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At least 955 records · Page 53

Deployment and validation of predictive 6-dimensional beam diagnostics through generative reconstruction with standard accelerator elements

Understanding the 6-dimensional phase space distribution of particle beams is essential for optimizing accelerator performance. Conventional diagnostics such as use of transverse deflecting cavities offer detailed characterization but require dedicated hardware and space. Generative phase space reconstruction (GPSR) methods have shown promise in beam diagnostics, yet prior implementations still rely on such components. Here we present the first experimental implementation and validation of the GPSR methodology, realized by the use of standard accelerator elements including accelerating cavities and dipole magnets, to achieve complete 6-dimensional phase space reconstruction. Through simulations and experiments at the Pohang Accelerator Laboratory X-ray Free Electron Laser facility, we successfully reconstruct complex, nonlinear beam structures. Furthermore, we validate the methodology by predicting independent downstream measurements excluded from training, revealing the reconstruction closely resembling ground truth. This advancement establishes a pathway for predictive diagnostics across beamline segments while reducing hardware requirements and expanding applicability to various accelerator facilities.

Kim, Seongyeol [Pohang Univ. of Science and Techno↗

Power flow in magnetically insulated transmission lines with ion backscatter effects

Ion backscattering off of surfaces in magnetically insulated transmission lines (MITLs) is often ignored in kinetic simulations of MITL power flow. Backscattering reduces ion current losses and the surface impact heating, which dictates the rate at which surface-adsorbed contaminants are liberated into the anode–cathode gap. Backscatter probabilities are difficult to implement in a kinetic code because there are limited data for incident ion energies less than a few keV. This paper presents an analytic model based on the Rutherford scattering formula that reproduces the measured backscatter probabilities at high incident energies and transitions to the highly reflective behavior expected at low incident energies. The backscatter model is implemented in power flow simulations, which are validated with current loss experiments conducted on the 0.4 TW Mykonos accelerator at Sandia National Laboratories. This simulation setup is then used in a high-current Z-machine shot. In conclusion, backscatter effects are found to be unimportant in the low-current Mykonos regime but significantly reduce current losses at the Z-machine scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

SIMULATIONS AND THEORY OF ION INJECTION AT NON-RELATIVISTIC COLLISIONLESS SHOCKS

We use kinetic hybrid simulations (kinetic ions-fluid electrons) to characterize the fraction of ions that are accelerated to non-thermal energies at non-relativistic collisionless shocks. We investigate the properties of the shock discontinuity and show that shocks propagating almost along the background magnetic field (quasi-parallel shocks) reform quasi-periodically on ion cyclotron scales. Ions that impinge on the shock when the discontinuity is the steepest are specularly reflected. This is a necessary condition for being injected, but it is not sufficient. Also, by following the trajectories of reflected ions, we calculate the minimum energy needed for injection into diffusive shock acceleration, as a function of the shock inclination. We construct a minimal model that accounts for the ion reflection from quasi-periodic shock barrier, for the fraction of injected ions, and for the ion spectrum throughout the transition from thermal to non-thermal energies. This model captures the physics relevant for ion injection at non-relativistic astrophysical shocks with arbitrary strengths and magnetic inclinations, and represents a crucial ingredient for understanding the diffusive shock acceleration of cosmic rays.

79 ASTRONOMY AND ASTROPHYSICS↗

Comparative Implementation of High Performance Computing for Power System Dynamic Simulations

Dynamic simulation for transient stability assessment is one of the most important, but intensive, computations for power system planning and operation. Present commercial software is mainly designed for sequential computation to run a single simulation, which is very time consuming with a single processer. The application of High Performance Computing (HPC) to dynamic simulations is very promising in accelerating the computing process by parallelizing its kernel algorithms while maintaining the same level of computation accuracy. This paper describes the comparative implementation of four parallel dynamic simulation schemes in two state-of-the-art HPC environments: Message Passing Interface (MPI) and Open Multi-Processing (OpenMP). These implementations serve to match the application with dedicated multi-processor computing hardware and maximize the utilization and benefits of HPC during the development process.

97 MATHEMATICS AND COMPUTING↗

DEGRADATION IN PERFORMANCE OF LANTHANUM STRONTIUM MANGANITE BASED SOLID OXIDE FUEL CELL CATHODES UNDER ACCELERATED TESTING

The performance of solid oxide fuel cells (SOFCs) with three different lanthanum strontium manganite (LSM) based cathode compositions were evaluated. All cells were yttria-stabilized zirconia (Zr0.92Y0.08O2-δ, 8YSZ) electrolyte-supported button cells, consisting of a nickel oxide – yttria-stabilized zirconia (NiO-8YSZ) anode and a cathode of 8YSZ and LSM. The three LSM compositions differed in the amount of excess Mn: Composition A was (La0.85Sr0.15)0.90MnO3±δ (10% excess Mn); Composition B was (La0.80Sr0.20)0.95MnO3±δ (5% excess Mn); and Composition C was (La0.80Sr0.20)0.98MnO3±δ (2% excess Mn). The cells were tested under conventional and accelerated conditions, where the accelerated conditions were meant to simulate the results of months of long-term testing in just 500 hours (approximately three weeks) of testing by using high operating temperature and current density. Accelerated tests showed lower degradation rates, lower continuous area specific resistance (ASR), and higher power output than conventional tests for all cathode compositions. Continuous measurements of the cells' output voltage versus time, together with periodic electrochemical impedance spectroscopy (EIS) measurements, were used to evaluate the performance of the cells in terms of ASR degradation rates (% ASR rise per kh) and power outputs. The EIS measurements also permitted a partial deconvolution of the cathode ASR from the anode ASR. Cathodes with 10% excess Mn tested under accelerated conditions had the lowest degradation rates, but the highest continuous ASR and lowest power outputs. Cathodes with 2% excess Mn tested under accelerated conditions had the lowest continuous ASR and highest power outputs; thus it was concluded that cells with the lowest amount of excess Mn cathodes performed the best.

08 HYDROGEN↗

Non-thermal electron acceleration from magnetically driven reconnection in a laboratory plasma

Magnetic reconnection rapidly converts magnetic energy into some combination of plasma flow energy, thermal energy and non-thermal energetic particles. Various reconnection acceleration mechanisms have been theoretically proposed and numerically studied in different collisionless and low-β environments, where β refers to the plasma-to-magnetic pressure ratio. These mechanisms include Fermi acceleration, betatron acceleration, parallel electric field acceleration along magnetic fields and direct acceleration by the reconnection electric field. However, none of them have been experimentally confirmed, as the direct observation of non-thermal particle acceleration in laboratory experiments has been difficult due to short Debye lengths for in situ measurements and short mean free paths for ex situ measurements. Here we report the direct measurement of accelerated non-thermal electrons from magnetically driven reconnection at low β in experiments using a laser-powered capacitor coil platform. We use kilojoule lasers to drive parallel currents to reconnect megagauss-level magnetic fields in a quasi-axisymmetric geometry. The angular dependence of the measured electron energy spectrum and the resulting accelerated energies, supported by particle-in-cell simulations, indicate that the mechanism of direct electric field acceleration by the out-of-plane reconnection electric field is at work. Scaled energies using this mechanism show direct relevance to astrophysical observations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Characterizing the acceleration time of laser-driven ion acceleration with data-informed neural networks

Peak ion energy is an important figure-of-merit in short-pulse, laser-driven ion acceleration and is dependent on an associated acceleration time. Standard metrics for these quantities depend on analytical results such as the self-similar fluid model or empirical models based on relatively small experimental and simulation datasets. In this work we attempt to use a data-informed neural network (NN) as a surrogate model for a large ensemble of PIC simulations to investigate an effective acceleration time. We explore the application of a stacked convolutional and recurrent NN architecture for improved regression by incorporating the time dependencies of the data into the training process. Of particular note is how pretraining a network on lower fidelity data, e.g. 1D analytical results, greatly improves the network's ability to learn more complex, higher fidelity data. Finally, the dependency of the acceleration time on various laser and plasma parameters is explored.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Accelerate M-TIP on GPUs and deploy to Summit and NERSC-9 (against simulated data) WBS 2.2.4.05 ExaFEL, Milestone ADSE13-199

We evaluated the orientation matching step in the M-TIP SPI workflow for potential offloading to accelerators. We ported the code to GPUs, benchmarked it, optimized and down-selected the best versions. The accelerated version of the orientation matching code that was developed at LANL (LANL GPU v3) is 34-55X faster than sequential, 2.4-4.9X faster than the fastest OpenMP open source version we found (FAISS OpenMP) and 1.5-4X faster than the fastest GPU open source version we found (FAISS GPU). Summit single-node GPU versions were somewhat faster than Cori GPU. Image size plays a role; mid-range image sizes take more time. The LANL CUDA multi-node, multi-GPU implementation shows mostly linear strong scaling. I/O also plays a large role; splitting data into parts improves read time and burst buffers dramatically improve read times. This work will be integrated into the M-TIP workflow as part of the next milestone ADSE13-193.

97 MATHEMATICS AND COMPUTING↗

Dependence of emittance on the length of an electron bunch during laser-plasma acceleration in guiding structures

We report a theoretical analysis and numerical simulation of the dynamics of transverse emittance of an electron bunch during its acceleration in wake fields generated by a laser pulse in a weakly nonlinear mode. Analytical expressions are obtained for the main factors affecting the emittance growth during acceleration and the case is considered when the characteristic transverse size of the injected bunch exceeds the matched radius determined by the focusing force at the injection point, the initial emittance and the electron bunch energy, and the resulting value of emittance is much larger than the initial one. The dynamics of the emittance growth during acceleration as a function of the length of the electron bunch is described, and the length of the bunch is found at which there occurs a complete phase mixing of betatron oscillations of electrons and the emittance increases to its maximum value determined by the bunch parameters and the focusing force at the injection point. Analytical expressions are in good agreement with the results of numerical simulation. (paper)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Challenges of conventional iterative all-atom and coarse-grained multiscale molecular dynamics

In this work, we evaluate the biomolecular dynamics behaviors when conventionally iterating between all-atom (AA) and coarse-grained (CG) molecular dynamics (MD) simulations over multiple cycles. We implemented the workflow to iterate between AA and CG in OpenMM, namely the iterative multiscale MD (iMMD) simulation workflow. In particular, we aim to identify practical applications for iterating between AA and CG simulations in a conventional manner without any constraints or model modifications. We evaluate the iMMD workflow on four representative systems, spanning folding of two soluble proteins and protein-protein as well as protein-lipid interactions of two membrane proteins. We observe that iteration between AA and CG representations could help the soluble proteins exit undesirable metastable states to fold, resulting from random protein structural distortions due to cycling. Consequently, the most reliable use of iterative AA and CG simulations appears to be to accelerating complex lipid mixing for membrane-bound protein systems rather than sampling protein conformational space. Our work explores the practical usages and limitations for iterative AA and CG simulations using readily available AA and CG force fields. The evaluated iMMD workflow in OpenMM is made available at https://github.com/lanl/iMMD.

59 BASIC BIOLOGICAL SCIENCES↗

Simulating Microbial Community Patterning Using Biocellion

Mathematical modeling and computer simulation are important tools for understanding complex interactions between cells and their biotic and abiotic environment: similarities and differences between modeled and observed behavior provide the basis for hypothesis forma- tion. Momeni et al. [5] investigated pattern formation in communities of yeast strains engaging in different types of ecological interactions, comparing the predictions of mathematical modeling and simulation to actual patterns observed in wet-lab experiments. However, simu- lations of millions of cells in a three-dimensional community are ex- tremely time-consuming. One simulation run in MATLAB may take a week or longer, inhibiting exploration of the vast space of parameter combinations and assumptions. Improving the speed, scale, and accu- racy of such simulations facilitates hypothesis formation and expedites discovery. Biocellion is a high performance software framework for ac- celerating discrete agent-based simulation of biological systems with millions to trillions of cells. Simulations of comparable scale and accu- racy to those taking a week of computer time using MATLAB require just hours using Biocellion on a multicore workstation. Biocellion fur- ther accelerates large scale, high resolution simulations using cluster computers by partitioning the work to run on multiple compute nodes. Biocellion targets computational biologists who have mathematical modeling backgrounds and basic C++ programming skills. This chap- ter describes the necessary steps to adapt the original Momeni et al.'s model to the Biocellion framework as a case study.

metabolic interaction↗

Active Learning Surrogates for Integrating Electron Microscopy and Computational Insights from Simulations in Autonomous Experiments

Artificial Intelligence (AI) combined with simulations and experiments has great potential to accelerate scientific discovery across technology and pharmaceuticals. However, the gap between simulations and experiments is challenging due to disparities in time and scale, making it difficult to estimate properties like energy and electronic states from experiments, and to provide feedback based on theoretical insights.Our research addresses the challenge by developing unique deep kernel based surrogate models that learns from microscopic images, mapping structural features to energy differences from defect formation. We start with full-training using simulated images to determine optimal settings, establishing a baseline for active learning. Using these settings from the baseline, active learning is trained, and predicts structures along simulation trajectories based on uncertainty and energetic stability, thus reducing data requirements, simulation time and computational costs. The results demonstrate that the model achieves a low average error margin of approximately 0.03 meV, indicating good performance. To enhance feature extraction and reconstruction capabilities, we developed an autoencoder-decoder as additional surrogate to create latent space to capture essential features, enabling precise comparisons between simulations and experiments. The results from this model achieved a reconstruction loss of around 0.2 and accurately reconstructed molecular structures.Overall, this work advances the steering of experiments through computational simulations by employing a surrogate models that actively predicts the trajectories of structural evolution, achieving time-to-solution comparable to experimental measurements.

Saranathan, Gayathri [Hewlett-Packard]↗

Modeling Electron Acceleration and Transport in the Early Impulsive Phase of the 2017 September 10th Solar Flare

The X8.2-class limb flare on 2017 September 10 is among the best studied solar flare events owing to its great similarity to the standard flare model and the broad coverage by multiple spacecraft and ground-based observations. These multiwavelength observations indicate that electron acceleration and transport are efficient in the reconnection and flare looptop regions. However, there lacks a comprehensive model for explaining and interpreting the multi-faceted observations. In this work, we model the electron acceleration and transport in the early impulsive phase of this flare. We solve the Parker transport equation that includes the primary acceleration mechanism during magnetic reconnection in the large-scale flare region modeled by MHD simulations. We find that electrons are accelerated up to several MeV and fill a large volume of the reconnection region, similar to the observations shown in microwaves. The electron spatial distribution and spectral shape in the looptop region agree well with those derived from the microwave and hard X-ray emissions before magnetic islands grow large and dominate the acceleration. Future emission modelings using the electron maps will enable direct comparison with microwave and hard X-ray observations. These results shed new light on the electron acceleration and transport in a broad region of solar flares within a data-constrained realistic flare geometry.

79 ASTRONOMY AND ASTROPHYSICS↗

Computational Methods to Characterize Panel Loading Conditions for Accelerated Testing

Panel cracking and degradation due to wind loading are known to have a detrimental effect on power output. Recreating these damaging conditions in a controlled experimental setting requires an understanding of the loads being generated at the panel surface as a function of both wind speed, wind direction, and panel orientation. To better understand these relationships, a computational fluid dynamics (CFD) simulation package was constructed using an open-source Python library for solving partial differential equations with the finite element method. This CFD package allows the simulated wind speed and panel orientation of a multi-panel array to be easily changed and provides the capability to measure the traction forces at discrete points along the sun-facing and ground-facing surface of an interior panel residing in the wake of one or more upstream panels. A parameter exploration was performed in which the panel angle was varied in even increments from -70 deg to 70 deg and the wind speed was varied from 2 to 30 m/s. During post processing, the measured traction along the panel surface was averaged spatially and interpreted as a time-varying signal, where further processing of this signal yielded the root mean square amplitude and a characteristic frequency associated with the loading. This study found that higher wind speeds are generally associated with increased amplitude of loading and that the panel orientation angle can significantly exacerbate or mitigate this loading. These outcomes are presented along with current work on higher-fidelity verification simulations and recommendations for performing accelerated experimental testing.

loading↗

Kinetic beaming in radiative relativistic magnetic reconnection: a mechanism for rapid gamma-ray flares in jets

ABSTRACT Rapid gamma-ray flares pose an astrophysical puzzle, requiring mechanisms both to accelerate energetic particles and to produce fast observed variability. These dual requirements may be satisfied by collisionless relativistic magnetic reconnection. On the one hand, relativistic reconnection can energize gamma-ray emitting electrons. On the other hand, as previous kinetic simulations have shown, the reconnection acceleration mechanism preferentially focuses high energy particles – and their emitted photons – into beams, which may create rapid blips in flux as they cross a telescope’s line of sight. Using a series of 2D pair-plasma particle-in-cell simulations, we explicitly demonstrate the critical role played by radiative (specifically inverse Compton) cooling in mediating the observable signatures of this ‘kinetic beaming’ effect. Only in our efficiently cooled simulations do we measure kinetic beaming beyond one light crossing time of the reconnection layer. We find a correlation between the cooling strength and the photon energy range across which persistent kinetic beaming occurs: stronger cooling coincides with a wider range of beamed photon energies. We also apply our results to rapid gamma-ray flares in flat-spectrum radio quasars, suggesting that a paradigm of radiatively efficient kinetic beaming constrains relevant emission models. In particular, beaming-produced variability may be more easily realized in two-zone (e.g. spine-sheath) set-ups, with Compton seed photons originating in the jet itself, rather than in one-zone external Compton scenarios.

79 ASTRONOMY AND ASTROPHYSICS↗

ADVANTG Results for a Proposed NDA System for Detecting Pin Diversion from SNF - Paper 120

This summary describes the results of applying the ADVANTG variance reduction parameter generator to accelerate continuous-energy Monte Carlo simulations of the {sup 252}Cf Interrogation with Prompt Neutron (CIPN) detection system proposed by Hu et al. for detecting the diversion of fuel elements from spent nuclear fuel (SNF) assemblies. In previous work, ADVANTG was applied to a suite of nine radiation detection, special nuclear material (SNM) movement detection, and safeguards test cases. That effort demonstrated that ADVANTG was able to provide large increases in tally figures of merit (FOMs) in nearly all of the cases without introducing bias into the Monte Carlo results. The objective of the work described here is to further evaluate ADVANTG, and also to identify gaps in capability with regard to nuclear safeguards applications, by applying the code to a challenging problem that is of a different nature from the ones previously studied. The CIPN nondestructive assay (NDA) system consists of three fission chambers embedded in a C-shaped block of polyethylene and a polyethylene-moderated {sup 252}Cf source that are placed on opposite sides of a subject SNF assembly. The idea of the detection system is to measure the difference between the background neutron count rate, due to spontaneous fission in the fuel material, and the count rate observed once the source is introduced, which is dominated by multiplication within the assembly. Based on the difference between these count rates, the fissile content of the assembly can be inferred, and this information can be used to determine if some fraction of the original fuel pins have been replaced with depleted uranium substitutes. The authors report that the system can detect the replacement of at least eight pins (3% of total mass). The ADVANTG code generates space- and energy-dependent weight-window bounds and biased source distributions based on approximate transport solutions that are efficiently generated by the Denovo 3-D discrete ordinates package. ADVANTG implements the Consistent Adjoint Driven Importance Sampling (CADIS) method for accelerating individual tallies and the Forward-Weighted CADIS (FW-CADIS) method for obtaining relatively uniform uncertainties across tallies over multiple regions and/or energy bins. The variance reduction parameters are generated in a format directly usable by standard versions of MCNP5 and MCNPX. In this work, the ADVANTG variance reduction parameter generator was applied to accelerate continuous energy MCNPX simulations of the {sup 252}Cf Interrogation with Prompt Neutron detection system for detecting the diversion of fuel elements from SNF assemblies. Variance reduction parameters generated with the existing version of ADVANTG actually slowed down tally convergence in all cases. The cause of the poor performance was found to be the lack of an induced fission source treatment in the fixed-source discrete ordinates calculations employed by ADVANTG. Because fission was treated as capture and not as a source, the importance maps generated by ADVANTG significantly underestimated the importance of thermal neutrons in and around the fuel elements. In order to obtain improved results, we developed an experimental implementation of a fission source outer iteration for the adjoint calculations. We used this prototype capability to generate new variance reduction parameters and found that the mean fission rates agreed well with those predicted by the conventional MCNPX simulations, as was expected. With these new parameters, speedup factors of 59 to 80 were obtained for the case with the background source, and factors of 17 to 24 were obtained for the cases with the interrogating source. These results demonstrate that a fission source treatment is needed to improve the effectiveness of ADVANTG in problems where the effects of induced fission are important. This includes many types of NDA problems that are relevant to safeguards applications. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Unified differentiable digital twin for the IOTA/FAST facility

As the design complexity of modern accelerators grows, there is more interest in using advanced simulations that have fast execution time or produce insights about accelerator state. One notable example of additional information are gradients of physical observables with respect to design parameters produced by differentiable simulations. The IOTA/FAST facility has recently begun a program to implement and experimentally validate a unified start-to-end differentiable digital twin to serve as a virtual accelerator test stand, allowing for rapid prototyping of new software and experiments with minimal beam time costs. In this contribution we will discuss our plans and progress. Specifically, we will cover the selection and benchmarking of both physics and ML codes, the development of generic interfaces between device models and surrogate or physics-based sections, and the export of the parameters through either a deterministic event loop or a fully asynchronous EPICS soft input/output controller. We will also discuss challenges in model calibration and uncertainty quantification, as well as future plans to support larger proton accelerators like PIPII and Booster.

Kuklev, Nikita [Fermilab]↗

Kernel fusion in atomistic spin dynamics simulations on Nvidia GPUs using tensor core

In atomistic spin dynamics simulations, the time cost of constructing the space- and time-displaced pair correlation function in real space increases quadratically as the number of spins N, leading to significant computational effort. The GEMM subroutine can be adopted to accelerate the calculation of the dynamical spin-spin correlation function, but the computational cost of simulating large spin systems (>40000 spins) on CPUs remains expensive. In this work, we perform the simulation on the graphics processing unit (GPU), a hardware solution widely used as an accelerator for scientific computing and deep learning. Here we show that GPUs can accelerate the simulation up to 25-fold compared to multi-core CPUs when using the GEMM subroutine on both. To hide memory latency, we fuse the element-wise operation into the GEMM kernel using CUTLASS that can improve the performance by 26% ~ 33% compared to implementation based on cuBLAS. Furthermore, we perform the on-the-fly calculation in the epilogue of the GEMM subroutine to avoid saving intermediate results on global memory, which makes the large-scale atomistic spin dynamics simulation feasible and affordable.

97 MATHEMATICS AND COMPUTING↗