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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Tracking Synthetic Particle Paths Generated in GATE with Multi-Positron Emission Particle Tracking (MPEPT)

Multi-Positron Emission Particle Tracking (MPEPT) is able to reconstruct the position of point-sources in a PET scanner to a high degree of accuracy. Experimental and simulated trajectories of activated point-sources are compared herein to validate the GATE model of our PET scanner, and test MPEPT performance. The trajectory followed by one point-source of activity 370000 Bq is simulated in GATE, and experimentally measured for velocities 0.18, 0.22. and 0.45 cm/s moving along the major axis of the detector bore. The average difference between the prescribed and predicted point-source positions is found to be approximately 0.3 mm. However, the number of Lines of Response (LOR) reported by GATE for the 370000 Bq source is larger than the number of LOR measured in the experiments. Additional testing of the accuracy of MPEPT is provided by the simulation of 20 point-sources of 20 Bq each placed around the surface of a sphere of radius 40 mm and moving radially inward to a radius of 20 mm at a constant velocity of 1 E-6 m/s. Point-source trajectories for the GATE simulation are compared to trajectories reconstructed from the GATE generated LOR using MPEPT. The average difference between prescribed and predicted point-source position is found to be approximately 0.72 mm. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Single‐Particle Tracking for Understanding Polydisperse Nanoparticle Dispersions

Abstract Colloidal dispersions of nanomaterials are often polydisperse in size, significantly complicating their characterization. This is particularly true for materials early in their historical development due to synthetic control, dispersion efficiency, and instability during storage. Because a wide range of system properties and technological applications depend on particle dimensions, it remains an important problem in nanotechnology to identify a method for the routine characterization of polydispersity in nanoparticle samples, especially changes over time. Commonly employed methods such as dynamic light scattering or analytical ultracentrifugation (AUC) accurately estimate only the first moment of the distribution or are not routine. In this work, the use of single‐particle tracking (SPT) to probe size distributions of common nanoparticle dispersions, including polystyrene nanoparticles, single‐walled carbon nanotubes, graphene oxide, chitosan‐tripolyphosphate, acrylate, hexagonal boron nitride, and poly(lactic‐ co ‐glycolic acid), is proposed and explored. The analysis of particle tracks is conducted using a newly developed Bayesian algorithm that is called Maximum A posteriori Nanoparticle Tracking Analysis. By combining SPT and AUC techniques, it is shown that it is possible to independently estimate the mean aspect ratio of anisotropic particles, an important characterization property. It is concluded that SPT provides a facile, rapid analytical method for routine nanomaterials characterization.

Gong, Xun↗
DOE OSTI2016

Monte Carlo N-Particle Tracking of Ultrafine Particle Flow in Bent Micro-Tubes

The problem of large pressure-differential driven laminar convective-diffusive ultrafine aerosol flow through bent micro-tubes is of interest in several contemporary research areas including; release of contents from pressurized containment vessels, aerosol sampling equipment, advanced scientific instruments, gas-phase micro-heat exchangers, and microfluidic devices. In each of these areas, the predominant problem is the determination of the fraction of particles entering the micro-tube that is deposited within the tube and the fraction that is transmitted through. Due to the extensive parameter restrictions of this class of problems, a Lagrangian particle tracking method making use of the coupling of the analytical stream line solutions of Dean and the simplified Langevin equation is quite a useful tool in problem characterization. This method is a direct analog to the Monte Carlo N-Particle method of particle transport extensively used in nuclear physics and engineering. In this work, 10 nm diameter particles with a density of 1 g/cm3 are tracked within micro-tubes with toroidal bends with pressure differentials ranging between 0.2175 and 0.87 atmospheres. The tubes have radii of 25 microns and 50 microns and the radius of curvature is between 1 m and 0.3183 cm. The carrier gas is helium, and temperatures of 298 K and 558 K are considered. Numerical convergence is considered as a function of time step size and of the number of particles per simulation. Particle transmission rates and deposition patterns within the bent micro-tubes are calculated.

Casella, Andrew M.↗
DOE OSTI2015

Particle tracking approach for transport in three-dimensional discrete fracture networks: Particle tracking in 3-D DFNs

The discrete fracture network (DFN) model is a method to mimic discrete pathways for fluid flow through a fractured low-permeable rock mass, and may be combined with particle tracking simulations to address solute transport. However, experience has shown that it is challenging to obtain accurate transport results in three-dimensional DFNs because of the high computational burden and difficulty in constructing a high-quality unstructured computational mesh on simulated fractures. We present a new particle tracking capability, which is adapted to control volume (Voronoi polygons) flow solutions on unstructured grids (Delaunay triangulations) on three-dimensional DFNs. The locally mass-conserving finite-volume approach eliminates mass balance-related problems during particle tracking. The scalar fluxes calculated for each control volume face by the flow solver are used to reconstruct a Darcy velocity at each control volume centroid. The groundwater velocities can then be continuously interpolated to any point in the domain of interest. The control volumes at fracture intersections are split into four pieces, and the velocity is reconstructed independently on each piece, which results in multiple groundwater velocities at the intersection, one for each fracture on each side of the intersection line. This technique enables detailed particle transport representation through a complex DFN structure. Verified for small DFNs, the new simulation capability enables numerical experiments on advective transport in large DFNs to be performed. As a result, we demonstrate this particle transport approach on a DFN model using parameters similar to those of crystalline rock at a proposed geologic repository for spent nuclear fuel in Forsmark, Sweden.

58 GEOSCIENCES↗
DOE OSTI2023

Parallelized domain decomposition for multi-dimensional Lagrangian random walk mass-transfer particle tracking schemes

Lagrangian particle tracking schemes allow a wide range of flow and transport processes to be simulated accurately, but a major challenge is numerically implementing the inter-particle interactions in an efficient manner. This article develops a multi-dimensional, parallelized domain decomposition (DDC) strategy for mass-transfer particle tracking (MTPT) methods in which particles exchange mass dynamically. We show that this can be efficiently parallelized by employing large numbers of CPU cores to accelerate run times. In order to validate the approach and our theoretical predictions we focus our efforts on a well-known benchmark problem with pure diffusion, where analytical solutions in any number of dimensions are well established. In this work, we investigate different procedures for “tiling” the domain in two and three dimensions (2-D and 3-D), as this type of formal DDC construction is currently limited to 1-D. An optimal tiling is prescribed based on physical problem parameters and the number of available CPU cores, as each tiling provides distinct results in both accuracy and run time. We further extend the most efficient technique to 3-D for comparison, leading to an analytical discussion of the effect of dimensionality on strategies for implementing DDC schemes. Increasing computational resources (cores) within the DDC method produces a trade-off between inter-node communication and on-node work. For an optimally subdivided diffusion problem, the 2-D parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to around 2700 cores, reducing a 5 h simulation to 8 s, while the 3-D algorithm maintains appreciable speedup up to 1700 cores.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Analysis and correction of errors in nanoscale particle tracking using the Single-pixel interior filling function (SPIFF) algorithm

Particle tracking, which is an essential tool in many fields of scientific research, uses algorithms that retrieve the centroid of tracked particles with sub-pixel accuracy. However, images in which the particles occupy a small number of pixels on the detector, are in close proximity to other particles or suffer from background noise, show a systematic error in which the particle sub-pixel positions are biased towards the center of the pixel. This “pixel locking” effect greatly reduces particle tracking accuracy. In this report, we demonstrate the severity of these errors by tracking experimental (and simulated) imaging data of optically trapped silver nanoparticles and single fluorescent proteins. We show that errors in interparticle separation, angle and mean square displacement are significantly reduced by applying the corrective Single-Pixel Interior Filling Function (SPIFF) algorithm. Our work demonstrates the potential ubiquity of such errors and the general applicability of SPIFF correction to many experimental fields.

Science & Technology - Other Topics↗
DOE OSTI2016

Application of Gauss's law space-charge limited emission model in iterative particle tracking method

The particle tracking method with a so-called gun iteration for modeling the space charge is discussed in the following paper. We suggest to apply the emission model based on the Gauss's law for the calculation of the space charge limited current density distribution using considered method. Based on the presented emission model we have developed a numerical algorithm for this calculations. This approach allows us to perform accurate and low time consumpting numerical simulations for different vacuum sources with the curved emitting surfaces and also in the presence of additional physical effects such as bipolar flows and backscattered electrons. The results of the simulations of the cylindrical diode and diode with elliptical emitter with the use of axysimmetric coordinates are presented. The high efficiency and accuracy of the suggested approach are confirmed by the obtained results and comparisons with the analytical solutions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

The HEP.TrkX Project: Deep Learning for Particle Tracking

Charged particle reconstruction in dense environments, such as the detectors of the High Luminosity Large Hadron Collider (HL-LHC) is a challenging pattern recognition problem. Traditional tracking algorithms, such as the combinatorial Kalman Filter, have been used with great success in HEP experiments for years. However, these state-of-the-art techniques are inherently sequential and scale quadratically or worse with increased detector occupancy. The HEP.TrkX project is a pilot project with the aim to identify and develop cross-experiment solutions based on machine learning algorithms for track reconstruction. Machine learning algorithms bring a lot of potential to this problem thanks to their capability to model complex non-linear data dependencies, to learn effective representations of high-dimensional data through training, and to parallelize easily on high-throughput architectures such as FPGAs or GPUs. In this paper we present the evolution and performance of our recurrent (LSTM) and convolutional neural networks moving from basic 2D models to more complex models and the challenges of scaling up to realistic dimensionality/sparsity.

Tsaris, Aristeidis↗
DOE OSTI2013

Space Charge Models for Particle Tracking on Long Time Scales

In order to efficiently track charged particles over long times, most tracking codes use either analytic charge distributions or particle-in-cell (PIC) methods based on fast Fourier transforms (FFTs). While useful for theoretical studies, analytic distribution models do not allow accurate simulation of real machines. PIC calculations can utilize realistic space charge distributions, but these methods suffer from the presence of discretization errors. We examine the situation for particle tracking with space charge over long times, and consider possible ideas to improve the accuracy of such calculations.

Holmes, Jeffrey A↗
DOE OSTI2012

Modeling Bimolecular Reactions and Transport in Porous Media Via Particle Tracking

We use a particle-tracking method to simulate several one-dimensional bimolecular reactive transport experiments. In this numerical method, the reactants are represented by particles: advection and dispersion dominate the flow, and molecular diffusion dictates, in large part, the reactions. The particle/particle reactions are determined by a combination of two probabilities dictated by the physics of transport and energetics of reaction. The first is that reactant particles occupy the same volume over a short time interval. The second is the conditional probability that two collocated particles favorably transform into a reaction. The first probability is a direct physical representation of the degree of mixing in an advancing displacement front, and as such lacks empirical parameters except for the user-defined number of particles. This number can be determined analytically from concentration autocovariance, if this type of data is available. The simulations compare favorably to two physical experiments. In one, the concentration of product, 1,2-naphthoquinoe-4-aminobenzene (NQAB) from reaction between 1,2-naphthoquinone-4-sulfonic acid (NQS) and aniline (AN), was measured at the outflow of a column filled with glass beads at different times. In the other, the concentration distribution of reactants (CuSO_4 and EDTA^{4-}) and products (CuEDTA^{4-}) were quantified by snapshots of transmitted light through a column packed with cryloite sand. The thermodynamic rate coefficient in the latter experiment was 10^7 times greater than the former experiment, making it essentially instantaneous. When compared to the solution of the advection-dispersion-reaction equation (ADRE) with the well-mixed reaction coefficient, the experiments and the particle-tracking simulations showed on the order of 20% to 40% less overall product, which is attributed to poor mixing. The poor mixing also leads to higher product concentrations on the edges of the mixing zones, which the particle model simulates more accurately than the ADRE.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Measurements of the Flow in the Vicinity of an Additively Manufactured Turbine Leading-Edge Using X-Ray Particle Tracking Velocimetry

X-ray particle tracking velocimetry (PTV) is performed, for the first time, to measure the velocity field inside a leading-edge of a turbine blade made by laser-additive-manufacturing (LAM) process. The traditional showerhead holes were replaced by a porous matrix in the leading-edge. The flow through such a leading-edge piece cannot be faithfully recreated by traditional prototype testing methods due to the surface roughness and imperfections caused by LAM process. Hence, direct measurement is the only option. However, it is difficult to measure flow inside such pieces with traditional velocimetry measurements due to the existence of metallic walls. Moreover, small internal size and high flow speeds call for a measurement technique with high spatial and temporal resolutions. To address these issues, we performed time-resolved X-ray PTV using the Advanced Photon Source (APS) synchrotron facility at the Argonne National Laboratory (ANL). A hydraulic system was constructed to run water, mixed with seeding particles, through the leading-edge piece. A high-speed camera captured the images of the seeding particles, which were later processed to create particle tracks. The time-averaged velocity field showed distinct pairs of vortices located in front of the porous outlet inside the leading-edge piece. The inlet channel showed reversed flow due to partial obstruction by the porous inlet of the test piece. Such knowledge of the flow field inside a leading-edge of a turbine blade will help us to design better cooling paths leading to higher cooling efficiency and increased life-span of a turbine blade.

42 ENGINEERING↗