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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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All sources NASA NTRS DOE OSTI

DOE OSTI2025

New electric force and charge exchange modules in discrete element model enables particle dynamics simulation in electric field

Discrete element modeling (DEM) is an important technique for particle dynamics simulation. The field of metal additive manufacturing often utilizes DEM to simulate the rheological behaviors of powder. Standard contact and short-range interactions are sufficient in most cases but insufficient to describe the particle dynamics with the influence of an electric field. Modeling such a system requires additional physics to describe the particle–field interactions. The relevant physics has been experimentally understood but is not yet available in DEM. Here, we develop a charge exchange and an electric force module. The electric force module governs particle response to the electric field, while the charge exchange module enables particles to acquire proper charge during contact with charged geometries. We validate the modules against analytical calculations and high-speed videos of electrostatic powder deposition experiments. Notably, the model struggles to capture the initial particle levitation. We later deploy a modified electric field, as supported by static electric field simulation, to better approximate the electric field penetration into the powder layer. This modification improves the model’s capability of simulating realistic particle levitation. The results highlight the challenges of modeling particle behaviors in the electric field while demonstrating the feasibility of obtaining quantitative results, which are difficult to measure experimentally.

charge exchange↗

NASA NTRS1995

Magnetotail particle dynamics and transport

The main thrust of our research is to study the consequences of particle dynamics in the current sheet region of the magnetotail. The importance of understanding particle dynamics, in and near current sheets, cannot be over estimated, especially in light of NASA's recent interest in developing global circulation models to predict space weather. We have embarked on a long-term study to investigate the electrical resistance due to chaotic behavior, compare this resistance to inertial effects, and relate it to that resistance required in MHD modeling for reconnection to proceed. Using a single-particle model and observations, we have also found that a neutral line region can be remotely sensed. We plan to evaluate other cases of satellite observations near times of substorm onset to elucidate the relationship between the temporal development of a near-Earth neutral line and onset.

Speiser, Theodore W.↗

NASA NTRS1990

Fractal boundaries in magnetotail particle dynamics

It has been recently established that particle dynamics in the magnetotail geometry can be described as a nonintegrable Hamiltonian system with well-defined entry and exit regions through which stochastic orbits can enter and exit the system after repeatedly crossing the equatorial plane. It is shown that the phase space regions occupied by orbits of different numbers of equatorial crossings or different exit modes are separated by fractal boundaries. The fractal boundaries in an entry region for stochastic orbits are examined and the capacity dimension is determined.

Chen, J.↗

NASA NTRS1990

Observational signatures of nonlinear magnetotail particle dynamics

It has been predicted that the nonlinear particle dynamics in the magnetotail leads to a class of resonance structures in the quiet-time ion distribution functions in the central plasma sheet (CPS). These structures exhibit a scaling law of H to the 1/4 power. The first identification of such a scaling law in quiet-time CPS distribution functions obtained aboard ISEE 1 is reported. A method is proposed which uses the observed resonance structures to determine the quiet-time current sheet thickness based on a measurement of the distribution function and magnetic field obtained by one satellite.

Chen, James↗

DOE OSTI2025

Symplectic neural network and its application to charged particle dynamics in electromagnetic fields

Recently, machine learning models have shown many successes in various applications in science and technology. In this work, we focus on the charged particle dynamics, with the development of a class of symplectic neural networks, including a linear version, SympMat, and a nonlinear version, HénonNet. Both are designed to preserve the structure of Hamiltonian systems. We show that they can be used to model relevant Hamiltonian systems of interest in plasma physics and astrophysics, for linear and nonlinear charged particle dynamics, with the potential to bridge multi-scale simulations. These symplectic neural networks are adapted to the applications in plasma simulations and particle-wave interaction with parametric dependence and periodicity, where we have investigated their performance and accuracy. In particular, SympMat is shown to outperform the traditional Boris particle pusher down to the sub-gyroperiod scale in the case of charged particles in uniform magnetic fields. HénonNet successfully predicts the hot electron distribution, which is validated against theoretical results. These results highlight the potential of symplectic neural networks as a trajectory integrator for particle-in-cell simulations or a fast surrogate to replace conventional numerical schemes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1985

Calculation of particle dynamics effects on laser velocimeter data

In order to analytically assess the effects of particle dynamics on laser velocimeter measurements, the particle response to the fluid in which it is entrained must be modeled. The equation of particle motion derived at Arnold Engineering and Development Center (AEDC), is used to model the motion of the particle. The equation is derived from the Navier-Stokes equation under the assumption of unsteady Stokes flow. It should be noted that the Stokes flow eliminates the need for a far field boundary condition, and hence eliminates any normal (lift) forces. To extend the equation to higher particle slip velocities, the Stokes drag is replaced with the particle drag law, modified to include heat transfer effects. The drag coefficient accounts for inertial, rarefaction, compressibility, shape, and heat transfer effects.

Nichols, R. H.↗

NASA NTRS1993

Experiments on the enhancement of compressible mixing via streamwise vorticity. II - Vortex strength assessment and seed particle dynamics

The effect of streamwise vorticity on compressible axisymmetric mixing layers is examined using vortex strength assessment and seed particle dynamics analysis. Experimental results indicate that the particles faithfully represent the dynamics of the turbulent swirling flow. A comparison of the previously determined mixing layer growth rates with the present vortex strength data reveals that the increase of turbulent mixing up to 60 percent scales with the degree of swirl. The mixing enhancement appears to be independent of the compressibility level of the mixing layer.

Naughton, J. W.↗

NASA NTRS1991

Effects of collisions on the nonlinear particle dynamics in the magnetotail

The effects of collisional processes on the nonlinear particle dynamics in the magnetotail are considered.A simple collision operator is developed to model the effects of pitch-angle and energy scattering. It is found that the phase space partition persists for up to moderate scattering amplitudes in pitch-angle and energy, and that certain distribution function features are robust even in the presence of large amplitude collisions. It is shown that if the collisions are due to short scale length electrostatic fields, excessively large field amplitudes are required to signifiantly alter the phase space structures and the resulting distribution function features.

Holland, Daniel L.↗

DOE OSTI2025

Nyström type exponential integrators for strongly magnetized charged particle dynamics

Solving for charged particle motion in electromagnetic fields (i.e. the particle pushing problem) is a computationally intensive component of particle-in-cell (PIC) methods for plasma physics simulations. This task is especially challenging when the plasma is strongly magnetized due numerical stiffness arising from the wide range of time scales between highly oscillatory gyromotion and long term macroscopic behavior. A promising approach to solve these problems is by a class of methods known as exponential integrators that can solve linear problems exactly and are A-stable. This work extends the standard exponential integration framework to derive Nyström-type exponential integrators that integrates the Newtonian equations of motion as a second-order differential equation directly. In particular, we derive second-order and third-order Nyström-type exponential integrators for strongly magnetized particle pushing problems. Numerical experiments show that the Nyström-type exponential integrators exhibit significant improvement in computation speed over the standard exponential integrators.

general physics↗

DOE OSTI2026

Data-driven Mori–Zwanzig modeling of Lagrangian particle dynamics in turbulent flows

The dynamics of Lagrangian particles in turbulence play a crucial role in mixing, transport, and dispersion in complex flows. Their trajectories exhibit highly nontrivial statistical behavior, motivating the development of surrogate models that can reproduce these trajectories without incurring the high computational cost of direct numerical simulations of the full Eulerian field. This task is particularly challenging because reduced-order models typically lack access to the full set of interactions with the underlying turbulent field. Novel data-driven machine learning techniques can be powerful in capturing and reproducing complex statistics of the reduced-order/surrogate dynamics. In this work, we show how one can learn a surrogate dynamical system that is able to evolve a turbulent Lagrangian trajectory in a way that is point-wise accurate for short-time predictions (with respect to Kolmogorov time) and stable and statistically accurate at long times. This approach is based on the Mori–Zwanzig formalism, which prescribes a mathematical decomposition of the full dynamical system into resolved dynamics that depend on the current state and the past history of a reduced set of observables, and the unresolved orthogonal dynamics due to unresolved degrees of freedom of the initial state. We show how by training this reduced order model on a point-wise error metric on short time-prediction, we are able to correctly learn the dynamics of Lagrangian turbulence, such that also the long-time statistical behavior is stably recovered at test time. This opens up a range of applications, for example, for the control of active Lagrangian agents in turbulence.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Particle dynamics in the spatial afterglow of flowing dusty plasmas

Final technical report for project Department of Energy - DE-SC0022242. The overarching hypothesis of this project was that the particle dynamics in the afterglow of dusty plasmas are determined by the interplay of the transient plasma properties and the material properties of dust particles. By combining experiments and modeling in an approach fundamentally different from prior research, this project investigated correlations between material properties and basic dust charging and decharging mechanisms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2003

Design and Preparation of a Particle Dynamics Space Flight Experiment, SHIVA

ABSTRACT This paper describes the flight experiment, supporting ground science, and the design rationale for project SHIVA (Spaceflight Holography Investigation in a Virtual Apparatus). SHIVA is a fundamental study of particle dynamics in fluids in microgravity. Gravity often dominates the equations of motion of a particle in a fluid, so microgravity provides an ideal environment to study the other forces, such as the pressure and viscous drag and especially the Basset history force. We have developed diagnostic recording methods using holography to save all of the particle field optical characteristics, essentially allowing the experiment to be transferred from space back to earth in what we call the "virtual apparatus" for on-earth microgravity experimentation. We can quantify precisely the three-dimensional motion of sets of particles, allowing us to test and apply new analytical solutions developed by members of the team as reported in the 2001 Conference (Banff, Canada). In addition to employing microgravity to augment the fundamental study of these forces, the resulting data will allow us to quantify and understand the ISS environment with great accuracy. This paper shows how we used both experiment and theory to identify and resolve critical issues and produce an optimal the study. We examined the response of particles of specific gravity from 0.1 to 20, with radii from 0.2 to 2mm. to fluid oscillation at frequencies up to 80 Hz with amplitudes up to 200 microns. To observe some of the interesting effects predicted by the new solutions requires the precise location of the position of a particle in three dimensions. To this end we have developed digital holography algorithms that enable particle position location to a small fraction of a pixel in a CCD array. The spaceflight system will record holograms both on film and electronically. The electronic holograms can be downlinked providing real time data, essentially acting like a remote window into the ISS experimental chamber. Ground experiments have provided input to a flight system design that can meet the requirements for a successful experiment on ISS. Moreover the ground experiments have provided a definitive, quantitative observation of the Basset History force over a wide range of conditions. Results of the ground experiments, the flight experiment design, preliminary flight hardware design, and data analysis procedures are reported.

Trolinger, James↗

DOE OSTI2025

Driven probe particle dynamics in a bubble and pattern forming system

We numerically examine the dynamics of a probe particle driven at a constant force through an assembly of particles with competing long-range repulsion and short-range attraction that forms a bubble or stripe state. In the bubble regime, we identify several distinct types of motion, including an elastic or pinned regime where the probe particle remains inside a bubble and drags all other bubbles with it. There is also a plastic bubble phase where the bubble in which the probe particle is trapped is able to move past the adjacent bubbles. At larger drives, there is a breakthrough regime where the probe particle jumps from bubble to bubble and, in some cases, can induce correlated rotations or plastic rearrangements of the particles within the bubbles. At the highest drives, the probe particle moves sufficiently rapidly that the background particles undergo only small distortions. The distinctive dynamic flow states and the transitions between them are accompanied by signatures in the effective drag on the driven particle, jumps in the velocity–force curves, and changes in the time-dependent velocity fluctuations. We map the dynamic phase diagram for this system for varied interaction lengths, bubble sizes, and densities.

36 MATERIALS SCIENCE↗

NASA NTRS1989

Particle dynamics and gamma-ray emission in the magnetospheres of neutron stars with accretion disks

Whether the existence of cold accretion disks around isolated, magnetized neutron stars might result in a distinct observational signature due to the Compton drag interaction between the electrostatically accelerated changes and the thermal radiation emitted by these disks. The particle dynamics resulting from the combined effects of electrostatic acceleration and the Compton drag interaction are determined. In the course of their deceleration, the charged particles boost the thermal disk radiation to gamma-ray energies, which may result in a significant spectral component. Cold disks are too underluminous to significantly retard the flow, and if such disks are present in pulsars, only a small fraction of the particle energy is transferred to the radiation field. The results also indicate that steady, unidirectional particle acceleration is unlikely to be the mechanism operating in gamma-ray burst sources.

Melia, Fulvio↗

DOE OSTI2024

Modeling hyperbranched polymer formation via ATRP using dissipative particle dynamics

Hyperbranched polymers (HBPs) offer distinguishing, advantageous properties that arise from their distinctive complex topology. One of the effective approaches to the synthesis of hyperbranched structures involves the use of a branching initiator (inibramer) that is activated only after incorporation into a polymer chain. There remain, however, challenges in determining and characterizing the structures of the synthesized HBPs. Dissipative particle dynamics (DPD) was used to probe the effects of inibramer concentration, solvent concentration, and inibramer reactivity on the kinetics, molecular weight, and dispersity of HBPs. Additionally, DPD allows for direct observation of branched structures, which was not possible in previously reported Monte Carlo type simulations. It was found that higher inibramer concentrations led to faster monomer consumption while forming more dendritic structures with fewer defects. Additionally, high dispersities characteristic of HBP systems were found to originate from asymmetric propagation rates between inibramer-inibramer and inibramer-monomer reactions.

Biswas, Santidan↗

NASA NTRS1979

Particle dynamics associated with the space environment

A major factor in dust dynamics in a microgravity environment is the absence of settling; hence, Spacelab air will contain larger particles than a comparable laboratory on earth. In addition, the presence of low level acceleration fluctuations (thruster firings, crew motions, etc.) could inhibit dust removal by surface scavenging. Because of the presence of larger particles, aerosol dynamics at larger Reynolds numbers must be considered. An accurate drag coefficient for spherical particles was developed for the higher Reynolds number phenomena. A general graphic correlation for the drag coefficient as a function of Reynolds and Knudsen numbers was developed based on currently available drag data for spheres. The general equations that govern dust dynamics were reviewed.

Sandborn, V. A.↗

NASA NTRS1982

Solid particle dynamic behavior through twisted blade rows

The particle trajectory calculations provide the essential information which is required for predicting the pattern and intensity of turbomachinery erosion. Consequently, the evaluation of the machine performance deterioration due to erosion is extremely sensitive to the accuracy of the flow field and blade geometry representation in the trajectory computational model. A model is presented that is simple and efficient yet versatile and general to be applicable to axial, radial and mixed flow machines, and to inlets, nozzles, return passages and separators. The results of the computations are presented for the particle trajectories through a row of twisted vanes in the inlet flow field. The effect of the particle size on their trajectories, blade impacts, and on their redistribution and separation are discussed.

Hamed, A.↗

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↗