/2 spin. They were discovered by Neddermeyer and Anderson from hadronic cosmic ray showers. Figure 1 provides a visual representation of a cosmic ray shower in Earth’s atmosphere. At a height of 50 000 m in the atmosphere, a primary cosmic ray (mainly protons, helium, a heavy nucleus or a gamma ray) interacts with a gas molecule. The striking of a gas molecule creates a cosmic ray shower, where the energy of the primary particle is distributed among many secondary particles and gamma rays. With each interaction, the cosmic ray particles in the shower lose energy but distribute this energy among a higher number of particles. From the initial interaction, primarily heavy nuclei and pions are generated. Heavy nuclei will interact with gas molecules to produce protons, gamma rays, electrons and pions. The dominant decay mode of neutral pions is to two gamma rays, while charged pions decay to a muon and a neutrino (equation 1): $π^+ → µ^+$ + $\overline ν$ $_µ$; $π → µ$ $^-$ + $\overline v$ $_µ$.

43 PARTICLE ACCELERATORS↗