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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 379 records · Page 21

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NASA NTRS1990

Vectorization of a particle code used in the simulation of rarefied hypersonic flow

A limitation of the direct simulation Monte Carlo (DSMC) method is that it does not allow efficient use of vector architectures that predominate in current supercomputers. Consequently, the problems that can be handled are limited to those of one- and two-dimensional flows. This work focuses on a reformulation of the DSMC method with the objective of designing a procedure that is optimized to the vector architectures found on machines such as the Cray-2. In addition, it focuses on finding a better balance between algorithmic complexity and the total number of particles employed in a simulation so that the overall performance of a particle simulation scheme can be greatly improved. Simulations of the flow about a 3D blunt body are performed with 10 to the 7th particles and 4 x 10 to the 5th mesh cells. Good statistics are obtained with time averaging over 800 time steps using 4.5 h of Cray-2 single-processor CPU time.

Baganoff, D.↗

DOE OSTI2020

Erosion Experimentation in Solar Power Systems

An alternate and sustainable form of energy is concentrated solar power (CSP) systems, which capture and store the sun’s energy in the form of heat. To increase the efficiency and overall cost of the plant, particles were used as a heat transfer medium. As particles flow through this system, the movement of particles creates erosion, in the forms of abrasion and attrition. Experiments were tested at room temperature and 800 degrees Celsius for both abrasion wear and attrition erosion. In abrasion wear, specimens were placed inside a container, particles were added, and the specimen rotated in and out of the particles. In attrition erosion, a steel disk rotated amongst particles which resulted in particles rubbing against each other. Abrasion wear increased when temperature increased while attrition showed that the particles broke down as the amount of time increased. For attrition at 800 degrees Celsius, oxide was increased and mixed with the particles. Durability models will be created to predict attrition and abrasion based on the particle and specimen mechanical properties. This discovery shows that this method of utilizing particles for CSP plants would improve efficiency and decrease overall costs.

14 SOLAR ENERGY↗

DOE OSTI2022

Viscoelastic Particle Focusing and Separation in a Spiral Channel

As one type of non-Newtonian fluid, viscoelastic fluids exhibit unique properties that contribute to particle lateral migration in confined microfluidic channels, leading to opportunities for particle manipulation and separation. In this paper, particle focusing in viscoelastic flow is studied in a wide range of polyethylene glycol (PEO) concentrations in aqueous solutions. Polystyrene beads with diameters from 3 to 20 μm are tested, and the variation of particle focusing position is explained by the coeffects of inertial flow, viscoelastic flow, and Dean flow. We showed that particle focusing position can be predicted by analyzing the force balance in the microchannel, and that particle separation resolution can be improved in viscoelastic flows.

42 ENGINEERING↗

DOE OSTI2024

The FLUKA code: Overview and new developments

The FLUKA Monte Carlo Radiation Transport and Interaction code package is widely used to simulate the interaction of particles with matter in a variety of fields, including high energy physics, space radiation, medical applications, radiation protection and shielding assessments, accelerator studies, astrophysical studies and well logging. This paper gives a brief overview of the FLUKA program and describes recent developments, in particular, improvements in the modelling of particle interactions and transport are described in detail. In addition, an overview of selected applications is given.

Ballarini, Francesca↗

DOE OSTI2025

Chemical Imaging of Atmospheric Biomass Burning Particles from North American Wildfires

The effects of biomass burning aerosols (BBA) on radiative forcing and cloud formation depend on chemical composition and the internal structures of individual particles within smoke plumes. To improve our understanding of the chemical and physical properties of BBA emitted at different times of the day and their evolution during atmospheric aging, we conducted a study as a part of the Fire Influence on Regional to Global Environments and Air Quality field campaign. Particle samples were collected onboard a research aircraft from smoke plumes from a wildfire in eastern Oregon during late afternoon and nighttime flights on August 28, 2019. A time-resolved aerosol collector was used to collect samples on substrates for offline spectromicroscopic imaging to investigate the single-particle characteristics of BBA particles. Approximately 20,400 individual particles from 10 selected samples were analyzed using computer-controlled scanning electron microscopy coupled with energy-dispersive X-ray microanalysis, revealing their elemental composition, morphology, and viscosity. Elemental microanalysis indicated that aged potassium is likely found in the form of K 2 SO 4 , KNO 3 , and possible K-organic salts. Further chemical speciation and carbon bonding mapping within individual particles were conducted using synchrotron-based scanning transmission X-ray microscopy (STXM) coupled with near edge X-ray absorption fine structure (NEXAFS) spectroscopy. Real-time, water-soluble light absorption measurements were acquired using a particle-into-liquid sampler instrument coupled to a liquid waveguide capillary cell and total organic analyzer. In the late afternoon samples, 65% of the total particle number population consisted entirely of organic components, compared to 46% in the nighttime particles. These differences were attributed to discrepancies in composition at the time of emission and to the daytime condensation and accumulation of photochemically formed secondary organic material on existing BBA particles, a process that halts at night. Microscopy images indicated that particle viscosity was lower in the nighttime particles (<10 1 Pa·s), likely due to increased relative humidity and a higher contribution from hygroscopic inorganic components. The chemical heterogeneity of individual particles was quantified using STXM-derived mixing state parameters. The nature of carbon bonding within individual particles was inferred from the extent of carbon sp 2 hybridization derived from NEXAFS spectra. Average percentages of sp 2 hybridization range between 40% and 60%, with no noticeable differences between late afternoon and nighttime flights. These findings were compared with the online optical properties of both late afternoon and nighttime smoke plumes, providing valuable insights into the complex relationship between chemical composition and optical properties of BBA particles at different times of the day.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2000

Quantum Interferometry

Recently, several researchers, including yours truly, have been able to demonstrate theoretically that quantum photon entanglement has the potential to also revolutionize the entire field of optical interferometry, by providing many orders of magnitude improvement in interferometer sensitivity. The quantum entangled photon interferometer approach is very general and applies to many types of interferometers. In particular, without nonlocal entanglement, a generic classical interferometer has a statistical-sampling shot-noise limited sensitivity that scales like 1/Sqrt[N], where N is the number of particles (photons, electrons, atoms, neutrons) passing through the interferometer per unit time. However, if carefully prepared quantum correlations are engineered between the particles, then the interferometer sensitivity improves by a factor of Sqrt[N] (square root of N) to scale like 1/N, which is the limit imposed by the Heisenberg Uncertainty Principle. For optical (laser) interferometers operating at milliwatts of optical power, this quantum sensitivity boost corresponds to an eight-order-of-magnitude improvement of signal to noise. Applications are to tests of General Relativity such as ground and orbiting optical interferometers for gravity wave detection, Laser Interferometer Gravity Observatory (LIGO) and the European Laser Interferometer Space Antenna (LISA), respectively.

Dowling, Jonathan P.↗

DOE OSTI2025

The Effect of a Carbon Fiber Layer Between the Cathode and the Current Collector on Battery Cell Performance

Contact resistance between the cathode active material (CAM) and the Al current collector can be reduced by applying carbon coatings to the Al current collector surface. However, this process requires an additional step of carbon layer coating on the current collector, which increases both manufacturing costs and processing time. In the present work, an interlayer of continuous unsized carbon fibers aligned in one direction (CF interlayer), is introduced between the Al current collector and the NMC811 cathode during cathode deposition on the Al current collector. This single-step approach eliminates the need for the additional carbon layer coating on the current collector. Additionally, this approach removes the use of toxic solvents and insulative polymers used for making the carbon coating. The CF interlayer improves the rate capability at higher C-rates. The CF interlayer lowers the contact resistance between the cathode particles and the current collector while improving the activation energy of charge transfer. The peel test showed that the CF interlayer does not affect the adhesion strength of the cathode layer with the current collector.

25 ENERGY STORAGE↗

NASA NTRS1993

Fuzzy logic particle tracking velocimetry

Fuzzy logic has proven to be a simple and robust method for process control. Instead of requiring a complex model of the system, a user defined rule base is used to control the process. In this paper the principles of fuzzy logic control are applied to Particle Tracking Velocimetry (PTV). Two frames of digitally recorded, single exposure particle imagery are used as input. The fuzzy processor uses the local particle displacement information to determine the correct particle tracks. Fuzzy PTV is an improvement over traditional PTV techniques which typically require a sequence (greater than 2) of image frames for accurately tracking particles. The fuzzy processor executes in software on a PC without the use of specialized array or fuzzy logic processors. A pair of sample input images with roughly 300 particle images each, results in more than 200 velocity vectors in under 8 seconds of processing time.

Wernet, Mark P.↗

DOE OSTI2022

A new method of studying the fundamental mechanisms involved in pigment liberation from recycle papers

Deinking flotation is the most efficient and widely used method of removing ink particles from printed papers to improve the recyclability. A prerequisite for successful deinking flotation is detachment of pigments from paper fibers, a subprocess known as liberation. The degree of liberation is usually determined via hyperwashing tests, which are costly and time consuming. Furthermore, they provide no information on the fundamental mechanisms controlling liberation. In the present work, we developed a new method in which ?-potentials of the particles in a pulp are measured and analyzed. If pigments are not liberated from paper fibers, a frequency distribution plot gives a single peak, while two peaks appear when they are liberated. One can readily determine the degrees of liberation from the peak positions and peak heights. In addition, the ?-potential data can be used to construct disjoining pressure isotherms using the DLVO theory that are useful to better understand the fundamental mechanisms involved and the roles of different reagents used to improve pigment liberation.

42 ENGINEERING↗

DOE OSTI2024

Reduced‐Order Probabilistic Emulation of Physics‐Based Ring Current Models: Application to RAM‐SCB Particle Flux

Abstract In this work, we address the computational challenge of large‐scale physics‐based simulation models for the ring current. Reduced computational cost allows for significantly faster than real‐time forecasting, enhancing our ability to predict and respond to dynamic changes in the ring current, valuable for space weather monitoring and mitigation efforts. Additionally, it can also be used for a comprehensive investigation of the system. Thus, we aim to create an emulator for the Ring current‐Atmosphere interactions Model with Self‐Consistent magnetic field (RAM‐SCB) particle flux that not only improves efficiency but also facilitates forecasting with reliable estimates of prediction uncertainties. The probabilistic emulator is built upon the methodology developed by Licata and Mehta (2023), https://doi.org/10.1029/2022sw003345 . A novel discrete sampling is used to identify 30 simulation periods over 20 years of solar and geomagnetic activity. Focusing on a subset of particle flux, we use Principal Component Analysis for dimensionality reduction and Long Short‐Term Memory (LSTM) neural networks to perform dynamic modeling. Hyperparameter space was explored extensively resulting in about 5% median symmetric accuracy across all data sets for one‐step dynamic prediction. Using a hierarchical ensemble of LSTMs, we have developed a reduced‐order probabilistic emulator (ROPE) tailored for time‐series forecasting of particle flux in the ring current. This ROPE offers accurate predictions of omnidirectional flux at a single energy with no pitch angle information, providing robust predictions on the test set with an error score below 11% and calibration scores under 8% with bias under 2% providing a significant speed up as compared to the full RAM‐SCB run.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

STATUS OF THE SECOND INTERACTION REGION DESIGN FOR ELECTRON-ION COLLIDER

Provisions are being made in the Electron Ion Collider (EIC) design for future installation of a second Interaction Region (IR), in addition to the day-one primary IR. The envisioned location for the second IR is the existing experi- mental hall at RHIC IP8. It is designed to work with the same beam energy combinations as the first IR, covering a full range of the center-of-mass energy of ?20 GeV to ?140 GeV. The goal of the second IR is to complement the first IR, and to improve the detection of scattered particles with magnetic rigidities similar to those of the ion beam. To achieve this, the second IR hadron beamline features a secondary focus in the forward ion direction. The design of the second IR is still evolving. This paper reports the current status of its pa- rameters, magnet layout, and beam dynamics and discusses the ongoing improvements being made to ensure its optimal performance.

Gamage, B.↗

DOE OSTI2024

STATUS OF THE SECOND INTERACTION REGION DESIGN FOR ELECTRON-ION COLLIDER

Gamage, B.↗

DOE OSTI2022

Dynamics of particle network in composite battery cathodes

We report that improving composite battery electrodes requires a delicate control of active materials and electrode formulation. The electrochemically active particles fulfill their role as energy exchange reservoirs through interacting with the surrounding conductive network. We formulate a network evolution model to interpret the regulation and equilibration between electrochemical activity and mechanical damage of these particles. Through statistical analysis of thousands of particles using x-ray phase contrast holotomography in a LiNi 0.8 Mn 0.1 Co 0.1 O 2 -based cathode, we found that the local network heterogeneity results in asynchronous activities in the early cycles, and subsequently the particle assemblies move toward a synchronous behavior. Our study pinpoints the chemomechanical behavior of individual particles and enables better designs of the conductive network to optimize the utility of all the particles during operation.

25 ENERGY STORAGE↗

DOE OSTI2023

Improving parameterization of ice microphysical processes in Arctic clouds using a synergistic modeling and observational approach (Final Report)

The primary goals of the project were to: 1) Improve the fundamental quantitative models of ice growth processes using ARM radar observations. 2) Better understand the growth of ice particle populations through vapor deposition, riming, and aggregation in Arctic clouds using a new particle-property microphysical model. 3) Robustly estimate and constrain key unknown model parameters using ARM radar observations combined with the particle-property model to develop an improved parameterization of ice growth processes for traditional bulk parameterizations used in cloud and climate models.

58 GEOSCIENCES↗

DOE OSTI2026

Effects of ZrN Coating and Heat Treatment on U-Mo Dispersion Fuel under Irradiation

The stability of U-Mo fuel particles in Al matrix can be improved using ZrN coating and heat treatment. This study investigated irradiation behaviors of fuel plates containing U-Mo fuel particles fabricated with different conditions including heat treatment and the thickness of ZrN coating. Additionally, different fission densities were applied to each fuel plate to understand how varying fission densities affect its irradiation behaviors. This study showed that more recrystallization of grains and development of high burnup structure (HBS) occurred in irradiated fuel particles with higher fission densities. Heat treatment reduced the accumulation of fission gas bubbles in the fuel particles by coarsening their grains. The fuel particles with a ZrN coating thickness of 1.2-1.8 µm showed less significant development of U-Mo/Al interaction layers than the particles with a coating thickness of 0.5 µm after irradiation. This might indicate the existence of a critical thickness of ZrN coating to minimize the formation of the interaction layers. Fission gas bubbles were observed at grain boundaries of irradiated U-Mo fuel particles at low fission densities, and the formation of dendritic features with a darker contrast was identified in backscattered electron images. These features stemmed from grain boundaries with fission gas bubbles or HBS, and some of them contained the bubbles, indicating that they might represent an early stage of HBS propagation in the fuel particles.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Improving neutrino energy estimation of charged-current interaction events with recurrent neural networks in MicroBooNE

We present a deep learning-based method for estimating the neutrino energy of charged-current neutrino-argon interactions. We employ a recurrent neural network (RNN) architecture for neutrino energy estimation in the MicroBooNE experiment, utilizing liquid argon time projection chamber (LArTPC) detector technology. Traditional energy estimation approaches in LArTPCs, which largely rely on reconstructing and summing visible energies, often experience sizable biases and resolution smearing because of the complex nature of neutrino interactions and the detector response. The estimation of neutrino energy can be improved after considering the kinematics information of reconstructed final-state particles. Utilizing kinematic information of reconstructed particles, the deep learning-based approach shows improved resolution and reduced bias for the muon neutrino Monte Carlo simulation sample compared to the traditional approach. In order to address the common concern about the effectiveness of this method on experimental data, the RNN-based energy estimator is further examined and validated with dedicated data-simulation consistency tests using MicroBooNE data. We also assess its potential impact on a neutrino oscillation study after accounting for all statistical and systematic uncertainties and show that it enhances physics sensitivity. This method has good potential to improve the performance of other physics analyses. Published by the American Physical Society 2024

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Deep Learning for Pion Identification and Energy Calibration with the ATLAS Detector

Separating charged and neutral pions as well as calibrating the pion energy response is a core component of reconstruction in the ATLAS calorimeter. This note presents an investigation of deep learning techniques for these tasks, representing the signal in the ATLAS calorimeter layers as pixelated images. Deep learning approaches outperform the classification applied in the baseline local hadronic calibration and are able to improve the energy resolution for a wide range in particle momenta, especially for low energy pions. This work demonstrates the potential of deep-learning-based low-level hadronic calibrations to significantly improve the quality of particle reconstruction in the ATLAS calorimeter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Moment preserving constrained resampling with applications to particle-in-cell methods

The Moment Preserving Constrained Resampling (MPCR) algorithm for particle resampling is introduced and applied to particle-in-cell (PIC) methods to increase simulation accuracy, reduce compute cost, and/or avoid numerical instabilities. The general algorithm partitions the system space into smaller subsets and resamples the distribution within each subset. Further, the algorithm is designed to conserve any number of particle and grid moments with a high degree of accuracy (i.e. machine accuracy). The effectiveness of MPCR is demonstrated with several numerical tests, including a use-case study in gyrokinetic fusion plasma simulations. Finally, the computational cost of MPCR is negligible compared to the cost of particle evolution in PIC methods, and the tests demonstrate that periodic particle resampling yields a significant improvement in the accuracy and stability of the results.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗