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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Sensitivity Study of Dust-Laden Flows in the DLR GBK Facility using the DUST-US3D Framework

The current work is aimed at performing a detailed numerical sensitivity study of dust-laden flow through the DLR GBK facility using the DUST-US3D frame-work. A three-dimensional volumetric grid of the GBK facility with emphasis on a precise reproduction of the dust particle injection process and the transit of particles through the facility has been developed for this work. The sensitivity study on this grid involves varying particle injection parameters such as the diameter distribution probability function, input velocity magnitude, and input velocity direction and accounting for particle-particle collisions. The resulting impact on particle-related statistics such as the dust mass flow rate is studied, and comparisons made to experimental data.

Dusty Flows↗
NASA NTRS1992

Collisional simulations of particles in a narrow planetary ring

A model is used to investigate how particle-particle collisions might modify some consequences of satellite perturbations relevant to short-term features of narrow planetary rings. A Monte Carlo-like simulation ring-model particle velocity alteration allows the simulation of collisions while individual particles are tracked. Periodic features visible in Voyager images are reproduced in a 2D numerical model which incorporates the collisional simulation as well as the perturbations of adjacent satellites. Collisions are noted to wash out periodic features within one collisional relaxation time.

Kolvoord, Robert A.↗
DOE OSTI2026

Collision Tracking in OpenMC: Methods and Applications in Neutron Noise, Neutron Imaging, Time-of-Flight, and Multiplicity Counting

We present the development and application of a collision tracking feature within the OpenMC Monte Carlo particle transport code, designed for diverse applications such as neutron spectroscopy, scatter camera system, neutron noise, and multiplicity counting simulations. This feature enables the tracking of individual particle collisions, with potential applications in nuclear nonproliferation, reactor physics, and nuclear security. Additionally, the feature holds potential for the calibration of neutron detectors, specifically in converting light output into energy deposited within the detectors. The implementation consists of a set of filters—such as reaction type, energy, cell, and material—that constrain the set of collisions that are tracked, extensions to the Python API to enable simple input specification, and support for writing either OpenMC’s native HDF5-based format or the Monte Carlo particle list format. This feature was added to the official OpenMC release in version 0.15.3. In this work, the feature will be applied to showcase scenarios such as time-of-flight simulations, scatter-camera imaging for neutron source localization, neutron-noise analysis to extract integral kinetic parameters such as the prompt decay constant α, and multiplicity counting to estimate the mass of special nuclear materials. Ultimately, this feature aims to expand the application scope of open-source Monte Carlo particle transport codes such as OpenMC.

Monte Carlo code↗
DOE OSTI2025

Coarse Graining Discrete Element Method Information in Particle-in-Cell Length Scales Using a Machine Learning Approach

This report details the development of a machine learning (ML)-driven framework to coarse-grain inter-particle collision dynamics from high-fidelity Discrete Element Method (DEM) simulations to Particle-in-Cell (PIC) scales for gas-solid systems. Traditional PIC models, while computationally efficient, rely on empirical granular stress formulations that fail to capture the full complexity of collision physics, particularly the heterogeneity in particle dynamics. This study adopts a bottom-up approach, integrating insights from DEM simulations to improve the physical fidelity and interpretability of PIC-scale models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

Advanced Multi-Phase Flow CFD Model Development for Solid Rocket Motor Flowfield Analysis

It is known that the simulations of solid rocket motor internal flow field with AL-based propellants require complex multi-phase turbulent flow model. The objective of this study is to develop an advanced particulate multi-phase flow model which includes the effects of particle dynamics, chemical reaction and hot gas flow turbulence. The inclusion of particle agglomeration, particle/gas reaction and mass transfer, particle collision, coalescence and breakup mechanisms in modeling the particle dynamics will allow the proposed model to realistically simulate the flowfield inside a solid rocket motor. The Finite Difference Navier-Stokes numerical code FDNS is used to simulate the steady-state multi-phase particulate flow field for a 3-zone 2-D axisymmetric ASRM model and a 6-zone 3-D ASRM model at launch conditions. The 2-D model includes aft-end cavity and submerged nozzle. The 3-D model represents the whole ASRM geometry, including additional grain port area in the gas cavity and two inhibitors. FDNS is a pressure based finite difference Navier-Stokes flow solver with time-accurate adaptive second-order upwind schemes, standard and extended k-epsilon models with compressibility corrections, multi zone body-fitted formulations, and turbulence particle interaction model. Eulerian/Lagrangian multi-phase solution method is applied for multi-zone mesh. To simulate the chemical reaction, penalty function corrected efficient finite-rate chemistry integration method is used in FDNS. For the AL particle combustion rate, the Hermsen correlation is employed. To simulate the turbulent dispersion of particles, the Gaussian probability distribution with standard deviation equal to (2k/3)(exp 1/2) is used for the random turbulent velocity components. The computational results reveal that the flow field near the juncture of aft-end cavity and the submerged nozzle is very complex. The effects of the turbulent particles affect the flow field significantly and provide better prediction of the ASRM performance. The multi-phase flow analysis using the FDNS code in the present research can be used as a design tool for solid rocket motor applications.

Liaw, Paul↗
DOE OSTI2025

Observation of nuclear modification of energy-energy correlators inside jets in heavy ion collisions

Energy-energy correlators are constructed by averaging the number of charged particle pairs within jets, weighted by the product of their transverse momenta, as a function of the angular separation of the particles within a pair. They are sensitive to a multitude of perturbative and nonperturbative quantum chromodynamics phenomena in high-energy particle collisions. Using lead-lead data recorded with the CMS detector, energy-energy correlators inside high transverse momentum jets are measured in heavy ion collisions for the first time. The data are obtained at a nucleon-nucleon center-of-mass energy of 5.02 TeV and correspond to an integrated luminosity of 1.70 nb −1 . A similar analysis is done for proton-proton collisions at the same center-of-mass energy to establish a reference. The ratio of lead-lead to proton-proton energy-energy correlators reveals significant jet substructure modifications in the quark-gluon plasma. The results are compared to different models that incorporate either color coherence or medium response effects, where the two effects predict similar substructure modifications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Full event interpretation with machine-learning-based particle-flow reconstruction in the CMS detector

The particle-flow (PF) algorithm constructs a global description of each particle collision by producing a comprehensive list of final-state particles, and is central to event reconstruction in the CMS experiment at the CERN LHC. The existing PF implementation relies on physics-motivated heuristics and assumptions that can be replaced by machine-learning (ML) models trained directly on simulated data and naturally suited to modern graphics processing units (GPUs). A state-of-the-art ML-based PF (MLPF) reconstruction algorithm, implemented within the CMS software framework, is presented. The MLPF algorithm performs a learnable full-event reconstruction on GPUs, generalizes across detector conditions and collision energies, and replaces multiple modular reconstruction steps with a single unified model. Physics performance comparable to standard PF reconstruction is achieved in both simulation and data, with improved jet energy resolution and inference time. In simulated top quark-antiquark events under LHC Run-3 (2023-2024) conditions, the jet energy resolution improves by 10-20% for jets with transverse momentum between 30-100 GeV. Inference time is evaluated using simulated multijet events, with a median of $20\,\hbox {ms}$ per event on an Nvidia L4 GPU, compared to approximately $110\,\hbox {ms}$ for the standard CMS PF reconstruction.

Hayrapetyan, Aram [Yerevan Phys. Inst.]↗
NASA NTRSDate not supplied

Sensitivity Study of Dust-Laden Flows in the DLR GBK Facility using the DUST-US3D Framework

An unstructured integrated simulation framework DUST-US3D has been used to study particle-laden flows in the German Aerospace Center (DLR) GBK facility. Air/particle inflow conditions and the overall simulation methodology has been adjusted to ensure consonance with recent experimental work. The resulting particle dynamics are found to be extremely sensitive to the configuration of the particle injection process. However, owing to relatively low particle mass flow rates incorporating 2-way coupling (particles-gas exchange momentum/energy) or particle-particle collisions has no significant impact on predictions. Numerical estimates for particle velocity magnitude are consistently lower than those observed during experiments which could be indicative of particles coalescing into larger, possibly non-spherical aggregates.

Dusty Flows↗
NASA NTRS1991

An assessment of 'shuffle algorithm' collision mechanics for particle simulations

Among the algorithms for collision mechanics used at present, the 'shuffle algorithm' of Baganoff (McDonald and Baganoff, 1988; Baganoff and McDonald, 1990) not only allows efficient vectorization, but also discretizes the possible outcomes of a collision. To assess the applicability of the shuffle algorithm, a simulation was performed of flows in monoatomic gases and the calculated characteristics of shock waves was compared with those obtained using a commonly employed isotropic scattering law. It is shown that, in general, the shuffle algorithm adequately represents the collision mechanics in cases when the goal of calculations are mean profiles of density and temperature.

Feiereisen, William J.↗
DOE OSTI2026

Artificial Intelligence for Event Reconstruction and Higgs Physics at CMS and Future Colliders

This dissertation charts a trajectory in which advances in artificial intelligence (AI) play a central role in pushing the high-energy physics frontier, complementing progress driven by higher collision energies and larger colliders. The discovery potential of the LHC and future colliders relies on accurate reconstruction of increasingly complex particle collision events. In the CMS experiment, this task is performed by the particle-flow (PF) algorithm. This dissertation presents the first implementation of a machine-learning-based particle-flow (MLPF) reconstruction in the CMS detector based on transformer architectures. In simulated top quark--antiquark pair (ttbar) events under LHC Run~3 (2023--2024) conditions, MLPF improves jet energy resolution by 10--20\% compared to standard PF for jets with transverse momentum between 30--100\GeV. Runtime performance is evaluated using simulated multijet events, with a median inference time of 20\unit{ms} per event on an NVIDIA L4 GPU, compa red to approximately 110\unit{ms} for standard PF. The MLPF algorithm is also validated on Run~3 collision data, representing the first data-validated ML-based reconstruction pipeline at any LHC experiment. We then extend MLPF toward future electron--positron colliders and introduce the first full-simulation cross-detector transfer learning workflow for PF reconstruction. The model is pre-trained on simulated events from the Compact Linear Collider detector (CLICdet) and fine-tuned on the CLIC-like detector (CLD) proposed for the Future Circular Collider (FCC). This approach achieves up to a 40\% improvement in jet energy resolution over rule-based reconstruction while reducing the required training dataset size by an order of magnitude, demonstrating the potential of AI to accelerate detector development and optimization. This dissertation also demonstrates how modern AI techniques enhance the sensitivity of LHC physics analyses. A CMS search for highly Lorentz-boosted Higgs bosons decaying to \textrm{W} boson pairs is presented, focusing on the single-lepton final state. A dedicated fine-tuning strategy for \ParT yields an approximately 70\% increase in expected sensitivity relative to the baseline model. The analysis uses proton--proton collision data at a center-of-mass energy of \ensuremath{\sqrt{s}=13\TeV} collected by CMS between 2016 and 2018, corresponding to an integrated luminosity of 138\ensuremath{\ \mathrm{fb}^{-1}}. The expected significance of the search is $1.86\sigma$, with an observed signal strength of $-0.19^{+0.48}_{-0.46}$. Finally, explainable AI techniques are applied to the MLPF and \ParticleNet algorithms using layerwise relevance propagation, showing that both models base their predictions on physically meaningful features consistent with our physics intuition. Together, these results demonstrate how advanced AI methods can enhance reconstruction, analysis sensitivity, and interpretability, shaping the next era of experimental parti cle physics.

Mokhtar, Farouk [UC, San Diego]↗
DOE OSTI2024

Elimination LArTPC Simulation Uncertainty

Liquid Argon Time Projection Chambers (LArTPC) are essential for detecting muons and neutrinos by capturing electrons released during particle collisions, which drift toward wire planes under an electric field and induce currents measured to reconstruct particle paths. However, LArTPCs face challenges from effects such as electron-ion recombination, electron diffusion, and electron attenuation, complicating data simulation. The Short Baseline Neutrino (SNB) detector aims to measure neutrinos before oscillation occurs. To bridge the gap between simulation and actual data, we propose modifying the amplitude and width of signals on the TPC wires, addressing uncertainties by adjusting signal characteristics to better match observed data. A Gaussian fit to current waveforms produces hits with associated charge and width, and by comparing data and simulated values, discrepancies highlight areas where the model fails. Initial results indicate the current modification algorithm may increase divergence between simulation and data, necessitating further refinement. A discovered bug in the WireModMakeHist_plug.cpp file, which incorrectly computed simulation and data ratios, underscores the need for precise algorithm adjustments. Future work involves correcting code errors, fine-tuning the model, and conducting multiple simulation runs to enhance statistical confidence and reduce uncertainties, ultimately aiming for accurate LArTPC operation and reliable neutrino detection.

Mkrtchyan, Ka'ren↗
NASA NTRS1991

Dynamics of low velocity collisions of ice particle, coated with frost

We continued our investigations of low velocity collisions of ice particles for velocities in range 10(exp -3) - 2 cm/s. The work focused on two effects: (1) the sticking forces for ice particles coated with CO2 frost, and (2) the completion of a 2-D pendulum system for glancing collisions. A new computer software was also developed to control and monitor the position of the 2-D pendulum.

Bridges, F.↗
NASA NTRS1995

The coefficient of restitution of ice particles in glancing collisions: Experimental results for unfrosted surfaces

Both Saturn's rings and planetesimal disks are made up of particles in Keplerian orbits. Inelastic collisions between these particles regulate their dynamical evolution and possible aggregation. We present an experiment to simulate glancing collisions in Saturn's rings and in planetesimal disks and thus measure contributions to the energy loss for both normal and tangential velocity components. In this experiment, a spherical iceball mounted on a long-period, two dimensional pendulum is made to impact a flat ice surface in a low-temperature environment. This paper describes the experimental apparatus in detail and presents results for smooth unfrosted surfaces. The energy loss for tangential motion is suprisingly low, indicating that very little friction is present at low impact speeds for relatively smooth ice surfaces and temperatures near 100 K. We have also investigated room-temperature collisions of a rubber ball on a rough surface to understand the energy loss in situations where the tangential friction force is not small. In this analogous case, the energy loss is maximum for impact angles in the range 45 deg-60 deg.

Supulver, Kimberley D.↗
NASA NTRS1992

Optimization of the parameters for a rotating, mixed-phase reactor

The motion of small, monodisperse particles in fluid was studied in a horizontal, cylindrical container rotating about its axis. One instigation for the study was the common requirement for mixed-phase, chemical or biological reactors to maintain particles in suspension for extended periods. A cylindrical, rotating reactor can allow long-term particle suspension without particle collisions and resulting agglomeration. The purpose of this study was to verify parametric effects and optimize the time of particle suspension. The theoretical and experimental results were obtained for inert, constant-diameter particles of nearly neutral buoyancy. The centrifugal buoyancy and gravitation terms were both included in the equations of motion. Laser illumination, photography and computer imaging were used to measure experimental particle concentration.

Cleland, J. G.↗
NASA NTRS2007

Observed Enhancement of Reflectivity and Electric Field in Long-Lived Florida Anvils

A study of two long-lived Florida anvils showed that reflectivity greater than 20 dBZ increased in area, thickness and sometimes magnitude at mid-level well downstream of the convective cores. In these same regions electric fields maintained strengths greater than 10 kV m(sup -1) for many tens of minutes and became quite uniform over tens of kilometers. Millimetric aggregates persisted at 9 to 10 km for extended times and distances. Aggregation of ice particles enhanced by strong electric fields might have contributed to reflectivity growth in the early anvil, but is unlikely to explain observations further out in the anvil. The enhanced reflectivity and existence of small, medium and large ice particles far out into the anvil suggest that an updraft was acting, perhaps in weak convective cells formed by instability generated from the evaporation and melting of falling ice particles. We conclude that charge separation must have occurred in these anvils, perhaps at the melting level but also at higher altitudes, in order to maintain fields greater than 10 kV m(sup -1) at 9 to 10 km for extended periods of time over large distances. We speculate that charge separation occurred as a result of ice-ice particle collisions (without supercooled water being present) via either a noninductive or perhaps even an inductive mechanism, given the observed broad ice particle spectra, the strong pre-existing electric fields and the many tens of minutes available for particle interactions. The observations, particularly in the early anvil, show that the charge structure in these anvils was quite complex.

Dye, James E.↗
NASA NTRS2007

Observed Enhancement of Reflectivity and Electric Field in Long-Lived Florida Anvils

A study of two long-lived Florida anvils showed that reflectivity >20 dBZ increased in area, thickness and sometimes magnitude at mid-level well downstream of the convective cores. In these same regions electric fields maintained strengths >10 kV m1 for many tens of minutes and became quite uniform over tens of kilometers. Millimetric aggregates persisted at 9 to 10 km for extended times and distances. Aggregation of ice particles enhanced by strong electric fields might have contributed to reflectivity growth in the early anvil, but is unlikely to explain observations further out in the anvil. The enhanced reflectivity and existence of small, medium and large ice particles far out into the anvil suggest that an updraft was acting, perhaps in weak convective cells formed by instability generated from the evaporation and melting of falling ice particles. We conclude that charge separation must have occurred in these anvils, perhaps at the melting level but also at higher altitudes, in order to maintain fields >10 kV m 1 at 9 to 10 km for extended periods of time over large distances. We speculate that charge separation occurred as a result of ice-ice particle collisions (without supercooled water being present) via either a non-inductive or perhaps even an inductive mechanism, given the observed broad ice particle spectra, the strong pre-existing electric fields and the many tens of minutes available for particle interactions. The observations, particularly in the early anvil, show that the charge structure in these anvils was quite complex.

Dye, James E.↗