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At least 811 records · Page 45

Dependence of Lamellar Eutectic Growth with Convection on Boundary Conditions and Geometric Confinement: A Phase-Field Lattice-Boltzmann Study

Simulating eutectic growth with convection is challenging because of the enormous computing demand resulting from the required domain size compared with the eutectic scale. In this study, a phase-field lattice-Boltzmann approach was employed to reproduce the eutectic growth with convection (both natural and forced). To enable and accelerate large-scale simulations, a parallel-adaptive mesh refinement algorithm was developed to combine with this numerical approach. The effects of the boundary conditions and the geometric confinement on the eutectic growth with convection were systematically investigated in the Al-Cu eutectic alloy. Results showed that both boundary conditions and the geometric confinement altered the eutectic evolution by affecting the distributions of the solute and velocity ahead of the eutectic solid/liquid interface. As the first attempt to explore the two factors on the eutectic growth with convection, our thorough investigation lays a foundation for modeling the coupled convection–solute eutectic evolution.

36 MATERIALS SCIENCE↗

Enhanced betatron X-rays from axially modulated plasma wakefields

In the cavitation regime of plasma-based accelerators, a population of high-energy electrons trailing the driver can undergo betatron motion. The motion results in X-ray emission, but the brilliance and photon energy are limited by the electrons' initial transverse coordinate. To overcome this, we exploit parametrically unstable betatron motion in a cavitated, axially modulated plasma. Theory and simulations are presented showing that the unstable oscillations increase both the total X-ray energy and average photon energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Efficient and generalizable nested Fourier-DeepONet for three-dimensional geological carbon sequestration

Geological carbon sequestration (GCS) involves injecting CO2 into subsurface geological formationsfor permanent storage. Numerical simulations could guide decisions in GCS projects by predictingCO 2 migration pathways and the pressure distribution in storage formation. However, these simula-tions are often computationally expensive due to highly coupled physics and large spatial-temporalsimulation domains. Surrogate modelling with data-driven machine learning has become a promis-ing alternative to accelerate physics-based simulations. Among these, the Fourier neural operator(FNO) has been applied to three-dimensional synthetic subsurface models. Despite its good accuracyin simulating CO 2 plume migration, it requires large computational resources in training and alsolacks generalizability. Here, to further improve performance, we have developed a nested Fourier-DeepONet by combining the expressiveness of the FNO with the modularity of a deep operatornetwork (DeepONet). This new framework is twice as efficient as a nested FNO for training and has atleast 80% lower GPU memory requirement due to its flexibility to treat temporal coordinates sepa-rately. These performance improvements are achieved without compromising prediction accuracy.In addition, the generalization and extrapolation ability of nested Fourier-DeepONet beyond thetraining range has been thoroughly evaluated. Nested Fourier-DeepONet outperformed the nestedFNO for extrapolation in time with more than 50% reduced error. It also exhibited good extrapolationaccuracy beyond the training range in terms of reservoir properties, number of wells, and injectionrate.

Lee, Jonathan E. [Department of Chemical and Envir↗

HybridSystemsSimulations.jl - Solving the Merchant Collocated Facilities with JuMP

The development of new clean-generation technologies also leads to new plant-level architectures that combine several generation and storage assets behind the point of connection. These co-located generation resources (Hybrid Systems) primarily operate as merchant assets that employ automated market bidding models and internal Energy Management Systems (EMS) to comply with the operator's signals. Formulating an optimal bidding model requires embedding the EMS control model into the bidding algorithm, resulting in a bi-level optimization problem. In this presentation, we first showcase using JuMP to formulate and solve this problem effectively for multiple merchant systems and the bidding outcomes considering different model formulations. Second, the bidding outcomes are later integrated into a PowerSimulations.jl (also built with JuMP) simulation to study the system-level effects of the various merchant bidding and the interactions between market-clearing models and the embedded EMS model. We will showcase simulations conducted in the RTS system considering different levels of merchant hybrid systems participation. The presentation provides the following specific insights on JuMP usage: 1) the Formulation of specialized bi-level problems with custom cuts to solve the merchant hybrid system bidding problem; 2) the integration of a modular model within a complex simulation workflow supported by JuMP in PowerSimulations.jl; 3) Accelerating the solution of power systems operations simulation that employ agent optimization problems using JuMP.

energy markets↗

MO-FG-BRA-01: 4D Monte Carlo Simulations for Verification of Dose Delivered to a Moving Anatomy

Purpose: To validate 4D Monte Carlo (MC) simulations of dose delivery by an Elekta Agility linear accelerator to a moving phantom. Methods: Monte Carlo simulations were performed using the 4DdefDOSXYZnrc/EGSnrc user code which samples a new geometry for each incident particle and calculates the dose in a continuously moving anatomy. A Quasar respiratory motion phantom with a lung insert containing a 3 cm diameter tumor was used for dose measurements on an Elekta Agility linac with the phantom in stationary and moving states. Dose to the center of tumor was measured using calibrated EBT3 film and the RADPOS 4D dosimetry system. A VMAT plan covering the tumor was created on the static CT scan of the phantom using Monaco V.5.10.02. A validated BEAMnrc model of our Elekta Agility linac was used for Monte Carlo simulations on stationary and moving anatomies. To compare the planned and delivered doses, linac log files recorded during measurements were used for the simulations. For 4D simulations, deformation vectors that modeled the rigid translation of the lung insert were generated as input to the 4DdefDOSXYZnrc code as well as the phantom motion trace recorded with RADPOS during the measurements. Results: Monte Carlo simulations and film measurements were found to agree within 2mm/2% for 97.7% of points in the film in the static phantom and 95.5% in the moving phantom. Dose values based on film and RADPOS measurements are within 2% of each other and within 2σ of experimental uncertainties with respect to simulations. Conclusion: Our 4D Monte Carlo simulation using the defDOSXYZnrc code accurately calculates dose delivered to a moving anatomy. Future work will focus on more investigation of VMAT delivery on a moving phantom to improve the agreement between simulation and measurements, as well as establishing the accuracy of our method in a deforming anatomy. This work was supported by the Ontario Consortium of Adaptive Interventions in Radiation Oncology (OCAIRO), funded by the Ontario Research Fund Research Excellence program.

60 APPLIED LIFE SCIENCES↗

Mechanistic Insights into Peptide Binding and Deactivation of an Adhesion G Protein-Coupled Receptor

Adhesion G protein-coupled receptors (ADGRGs) play critical roles in the reproductive, neurological, cardiovascular, and endocrine systems. In particular, ADGRG2 plays a significant role in Ewing sarcoma cell proliferation, parathyroid cell function, and male fertility. In 2022, a cryo-EM structure was reported for the active ADGRG2 bound by an optimized peptide agonist IP15 and the Gs protein. The IP15 peptide agonist was also modified to antagonists 4PH-E and 4PH-D with mutations of the 4PH residue to Glu and Asp, respectively. However, experimental structures of inactive antagonist-bound ADGRs remain to be resolved, and the activation mechanism of ADGRs such as ADGRG2 is poorly understood. Here, we applied Gaussian accelerated molecular dynamics (GaMD) simulations to probe conformational dynamics of the agonist- and antagonist-bound ADGRG2. By performing GaMD simulations, we were able to identify important low-energy conformations of ADGRG2 in the active, intermediate, and inactive states, as well as explore the binding conformations of each peptide. Moreover, our simulations revealed critical peptide-receptor residue interactions during the deactivation of ADGRG2. In conclusion, through GaMD simulations, we uncovered mechanistic insights into peptide (agonist and antagonist) binding and deactivation of the ADGRG2. These findings will potentially facilitate rational design of new peptide modulators of ADGRG2 and other ADGRs.

59 BASIC BIOLOGICAL SCIENCES↗

Large Eddy Simulation of a Supercritical Fuel Jet in Cross Flow using GPU-Acceleration

Fuel is routinely injected into combustion chambers at elevated pressures resulting in formation of supercritical fluid flow. The dispersion of fuel and the combustion processes are significantly different in high pressure conditions as the raditional liquid atomization and evaporation are replaced by diffusion-dominated mixing. Modeling supercritical flow is challenging due to the complex thermodynamics and transport properties of the fluids and in most cases high fidelity numerical simulations are prohibitively expensive. However, numerical investigations must incorporate the flow properties appropriate for the regime for accurate description of the physical processes involved. In this paper, we consider real-fluid properties and simulate the turbulent mixing of fuel jet in cross flow at high ambient pressure. In order to make efficient use of the computer resources and reduce the time to solution, without compromising the resolution requirements, the real-fluid property routines are accelerated via Graphics Processing Unit (GPU) computation. The numerical simulations performed at different resolutions suggest that the high fidelity computations with refined mesh are essential to capture the non-linear dynamics of vortex evolution downstream of the fuel jet and signifies the necessity for an accelerated code. The code is accelerated using the Kokkos C++ library and is demonstrated to be about 2 times faster than the non-accelerated version. Considerable computational cost associated with the thermodynamics routines is reduced in the accelerated version. The results also suggest the resource requirements to compute turbulent closures and the need for acceleration of the routines associated with the sub-grid scale closures.

Gottiparthi, Kalyana C.↗

Exploring the Acceleration Mechanisms for Particle Injection and Power-law Formation during Transrelativistic Magnetic Reconnection

Magnetic reconnection in the relativistic and transrelativistic regimes is able to accelerate particles to hard power-law energy spectra f ∝ γ -p (approaching p = 1). The underlying acceleration mechanism that determines the spectral shape is currently a topic of intense investigation. By means of fully kinetic plasma simulations, we carry out a study of particle acceleration during magnetic reconnection in the transrelativistic regime of a proton–electron plasma. While earlier work in this parameter regime has focused on the effects of electric field parallel to the local magnetic field on the particle injection (from thermal energy to the lower-energy bound of the power-law spectrum), here we examine the roles of both parallel and perpendicular electric fields to gain a more complete understanding on the injection process and further development of a power-law spectrum. We show that the parallel electric field does contribute significantly to particle injection, and is more important in the initial phase of magnetic reconnection. However, as the simulation proceeds, the acceleration by the perpendicular electric field becomes more important for particle injection and completely dominates the acceleration responsible for the high-energy power-law spectrum. This holds robustly, in particular for longer reconnection times and larger systems, i.e., in simulations that are more indicative of the processes in astrophysical sources.

79 ASTRONOMY AND ASTROPHYSICS↗

Performance of concrete under accelerated physical salt attack and carbonation

Conventional testing of physical salt attack (PSA) on concrete does not consider concomitant factors that may exist in service and alter the mechanisms and kinetics of PSA. This study adopted a combined testing approach where concrete was concurrently investigated under accelerated PSA and carbonation, simulating elements serving in heavy traffic and industrial zones, while implementing ambient conditions similar to that in geographic locations with previous cases of PSA. Based on the tested mixture design parameters [water-to-binder ratio, cement type, and supplementary cementitious materials], potential performance improvement and risks were identified. Thermal, mineralogical, and microscopy analyses elucidated the co-occurrence of complex degradation processes in concrete subjected to accelerated PSA and carbonation, which were distinctive from that induced by the single-factor PSA exposure. The synoptic results from this study may informatively improve guidance on mixture design of concrete when dual exposure to PSA and carbonation is expected in the field.

36 MATERIALS SCIENCE↗

RECURRENT EXPLOSIVE ERUPTIONS AND THE ''SIGMOID-TO-ARCADE'' TRANSFORMATION IN THE SUN DRIVEN BY DYNAMICAL MAGNETIC FLUX EMERGENCE

We report on three-dimensional MHD simulations of recurrent mini coronal mass ejection (CME)-like eruptions in a small active region (AR), which is formed by the dynamical emergence of a twisted (not kink unstable) flux tube from the solar interior. The eruptions develop as a result of the repeated formation and expulsion of new flux ropes due to continuous emergence and reconnection of sheared field lines along the polarity inversion line of the AR. The acceleration of the eruptions is triggered by tether-cutting reconnection at the current sheet underneath the erupting field. We find that each explosive eruption is followed by reformation of a sigmoidal structure and a subsequent ''sigmoid-to-flare arcade'' transformation in the AR. These results might have implications for recurrent CMEs and eruptive sigmoids/flares observations and theoretical studies.

79 ASTRONOMY AND ASTROPHYSICS↗

A CR-hydro-NEI model of the structure and broadband emission from Tycho's supernova remnant

Tycho's supernova remnant (SNR) is well-established as a source of particle acceleration to very high energies. Constraints from numerous studies indicate that the observed γ-ray emission results primarily from hadronic processes, providing direct evidence of highly relativistic ions that have been accelerated by the SNR. Here we present an investigation of the dynamical and spectral evolution of Tycho's SNR by carrying out hydrodynamical simulations that include diffusive shock acceleration of particles in the amplified magnetic field at the forward shock of the SNR. Our simulations provide a consistent view of the shock positions, the nonthermal emission, the thermal X-ray emission from the forward shock, and the brightness profiles of the radio and X-ray emission. We compare these with the observed properties of Tycho to determine the density of the ambient material, the particle acceleration efficiency and maximum energy, the accelerated electron-to-proton ratio, and the properties of the shocked gas downstream of the expanding SNR shell. We find that evolution of a typical Type Ia supernova in a low ambient density (n {sub 0} ∼ 0.3 cm{sup –3}), with an upstream magnetic field of ∼5 μG, and with ∼16% of the SNR kinetic energy being converted into relativistic electrons and ions through diffusive shock acceleration, reproduces the observed properties of Tycho. Under such a scenario, the bulk of observed γ-ray emission at high energies is produced by π{sup 0}-decay resulting from the collisions of energetic hadrons, while inverse-Compton emission is significant at lower energies, comprising roughly half of the flux between 1 and 10 GeV.

79 ASTRONOMY AND ASTROPHYSICS↗

Plasma electron-hole kinematics: momentum conservation

We analyse the kinematic properties of a plasma electron hole: a non-linear self-sustained localized positive electric potential perturbation, trapping electrons, that behaves as a coherent entity. When a hole accelerates or grows in depth, ion and electron plasma momentum is changed both within the hole and outside it, by an energization process we call jetting. We present a comprehensive analytic calculation of the momentum changes of an isolated general one-dimensional hole. The conservation of the total momentum gives the hole's kinematics, determining its velocity evolution. Our results explain many features of the behavior of hole speed observed in numerical simulations, including self-acceleration at formation, and hole pushing and trapping by ion streams.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simulation of shot noise effects in the EIC strong hadron cooling accelerator using real number of electrons

In the electron ion collider design, in order to achieve the peak luminosity 10 34 /cm 2 /s with a reasonable lifetime, an efficient coherent electron cooling scheme was proposed to reduce the hadron beam emittance growth. Such a cooling scheme requires a good electron beam quality with a small energy spread. However, the shot noise in the electron beam through the accelerator might be amplified due to the microbunching instability and degrades the electron beam quality in the modulator section of the strong hadron cooling channel and correspondingly cooling rate. In this study, we report on self-consistent simulations of these effects using a real number of electrons to capture the details of shot noise and analysis of the shot noise growth through the accelerator.

Qiang, Ji↗

Graph-EAM: An Interpretable and Efficient Graph Neural Network Potential Framework

The development of deep learning interatomic potentials has enabled efficient and accurate computations in quantum chemistry and materials science, circumventing computationally expensive ab initio calculations. However, the huge number of learnable parameters in deep learning models and their complex architectures hinder physical interpretability and affect the robustness of the derived potential. In this work, we propose graph-EAM, a lightweight graph neural network (GNN) inspired by the empirical embedded atom method to model the interatomic potential of single-element structures. Four material systems: platinum, niobium, silicon, and amorphous-carbon, for which quantum simulation data sets are publicly available, are examined to demonstrate that graph-EAM can achieve high energy and force prediction accuracy-comparable or better than existing state-of-the-art machine learning models-with much fewer parameters. It is also shown that the explicit inclusion of the angular information via three-body atomic density increases the prediction accuracy. In conclusion, the accuracy and efficiency of potentials obtained from graph-EAM can help accelerate the molecular dynamics simulation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Collaboration for Advanced Modeling of Particle Accelerators

The pverarching purpose is to accelerate and expand the scope of discoveries from high energy physics (HEP) particle accelerators by enabling the design of accelerators that are significantly more compact and cheaper to build and run. This will be realized through (i) developing high-performance computing (HPC) accelerator and beam modeling capabilities to design the full range of systems required (ii) developing community simulation ecosystems that seamlessly integrate accelerator elements to facilitate the design and control of next-generation accelerators.

43 PARTICLE ACCELERATORS↗

Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e

We introduce a novel Proximal Policy Optimization (PPO) algorithm aimed at addressing the challenge of maintaining a uniform proton beam intensity delivery in the Muon to Electron Conversion Experiment (Mu2e) at Fermi National Accelerator Laboratory (Fermilab). Our primary objective is to regulate the spill process to ensure a consistent intensity profile, with the ultimate goal of creating an automated controller capable of providing real-time feedback and calibration of the Spill Regulation System (SRS) parameters on a millisecond timescale. We treat the Mu2e accelerator system as a Markov Decision Process suitable for Reinforcement Learning (RL), utilizing PPO to reduce bias and enhance training stability. A key innovation in our approach is the integration of a neuralized Proportional-Integral-Derivative (PID) controller into the policy function, resulting in a significant improvement in the Spill Duty Factor (SDF) by 13.6%, surpassing the performance of the current PID controller baseline by an additional 1.6%. This paper presents the preliminary offline results based on a differentiable simulator of the Mu2e accelerator. It paves the groundwork for real-time implementations and applications, representing a crucial step towards automated proton beam intensity control for the Mu2e experiment.

43 PARTICLE ACCELERATORS↗

Temperature Profile of the Solution Vessel of an Accelerator-Driven Subcritical Fissile Solution System

Dynamic System Simulation (DSS) models of fissile solution systems have been developed and verified against a variety of historical configurations. DSS techniques have been applied specifically to subcritical accelerator-driven systems using fissile solution fuels of uranium. Initial DSS models were developed in DESIRE, a specialized simulation scripting language. In order to tailor the DSS models to specifically meet needs of system designers they were converted to a Visual Studio implementation, and one of these subsequently to National Instrument’s LabVIEW for human factors engineering and operator training. Specific operational characteristics of subcritical accelerator-driven systems have been examined using a DSS model tailored to this particular class using fissile fuel.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗