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At least 703 records · Page 39

Transformation of Spinors in Accelerators and Beam Transfer Lines

The stable spin direction and the spin tune are two important concepts used when polarized beams are transferred along beam lines or circulating in an accelerator. One of the methods to calculate the stable spin direction and the spin tune of the reference particle of a polarized beam bunch is by integrating simultaneously the Lorentz Force $\vec{F}$ = q($\vec{E}$ +$\vec{v}$ x $\vec{B}$) and the BMT equation of the reference particle as it is transported by the magnets of a beam line or accelerator. A modified version of the Raytrace code was used to integrate the Lorentz equation and the BMT equation. Using the spin motion which is governed by the BMT equation one can compute both, the stable spin direction of the reference particle at any point along the reference orbit of an accelerator or a beam line, and the spin tune of the closed orbit in an accelerator. The simultaneous integration of the Lorentz force and of the BMT equation is the most accurate method to calculate the trajectory and the spin motion of a charged particle moving in an electromagnetic field, however this method requires the accurate description of the electromagnetic fields of the elements in which the charged particles are moving. An alternative method of calculating the stable spin direction and the spin tune of spin ½ charged particles along the reference trajectory of a beam line or an accelerator is the transformation of the spinor which is the wavefunction of spin ½ particles. This method requires the knowledge of the stable spin direction of each element of the beam line or the accelerator. This technical note describes the “spinor-method” to calculate the stable-spin- direction and the spin-tune of a spin ½ particle moving along the reference trajectory of a beam line or an accelerator.

43 PARTICLE ACCELERATORS↗

Role of quadrupole deformation and continuum effects in the “island of inversion” nuclei 28,29,31 F

The peculiar properties of nuclei in the so-called “island of inversion” around Z = 10 and N = 20 are the focus of current nuclear physics research. Recent studies showed that 28 F has a negative-parity ground state and thus lies within the southern shore of the island of inversion, and 29 F presents a halo structure in its ground state, but it is unclear which effects, such as deformation, shell evolution due to tensor forces, or couplings to the continuum, lead to this situation. Here, we investigate the role of quadrupole deformation and continuum effects on the single-particle structure of 28,29,31 F from a relativistic mean-field approach and show how both phenomena can lead to a negative-parity ground state in 28 F and halo structures in 29,31 F. We solve the Dirac equation in the complex-momentum (Berggren) representation for a potential with quadrupole deformation at the first order obtained from relativistic mean-field calculations using the NL3 interaction and calculate the continuum level densities using the Green’s function method. We extract single-particle energies and widths from the continuum level densities to construct the Nilsson diagrams of 28,29,31 F in the continuum and analyze the evolution of both the widths and occupation probabilities of relevant Nilsson orbitals in 28 F and find that some amount of prolate deformation must be present. In addition, we calculate the density distributions for bound Nilsson orbitals near the Fermi surface in 29,31 F and reveal that, for a quadrupole deformation 0.3 ≤ β 2 ≤ 0.45 (prolate), characteristic halo tails appear at large distances. Using the relativistic mean-field approach in the complex-momentum representation with the Green’s function method, we demonstrate that in neutron-rich fluorine isotopes, while in the spherical case the pf shells are already inverted and close to the neutron emission threshold, a small amount of quadrupole deformation can dramatically reduce the gap between positive- and negative-parity states and increase the role of continuum states, ultimately leading to the negative parity in the ground state of 28 F and the halo structures in 29,31 F.

20 ≤ A ≤ 38↗

An Overview of Neutron Irradiated SiC Layer Behavior using Micro-and Nano-Characterization Techniques

The complexity of fission product distribution and composition within the SiC layer of tristructural isotropic (TRISO) coated particles, irradiation effects on the SiC structure as well as the variable nature of metallic fission product release, has led to the exploration of multiple micro- and nano-characterization techniques. The fine scale of the fission product precipitates necessitates unique learnings and application of electron microscopic techniques with irradiated fuel during the Advanced Gas Reactor (AGR)-1 experiment analysis. A summarized discussion on the specific advanced techniques with associated method development for TRISO coated particles is provided followed by the down selected techniques currently considered to provide the highest impact. Techniques considered are electron probe micro-analyzer (EPMA), scanning transmission electron microscopy (STEM), and Precession electron diffraction (PED). SiC grain boundary characteristics are evaluated due to the mobility of specific fission products through grain boundaries. PED was performed for understanding the role of grain boundary character on fission product transport. One set of comparative analyses between AGR-1 and AGR-2 particles leads to a finding that the AGR-1, high-Ag-retention particle, had statistically more coincidence site lattice (CSL)-related grain boundaries (but fewer low-angle grain boundaries), compared to the AGR-2 particle. This implies that CSL-related grain boundaries may have a direct influence on Ag retention. However, precipitates were found on a relatively small fraction of CSL-related grain boundaries in both particles. In another set of comparison between AGR-1 and AGR-2 particles that were subjected to safety testing, there is significant differences in average SiC grain boundary distributions, but the fission product distributions on these grain boundaries are very similar.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Micro- and Nano-techniques for the Study of Fission Product Precipitation in SiC Layer

The complexity of fission product distribution and composition within the SiC layer of tristructural isotropic (TRISO) coated particles, irradiation effects on the SiC structure as well as the variable nature of metallic fission product release, has led to the exploration of multiple micro- and nano-characterization techniques. The fine scale of the fission product precipitates necessitates unique learnings and application of electron microscopic techniques with irradiated fuel during the Advanced Gas Reactor (AGR)-1 experiment analysis. A summarized discussion on the specific advanced techniques with associated method development for TRISO coated particles is provided followed by the down selected techniques currently considered to provide the highest impact. Techniques considered are electron probe micro-analyzer (EPMA), scanning transmission electron microscopy (STEM), and Precession electron diffraction (PED). SiC grain boundary characteristics are evaluated due to the mobility of specific fission products through grain boundaries. PED was performed for understanding the role of grain boundary character on fission product transport. One set of comparative analyses between AGR-1 and AGR-2 particles leads to a finding that the AGR-1, high-Ag-retention particle, had statistically more coincidence site lattice (CSL)-related grain boundaries (but fewer low-angle grain boundaries), compared to the AGR-2 particle. This implies that CSL-related grain boundaries may have a direct influence on Ag retention. However, precipitates were found on a relatively small fraction of CSL-related grain boundaries in both particles. In another set of comparison between AGR-1 and AGR-2 particles that were subjected to safety testing, there is significant differences in average SiC grain boundary distributions, but the fission product distributions on these grain boundaries are very similar.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Internal-Gelation Production of Uranium Oxide Sol-Gel Particles for Forensic Applications

The purpose of this project was to develop and demonstrate a novel method for the production of uranium oxide microsphere particles with tunable chemical compositions via a sol-gel process using a 3D-printer setup. These particles can serve several purposes in research and development as a forensic training tool or as standard reference materials. A key component of the project was to demonstrate the ability to control physical and chemical parameters of the particles created. First, we demonstrated the ability to employ an internal gelation sol-gel process to create individual uranium oxide particles. The particles were successfully dispensed using a unique 3D-printing setup onto a substrate to react and then were collected and thermally processed. A series of temperatures for the annealing process was tested on individual samples to investigate the effect on the sol-gel chemical composition and physical integrity. Next, we demonstrated the ability to control matrix composition of the particles by separately incorporating fission product isotopes as well as Np-237 into the sol-gel solution. It was shown by gamma-ray spectroscopy that these matrix elements were successfully retained during the gelation process. We studied the retention of the elements across a series of annealing temperatures. Additionally, we demonstrated the ability to quantitatively control the isotopic composition of the particles by altering the U-237/U-238 ratio to a controlled value. Finally, X-ray diffraction analysis (XRD) was used to investigate the oxidation state of the sol-gel after annealing at different temperatures.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

Learning protocols for the fast and efficient control of active matter

Exact analytic calculation shows that optimal control protocols for passive molecular systems often involve rapid variations and discontinuities. However, similar analytic baselines are not generally available for active-matter systems, because it is more difficult to treat active systems exactly. Here we use machine learning to derive efficient control protocols for active-matter systems, and find that they are characterized by sharp features similar to those seen in passive systems. We show that it is possible to learn protocols that effect fast and efficient state-to-state transformations in simulation models of active particles by encoding the protocol in the form of a neural network. We use evolutionary methods to identify protocols that take active particles from one steady state to another, as quickly as possible or with as little energy expended as possible. Our results show that protocols identified by a flexible neural-network ansatz, which allows the optimization of multiple control parameters and the emergence of sharp features, are more efficient than protocols derived recently by constrained analytical methods. Our learning scheme is straightforward to use in experiment, suggesting a way of designing protocols for the efficient manipulation of active matter in the laboratory.

74 ATOMIC AND MOLECULAR PHYSICS↗

Signatures and detection prospects for sub-GeV dark matter with superfluid helium

We explore the possibility of using superfluid helium for direct detection of sub-GeV dark matter (DM). We discuss the relevant phenomenology resulting from the scattering of an incident dark matter particle on a Helium nucleus. Rather than directly exciting quasi-particles, DM in this mass range will interact with a single He atom, triggering an atomic cascade which eventually also includes emission and thermalization of quasi-particles. We present in detail the analytical framework needed for modeling these processes and determining the resulting flux of quasi-particles. We propose a novel method for detecting this flux with modern force-sensitive devices, such as nanoelectro-mechanical system (NEMS) oscillators, and derive the sensitivity projections for a generic sub-GeV DM detection experiment using such sensors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Three-dimensional phase field sintering simulations accounting for the rigid-body motion of individual grains

Sintering is a widely used powder processing technique in industrial applications. During sintering, atoms migrate to decrease the energy of the system via two main mechanisms: coarsening and densification, both of which lead to significant morphological variation of the sintered microstructure. When simulating sintering dynamics, the phase-field method has been broadly utilized because of its convenience in tracking morphology evolution. When a large number of grains is involved, it is common to use the same order parameter to describe multiple grains that are not in direct contact with one another (in order to reduce the computational memory demands). However, with this treatment it is difficult to handle the rigid-body motion of individual grains during densification. In this work, an implementation scheme is introduced to overcome the challenge of calculating individual particle motion based on existing equations. It uses a grouping algorithm and sets a cutoff radius on each grain for calculating the particle velocity during densification. This method allows for the incorporation of the densification mechanism, which has been commonly ignored in previous work, into phase-field sintering models in three-dimensional simulations with a large number of particles/grains. Moreover, through combination with the smoothed boundary method, material properties of sintered microstructures, such as the effective diffusivity and Young’s modulus, can be calculated during the sintering processes.

36 MATERIALS SCIENCE↗

Determination of Seven Organic Impurities in FD&C Yellow No. 6 by Ultra-High-Performance Liquid Chromatography

The U.S. Food and Drug Administration (FDA) batch certifies FD&C Yellow No. 6 (Y6) to ensure that the color additive meets requirements published in the Code of Federal Regulations (CFR), including specifications for seven organic manufacturing impurities consisting of two intermediates, a reaction by-product, an impurity originating from an intermediate, and three subsidiary colors. An ultra-high-performance liquid chromatography (UHPLC) method was developed and validated for determining seven organic impurities in Y6. For comparison, the currently used high-performance liquid chromatography (HPLC) method was also validated. The new UHPLC method uses a 1.7 µm particle size biphenyl column with aqueous ammonium formate and methanol as eluants. Analytes are identified by comparing their retention times and UV-visible spectra to those of reference standards. Calibration is performed in the presence of the dye matrix and analyte levels are determined from their peak areas. UHPLC and HPLC validation studies obtained linear calibration curves and excellent values for limits of detection, limits of quantitation, recovery, repeatability, and intermediate precision for all analytes. Survey analyses of 30 samples using the UHPLC and HPLC methods yielded results that were consistent within experimental error; however, the UHPLC method provided more accurate results for two analytes that coelute using the HPLC method. The UHPLC method satisfies the accuracy and precision requisites for routine certification of Y6. The UHPLC method is faster and generates less waste than the HPLC method while delivering better sensitivity, separation, and accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DUAL-PARTICLE DOSEMETER BASED ON ORGANIC SCINTILLATOR

Abstract Traditionally available handheld dosemeters are generally sensitive to only one type of radiation: neutrons or photons. Some dosemeters also rely on very specific attenuation correlations between response and dose, are not scalable in size and multiple dosemeters are required to characterise mixed-particle fields. The research presented here serves as a proof-of-concept for a method to simultaneously measure dose rates from neutrons and photons using a particle discriminating organic scintillation detector without the need for spectral deconvolution. The method was compared with traditional instruments and to simulation. Isotopic photon dose rates measured with this method were within 4% of simulated truth, whereas fission spectrum neutron dose rates were measured within 21%. Measurements of dose rates from both particles agree with simulated truth better than traditional instruments. This new method allows for measurement of dose equivalent from both neutrons and photons with a single instrument and no reliance on spectral deconvolution.

Miller, C. A.↗

Verification of an improved equation-free projective integration method for neoclassical plasma-profile evolution in tokamak geometry

A brute-force, long-time gyrokinetic simulation of plasma profile evolution in magnetic fusion devices is not desirable due to large computational resource requirements and a possible accumulation of numerical error. The equation-free projective integration method of Keverekidis et al. [Commun. Math. Sci. 1(4), 715–762 (2003)] is one of the outstanding candidates in projecting micro-scale simulations to a longer timescale. However, its application to tokamak plasma has not been fruitful due to the appearance of spurious transient oscillations in the lifting process, which are present when the kinetic simulations are initialized with a simplified model distribution function and which make the kinetic simulations to deviate from the desired paths. In this work, a kinetically informed lifting algorithm is added to the equation-free projective integration method, which is then verified in the electrostatic gyrokinetic particle-in-cell code XGCa [R. Hager and C. S. Chang, Phys. Plasmas 23, 042503 (2016)] for a neoclassical ion heat transport problem with adiabatic electrons. This new lifting operator is demonstrated to control spurious transients, enabling an over four-times reduction in the overall computing time in the time-evolution of the ion temperature profile in an axisymmetric toroidal plasma. Further reduction in the computing time is found to be limited due to the stability properties of the linear least squares projective integrator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Calorimetry with deep learning: particle simulation and reconstruction for collider physics

Using detailed simulations of calorimeter showers as training data, we investigate the use of deep learning algorithms for the simulation and reconstruction of single isolated particles produced in high-energy physics collisions. We train neural networks on single-particle shower data at the calorimeter-cell level, and show significant improvements for simulation and reconstruction when using these networks compared to methods which rely on currently-used state-of-the-art algorithms. We define two models: an end-to-end reconstruction network which performs simultaneous particle identification and energy regression of particles when given calorimeter shower data, and a generative network which can provide reasonable modeling of calorimeter showers for different particle types at specified angles and energies. We investigate the optimization of our models with hyperparameter scans. Furthermore, we demonstrate the applicability of the reconstruction model to shower inputs from other detector geometries, specifically ATLAS-like and CMS-like geometries. These networks can serve as fast and computationally light methods for particle shower simulation and reconstruction for current and future experiments at particle colliders.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Understanding Aitken Mode Aerosol Variability over the Southern Ocean and Antarctica: Insights from Cloud Condensation Nuclei Data

Aitken mode aerosol particles play an important role influencing cloud properties and sustenance, acting as a reservoir of potential cloud condensation nuclei against precipitation scavenging. However, there is limited data on Aitken mode aerosols. In this study, we develop a method to estimate Aitken mode aerosol concentrations and size distribution using cloud condensation nuclei measurements (CCN) and κ-Köhler theory. The performance of this method is evaluated using scanning mobility particle sizer (SMPS) data from recent field campaigns to demonstrate its skills and applicability. The method reasonably estimates Aitken- and accumulation-mode aerosol concentrations, achieving correlations of 0.7–0.9 with only modest biases (mean fractional bias within ±23% for Aitken mode and ±34% for accumulation-mode). This method is further applied to measurements collected over the Southern Ocean and Antarctica in recent years from multiple platforms, including ground sites, aircraft, and ships, to derive Aitken and accumulation-mode aerosol concentrations. Using the derived data, we examine the seasonal cycle, latitudinal variations, and vertical distribution of aerosols. Aitken mode aerosol concentrations are elevated over the Southern Ocean and Antarctica during the austral summer similar to the accumulation mode. In the austral summer, the free troposphere has more Aitken mode aerosols and fewer accumulation mode aerosols than the boundary layer, and thus likely serves as an important source of cloud-forming aerosol while also diluting the accumulation mode.

Kang, Litai [University of Washington] (ORCID:0000↗

Online Parameter Estimation Methods for Adaptive Cruise Control Systems

Modeling Adaptive Cruise Control (ACC) vehicles enables the understanding of the impact of these vehicles on traffic flow. In this work, two online methods are used to provide real time system identification of ACC enabled vehicles. The first technique is a recursive least squares (RLS) approach, while the second method solves a nonlinear joint state and parameter estimation problem via particle filtering (PF). We provide a parameter identifiability analysis for both methods to analytically show that the model parameters are not identifiable using equilibrium driving. The accuracy and computational runtime of the online methods are compared to a commonly used offline simulation-based optimization (i.e., batch optimization) approach. The methods are tested on synthetic data as well as on empirical data collected directly from a 2019 model year ACC vehicle using data from sensors that are part of the stock ACC system. The online methods are scalable and provide comparable accuracy to the batch method. RLS runs in real time and is two orders of magnitude faster than the batch method for modest sized (e.g., 15 min) datasets. The particle filter also runs in real- time, and is also suitable in streaming applications in which the datasets can grow arbitrarily large.

33 ADVANCED PROPULSION SYSTEMS↗

Preliminary study of auto-differentiation algorithm in beam dynamics with stochastic process

Modern particle accelerator optimization requires sophisticated computational methods to address the inherently stochastic nature of beam dynamics. This research develops a framework applying AD to SDEs that specifically addresses beam dynamics challenges in particle accelerators, focusing on accurately modeling and optimizing beam behavior in regimes dominated by stochastic processes. By incorporating key physical phenomena such as synchrotron radiation, wakefield effects, and quantum excitation, the framework aims to provide auto differentiation on the figure of merit of the phase space evolution and beam dynamics. The methodology will enable effective optimization method in a dynamic system with stochastic process.

Accelerator Physics↗

A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design

We present a benchmarking study of active learning (AL) schemes for designing planar multilayer nanophotonic metamaterials, where the design tasks are formulated as binary optimization problems. Different surrogate models, including factorization machine (FM), Gaussian process regression (GPR), and convolutional neural network (CNN), combined with different optimization methods, including exhaustive enumeration, discrete particle swarm optimization (DPSO), quantum annealing (QA), hybrid QA, and simulated annealing are studied. The benchmark cases investigated range from small problems with short binary lengths (N = 25) to large problems with N up to 100, focusing on the design of two classes of photonic structures, including antireflective coatings for the long-wavelength infrared region and transparent radiative coolers. For small problems, CNN coupled with DPSO in AL achieves the best performance. As N increases, FM with QA outperforms GPR and CNN. For FM-based AL, hybrid QA yields the best optimization results, particularly in high-dimensional cases (N = 100). These results demonstrate that the optimization method can significantly affect in AL performance as N increases, and that QA-based optimization can provide practical routes for mitigating the optimization bottleneck in high-dimensional problems.

Jung, Serang [Kyung Hee University, Korea]↗

Geometric electrostatic particle-in-cell algorithm on unstructured meshes

We present a geometric particle-in-cell (PIC) algorithm on unstructured meshes for studying electrostatic perturbations with frequency lower than electron gyrofrequency in magnetized plasmas. In this method, ions are treated as fully kinetic particles and electrons are described by the adiabatic response. The PIC method is derived from a discrete variational principle on unstructured meshes. To preserve the geometric structure of the system, the discrete variational principle requires that the electric field is interpolated using Whitney 1-forms, the charge is deposited using Whitney 0-forms and the electric field is computed by discrete exterior calculus. The algorithm has been applied to study the ion Bernstein wave (IBW) in two-dimensional magnetized plasmas. The simulated dispersion relations of the IBW in a rectangular region agree well with theoretical results. In a two-dimensional circular region with fixed boundary condition, the spectrum and eigenmode structures of the IBW are obtained from simulations. We compare the energy conservation property of the geometric PIC algorithm derived from the discrete variational principle with that of previous PIC methods on unstructured meshes. The comparison shows that the new PIC algorithm significantly improves the energy conservation property.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗