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At least 343 records · Page 19

Real-time tracking and analysis of gas bubble dynamics in laser powder bed fusion using in-situ X-ray characterization and machine learning

Porosity defects remain a significant challenge in the laser powder bed fusion (LPBF) process, adversely affecting the mechanical properties and reliability of additively manufactured components. Here, this study investigates the real-time formation and trajectory of gas bubbles during LPBF of Al6061 alloy using advanced in-situ X-ray characterization and machine learning. The unsupervised Gaussian mixture model and particle tracking algorithm developed are able to precisely track and quantify the properties of gas bubbles and keyhole pores. Our analysis identified five distinct types of gas bubble formation and movement patterns, emphasizing the diverse origins and behaviors of these defects. It enables precise quantification of trajectories, velocities, and morphological changes of gas bubbles, offering a granular view of the subsurface dynamics within the melt pool. Additionally, we explored keyhole-induced pore dynamics, revealing the critical role of keyhole oscillation and collapse for the formation of both large and small gas pores. It defines four different regions of gas bubble movement within the melt pool, providing a clearer understanding of how local fluid dynamics affect pore behavior. The results underscore the importance of integrating in-situ experimental observation and automated machine learning to develop a more robust predictive model for defect formation in LPBF.

In-situ X-ray imaging↗

Impact of Track Structure Effects on Shielding and Dosimetry

Galactic cosmic rays (GCR) consisting of nuclei of all the known elements with kinetic energies extending from tens to millions of MeV pose a significant health hazard to future deep space operations. Even half of the radiation exposures expected in ISS will result from GCR components. The biological actions of these radiations are known to depend on the details of the energy deposition (not just linear energy transfer, LET, but the lateral dispersion of energy deposition about the particle track). Energy deposits in tissues are dominated by the transfer of tens to hundreds of eV to the tissue's atomic electrons. In the case of low LET radiations, the collisions are separated by large dimensions compared to the size of important biomolecular structures. If such events are also separated in time, then the radiation adds little to the background of radicals occurring from ordinary metabolic processes and causes little or no biological injury. Hence, dose rate is a strong determinant of the action of low LET exposures. The GCR exposures are dominated by ions of high charge and energy (HZE) characterized by many collisions with atomic electrons over biomolecular dimensions, resulting in high radical- density events associated with a few isolated ion paths through the cell and minimal dose rate dependence at ordinary exposure levels. The HZE energy deposit declines quickly laterally and merges with the background radical density in the track periphery for which the exact lateral distribution of the energy deposit is the determinant of the biological injury. Although little data exists on human exposures from HZE radiations, limited studies in mice and mammalian cell cultures allow evaluation of the effects of track structure on shield attenuation properties and evaluation of implications for dosimetry. The most complete mammalian cell HZE exposure data sets have been modeled including the C3H10T1/2 survival and transformation data of Yang et al., the V79 survival and mutation data of various groups, and the Harderian gland tumor data of Alpen et al. Model results for the Harderian gland tumor data in comparison with data from Alpen et al. The Harderian target cell initiation cross section compares closely with the transformation cross section found for the C3H10T1/2 cell transformation data of Yang et al. The most notable feature of the cross sections are the multivalued cross sections for a given LET which implies the corresponding relative biological effectiveness (RBE) is dependent not only on the LET but also the ion type. This fact is at variance with the latest ICRP recommended quality factor which is a defined function of only the LET.

Wilson, J. W.↗

Energy gain in a two-gap RF cavity

Velocity of a deeply non-relativistic particle can change during its acceleration inside an RF cavity significantly enough to cause a deviation of the energy gain from a linear model. This paper derives formulae for corrections to the energy gain in a two-gap RF cavity calculated by taking into account this velocity change in the next approximation. Then, the results are compared with direct particle tracking of an HWR cavity used at the PIP2IT test accelerator. The formulae significantly extend the range of parameters where analytical calculations work with a good accuracy. The approach is applied to two aspects of cavity phasing.

43 PARTICLE ACCELERATORS↗

Radiation Shielding Analysis of Linac Extension Area in APS Using FLUKA and PHITS Monte Carlo Radiation Transport Codes

The Linac extension area tunnel can accept 300- to 500-MeV electrons for experiments. Radiations from various normal and accident beam loss scenarios were analyzed with the FLUKA and PHITS Monte Carlo radiation transport codes. In normal beam loss scenarios, the beam was dumped on the horizontal and vertical beam dumps, while the accident scenarios were horizontal and vertical mis-steered beams that can occur due to incorrect beam energy and magnet settings. The extent of beam deviation, which was established using particle tracking studies, was used to define the beam directions in the Monte Carlo transport calculations. Further, a mis-steered condition, where the beam was not intercepted by the dumps, was also analyzed. For the horizontal dump, the PHITS results above the berm were higher for neutrons and somewhat lower for photons, compared to the FLUKA results. Comparison of the secondary particle yields from FLUKA and PHITS from an Al block with dimensions comparable to what was used in the beam dumps showed a 40% higher neutron yield and a 10% lower photon yield. Finally, to ensure compliance with Argonne National Laboratory's shielding policy, the design of the horizontal beam dump was modified, and additional shielding was recommended.

FLUKA↗

A Lagrangian Study of Interfaces at the Edges of Cumulus Clouds

Abstract Interfaces at the edge of an idealized, nonprecipitating, warm cloud are studied using direct numerical simulation (DNS) complemented with a Lagrangian particle tracking routine. Once a shell has formed, four zones can be distinguished: the cloud core, visible shell, invisible shell, and the environment. The union of the visible and invisible regions is the shell commonly referred to in literature. The boundary between the invisible shell and the environment is the turbulent–nonturbulent interface (TNTI), which is typically not considered in cloud studies. Three million particles were seeded homogeneously across the domain and properties were recorded along individual trajectories. The results demonstrate that the traditional cloud boundary (separating cloudy and noncloudy regions using thresholds applied on liquid condensate or updraft velocity) are some distance away from the TNTI. Furthermore, there is no dynamic difference between the traditional liquid-condensate boundary and the region extending to the TNTI. However, particles crossing the TNTI exhibit a sharp jump in enstrophy and a smooth increase in buoyancy. The traditional cloud boundary coincides with the location of minimum buoyancy in the shell. The shell premixes the entraining and detraining air and analysis reveals a highly skewed picture of entrainment and detrainment at the traditional cloud boundary. A preferential entrainment of particles with velocity and specific humidity higher than the mean values in the shell is observed. Large-eddy simulation of a more realistic setup detects an interface with similar properties using the same thresholds as in the DNS, indicating that the DNS results extrapolate beyond their idealized conditions.

54 ENVIRONMENTAL SCIENCES↗

GERMcode: A Stochastic Model for Space Radiation Risk Assessment

A new computer model, the GCR Event-based Risk Model code (GERMcode), was developed to describe biophysical events from high-energy protons and high charge and energy (HZE) particles that have been studied at the NASA Space Radiation Laboratory (NSRL) for the purpose of simulating space radiation biological effects. In the GERMcode, the biophysical description of the passage of HZE particles in tissue and shielding materials is made with a stochastic approach that includes both particle track structure and nuclear interactions. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections. For NSRL applications, the GERMcode evaluates a set of biophysical properties, such as the Poisson distribution of particles or delta-ray hits for a given cellular area and particle dose, the radial dose on tissue, and the frequency distribution of energy deposition in a DNA volume. By utilizing the ProE/Fishbowl ray-tracing analysis, the GERMcode will be used as a bi-directional radiation transport model for future spacecraft shielding analysis in support of Mars mission risk assessments. Recent radiobiological experiments suggest the need for new approaches to risk assessment that include time-dependent biological events due to the signaling times for activation and relaxation of biological processes in cells and tissue. Thus, the tracking of the temporal and spatial distribution of events in tissue is a major goal of the GERMcode in support of the simulation of biological processes important in GCR risk assessments. In order to validate our approach, basic radiobiological responses such as cell survival curves, mutation, chromosomal aberrations, and representative mouse tumor induction curves are implemented into the GERMcode. Extension of these descriptions to other endpoints related to non-targeted effects and biochemical pathway responses will be discussed.

Kim, Myung-Hee Y.↗

Simulation of the RF system with reversed phasing

In this paper we report on the ELEGANT simulation for the Electron Storage Ring (ESR) RF system with reversed phasing using the lattice version of 5.3 at 5 GeV energy. The full beam dynamics results, including energy spread, bunch length and centroid offset as a function of bunch number in the train are presented. Some of the RF system related parameters, required as the input for particle tracking simulations, have been calculated analytically using the RF system related equations. The obtained results has been compared with the results simulated by Tianmu Xin, Michael Blaskiewicz and Gabriele Bassi using C++ and the SPACE codes.

43 PARTICLE ACCELERATORS↗

Composition of heavy cosmic rays from 25 to 180 MeV per atomic mass unit

Relative abundances of elements from neon through zinc in the energy range from 25 to 180 MeV per amu have been determined from particle tracks in polycarbonate detectors exposed on the Apollo 16 mission. The ratios of elemental abundances of Ne + Si and 17 less than Z less than 25 to Fe + Co + Ni are found to be 5.8 plus or minus 1.9 and 2.1 plus or minus 0.7, respectively, in agreement with the results from cellulose triacetate detectors by O'Sullivan et al. (1973). These results imply that the heavy particles observed are predominantly galactic in origin. The availability to investigators of unetched plastic detectors exposed to solar-flare particles on the Apollo 16 mission is noted.

Fleischer, R. L.↗

Development of ML FPGA Filter for Particle Identification and Tracking in Real Time

Real-time data processing is a frontier field in experimental particle physics. Machine Learning methods are widely used and have proven to be very powerful in particle physics. The growing computational power of modern FPGA boards allows us to add more sophisticated algorithms for real time data processing. Many tasks could be solved using modern Machine Learning (ML) algorithms which are naturally suited for FPGA architectures. The FPGA-based machine learning algorithm provides an extremely low, sub-microsecond, latency decision and makes information-rich data sets for event selection. We report work has started to evaluate an FPGA based Machine Learning (ML) algorithm for a real-time particle identification and tracking with Transition Radiation Detector (TRD) and e/m calorimeter. The first target is the GlueX experiment, with a plan to build a TRD based on GEM technology. GlueX trigger latency is 3.3 μs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Reconstruction of cosmic-ray muon events with CUORE

We report the in-situ 3D reconstruction of through-going muons in the CUORE experiment, a cryogenic calorimeter array searching for neutrinoless double beta (0vββ) decay, leveraging the segmentation of the detector. Due to the slow time response of the detector, time-of-flight estimation is not feasible. Therefore, the track reconstruction is performed using a multi-objective optimization algorithm that relies on geometrical information from the detector as a whole. We measure the integral flux of cosmic-ray muons underground at the Laboratori Nazionali del Gran Sasso, and find our value to be in good agreement with other experiments that have performed a similar measurement. To our knowledge, this work represents the first demonstration of 3D particle tracking and reconstruction of through-going muons with per-event angular determination in a millikelvin cryogenic detector array. The analysis performed for this work will be critical for validating the muon-related background in CUPID, a next-generation 0vββ experiment, and for follow-up studies on detector response and on delayed products induced by cosmic-ray muons.

Adams, D. Q. [University of South Carolina]↗

Summary of LET spectra and dose measurements on ten STS missions

A comparison of linear energy transfer (LET) spectra measurements made with plastic nuclear track detectors (PNTD's) from area passive dosimeters (APD's), was made for ten different STS missions under similar shielding. The results show that integral flux, dose rate and equivalent dose rate values follow a general increase with respect to increasing orbital inclination and altitude but that there are large variations from a simple relationship. This is to be expected since it has been shown that Shuttle attitude variations, combined with the anisotropic particle flux at the South Atlantic Anomaly (SAA), can result in differences of a factor of 2 in dose rate inside the Shuttle (Badhwar et al., 1995). Solar cycle and shielding differences also result in variations in radiation dose between STS missions. Spaceflight dosimeters from the STS missions are also being used in the development of a method for increasing LET spectra measurement accuracy by extending LET measurements to particle tracks of ranges 10-80 microns. Refinements in processing and measurement techniques for the flight PNTD's have yielded increased detection efficiencies for the short tracks when LET spectra determined by using the standard and refined methods were intercompared.

Source record↗

Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics

Graph neural networks have been shown to achieve excellent performance for several crucial tasks in particle physics, such as charged particle tracking, jet tagging, and clustering. An important domain for the application of these networks is the FGPA-based first layer of real-time data filtering at the CERN Large Hadron Collider, which has strict latency and resource constraints. We discuss how to design distance-weighted graph networks that can be executed with a latency of less than one μs on an FPGA. To do so, we consider a representative task associated to particle reconstruction and identification in a next-generation calorimeter operating at a particle collider. We use a graph network architecture developed for such purposes, and apply additional simplifications to match the computing constraints of Level-1 trigger systems, including weight quantization. Using the hls4ml library, we convert the compressed models into firmware to be implemented on an FPGA. Performance of the synthesized models is presented both in terms of inference accuracy and resource usage.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Self-Consistent Large-Scale Magnetosphere-Ionosphere Coupling: Computational Aspects and Experiments

Both external and internal phenomena impact the terrestrial magnetosphere. For example, solar wind and particle precipitation effect the distribution of hot plasma in the magnetosphere. Numerous models exist to describe different aspects of magnetosphere characteristics. For example, Tsyganenko has developed a series of models (e.g., [TSYG89]) that describe the magnetic field, and Stern [STER75] and Volland [VOLL73] have developed an analytical model that describes the convection electric field. Over the past several years, NASA colleague Khazanov, working with Fok and others, has developed a large-scale coupled model that tracks particle flow to determine hot ion and electron phase space densities in the magnetosphere. This model utilizes external data such as solar wind densities and velocities and geomagnetic indices (e.g., Kp) to drive computational processes that evaluate magnetic, electric field, and plasma sheet models at any time point. These models are coupled such that energetic ion and electron fluxes are produced, with those fluxes capable of interacting with the electric field model. A diagrammatic representation of the coupled model is shown.

Newman, Timothy S.↗

In-situ Observations of Directed Energy Deposition Additive Manufacturing Using High-Speed X-ray Imaging

In laser-based directed energy deposition (DED) additive manufacturing, interactions among the laser beam, particle flow, and melt pool influence the properties of the solidified final part. Two separate DED systems, one with high powder flow rates to represent industrial-scale DED processing and the other with low powder flow rates for individual particle tracking, were synchronized with the high-speed imaging setup at the Advanced Photon Source in Argonne National Laboratory. In-situ x-ray imaging of the DED process using both systems highlighted the influence of powder flow rates. Increased powder flow rates resulted in less laser absorption into the melt pool, leading to a transition from a keyhole mode to a melt pool without a keyhole but with surface fluctuations due to powder flow. Increased velocities of particles during powder flow resulted in a decrease in particle melting times and a greater propensity for porosity formation. Altogether, better understanding of the interactions that occur during various scales of the DED process will enable flexibility, control, and new materials development in DED-based additive manufacturing.

36 MATERIALS SCIENCE↗

Revising the Role of Cortical Cytoskeleton during Secretion: Actin and Myosin XI Function in Vesicle Tethering

In plants, secretion of cell wall components and membrane proteins plays a fundamental role in growth and development as well as survival in diverse environments. Exocytosis, as the last step of the secretory trafficking pathway, is a highly ordered and precisely controlled process involving tethering, docking, and fusion of vesicles at the plasma membrane (PM) for cargo delivery. Although the exocytic process and machinery are well characterized in yeast and animal models, the molecular players and specific molecular events that underpin late stages of exocytosis in plant cells remain largely unknown. Here, by using the delivery of functional, fluorescent-tagged cellulose synthase (CESA) complexes (CSCs) to the PM as a model system for secretion, as well as single-particle tracking in living cells, we describe a quantitative approach for measuring the frequency of vesicle tethering events. Genetic and pharmacological inhibition of cytoskeletal function, reveal that the initial vesicle tethering step of exocytosis is dependent on actin and myosin XI. In contrast, treatments with the microtubule inhibitor, oryzalin, did not significantly affect vesicle tethering or fusion during CSC exocytosis but caused a minor increase in transient or aborted tethering events. With data from this new quantitative approach and improved spatiotemporal resolution of single particle events during secretion, we generate a revised model for the role of the cortical cytoskeleton in CSC trafficking.

Zhang, Weiwei↗

Ionization detail parameters and cluster dose: a mathematical model for selection of nanodosimetric quantities for use in treatment planning in charged particle radiotherapy

Abstract Objective . To propose a mathematical model for applying ionization detail (ID), the detailed spatial distribution of ionization along a particle track, to proton and ion beam radiotherapy treatment planning (RTP). Approach . Our model provides for selection of preferred ID parameters ( I p ) for RTP, that associate closest to biological effects. Cluster dose is proposed to bridge the large gap between nanoscopic I p and macroscopic RTP. Selection of I p is demonstrated using published cell survival measurements for protons through argon, comparing results for nineteen I p : N k , k = 2, 3, …, 10, the number of ionizations in clusters of k or more per particle, and F k , k = 1, 2, …, 10, the number of clusters of k or more per particle. We then describe application of the model to ID-based RTP and propose a path to clinical translation. Main results . The preferred I p were N 4 and F 5 for aerobic cells, N 5 and F 7 for hypoxic cells. Significant differences were found in cell survival for beams having the same LET or the preferred N k . Conversely, there was no significant difference for F 5 for aerobic cells and F 7 for hypoxic cells, regardless of ion beam atomic number or energy. Further, cells irradiated with the same cluster dose for these I p had the same cell survival. Based on these preliminary results and other compelling results in nanodosimetry, it is reasonable to assert that I p exist that are more closely associated with biological effects than current LET-based approaches and microdosimetric RBE-based models used in particle RTP. However, more biological variables such as cell line and cycle phase, as well as ion beam pulse structure and rate still need investigation. Significance . Our model provides a practical means to select preferred I p from radiobiological data, and to convert I p to the macroscopic cluster dose for particle RTP.

Engineering↗

Fast dynamic aperture optimization with forward-reversal integration

A fast dynamic aperture (DA) optimization method for storage rings has been developed through the use of reversal integration. Even if dynamical systems have an exact reversal symmetry, a numerical forward integration differs from its reversal. For a chaotic trajectory, cumulative round-off errors are scaled, which results in an exponential growth on the difference. The exponential effect is a generic chaos indicator which represents the sensitivity of the chaotic motion to its initial condition. The chaos indicator of the charged particle motion can be obtained by comparing the forward integrations of particle trajectories with corresponding reversals, a.k.a. “backward integrations.” The indicator is observable even through short-term particle tracking simulations. Therefore, adopting it as an objective function could speed up optimization. Finally, the DA of the National Synchrotron Light Source II storage ring, and another test diffraction-limited light source ring, were optimized using this method for the purpose of demonstration.

43 PARTICLE ACCELERATORS↗

Neutron-antineutron oscillation search with MicroBooNE and DUNE

The Deep Underground Neutrino Experiment (DUNE) is an international project aiming at neutrino physics and astrophysics and a search for phenomena predicted by theories beyond the standard model (BSM). The excellent imaging capability of Liquid Argon Time Projection Chamber (LArTPC) technology, particle tracking and identification utilized in the Far Detector, as well as the Far Detector size and underground placement, allow the experiment to achieve high sensitivity to various rare processes. BSM theories predict the existence of baryon number non-conservation effects, in particular when the baryon number changes by 2. Here we discuss the sensitivity of DUNE to neutron-antineutron oscillation. With full event simulation and reconstruction using the LArSoft package, we have investigated the background to potential signal events from atmospheric neutrino interactions and particle misidentification, and utilized machine learning techniques to enhance the discrimination between signal and background. The methodologies being developed for a high-sensitivity search for neutron-antineutron oscillation in DUNE can also be demonstrated with the currently running MicroBooNE LArTPC. We discuss progress on demonstrating the developed techniques with the first-ever search for neutron-antineutron oscillation in a LArTPC using MicroBooNE data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗