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At least 271 records · Page 15

Simulated orbiter lift-off acceleration - A stochastic model

A simple procedure for generating synthetic orbiter liftoff acceleration is described. This stochastic method is based on a filtered white noise model which accounts for the nonstationary time evolution of amplitude and frequency content of orbiter lift-off accelerations. The example of Space Transportation System STS-41 Z-acceleration is carefully examined, and the corresponding synthetic orbiter lift-off accelerations model was developed. It is shown that the resulting simulated accelerations preserve significant properties of the original record. Statistically based acceleration response spectra curves for the simulated orbiter lift-off excitations are also evaluated and the results are compared with those for the actual flight data.

Lee-Glauser, Gina↗

Kinetic Simulations of Particle Acceleration at Shocks

Collisionless shocks are mediated by collective electromagnetic interactions and are sources of non-thermal particles and emission. The full particle-in-cell approach and a hybrid approach are sketched, simulations of collisionless shocks are shown using a multicolor presentation. Results for SN 1006, a case involving ion acceleration and B field amplification where the shock is parallel, are shown. Electron acceleration takes place in planetary bow shocks and galaxy clusters. It is concluded that acceleration at shocks can be efficient: >15%; CRs amplify B field via streaming instability; ion DSA is efficient at parallel, strong shocks; ions are injected via reflection and shock drift acceleration; and electron DSA is efficient at oblique shocks.

79 ASTRONOMY AND ASTROPHYSICS↗

Numerical and laboratory simulations of auroral acceleration

The existence of parallel electric fields is an essential ingredient of auroral physics, leading to the acceleration of particles that give rise to the auroral displays. An auroral flux tube is modelled using electrostatic Vlasov simulations, and the results are compared to simulations of a proposed laboratory device that is meant for studies of the plasma physical processes that occur on auroral field lines. The hot magnetospheric plasma is represented by a gas discharge plasma source in the laboratory device, and the cold plasma mimicking the ionospheric plasma is generated by a Q-machine source. In both systems, double layers form with plasma density gradients concentrated on their high potential sides. The systems differ regarding the properties of ion acoustic waves that are heavily damped in the magnetosphere, where the ion population is hot, but weakly damped in the laboratory, where the discharge ions are cold. Ion waves are excited by the ion beam that is created by acceleration in the double layer in both systems. The efficiency of this beam-plasma interaction depends on the acceleration voltage. For voltages where the interaction is less efficient, the laboratory experiment is more space-like.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Community Project for Accelerator Science and Simulation (ComPASS) Final Report

Tech-X participated across the full range of ComPASS activities, with efforts in the Energy Frontier primarily through modeling of laser plasma accelerators and dielectric laser acceleration, in the Intensity Frontier primarily through electron cloud modeling, and in Uncertainty Quantification being applied to dielectric laser acceleration. In the following we present the progress and status of our activities for the entire period of the ComPASS project for the different areas of Energy Frontier, Intensity Frontier and Uncertainty Quantification.

43 PARTICLE ACCELERATORS↗

NUMERICAL SIMULATIONS OF SPICULE ACCELERATION

Observations in the H{alpha} line of hydrogen and the H and K lines of singly ionized calcium on the solar limb reveal the existence of structures with jet-like behavior, usually designated as spicules. The driving mechanism for such structures remains poorly understood. Sterling et al. shed some light on the problem mimicking reconnection events in the chromosphere with a one-dimensional code by injecting energy with different spatial and temporal distributions and tracing the thermodynamic evolution of the upper chromospheric plasma. They found three different classes of jets resulting from these injections. We follow their approach but improve the physical description by including non-LTE cooling in strong spectral lines and non-equilibrium hydrogen ionization. Increased cooling and conversion of injected energy into hydrogen ionization energy instead of thermal energy both lead to weaker jets and smaller final extent of the spicules compared with Sterling et al. In our simulations we find different behavior depending on the timescale for hydrogen ionization/recombination. Radiation-driven ionization fronts also form.

79 ASTRONOMY AND ASTROPHYSICS↗

Simulation Studies of the Dielectric Grating as an Accelerating and Focusing Structure

A grating-based design is a promising candidate for a laser-driven dielectric accelerator. Through simulations, we show the merits of a readily fabricated grating structure as an accelerating component. Additionally, we show that with a small design perturbation, the accelerating component can be converted into a focusing structure. The understanding of these two components is critical in the successful development of any complete accelerator. The concept of accelerating electrons with the tremendous electric fields found in lasers has been proposed for decades. However, until recently the realization of such an accelerator was not technologically feasible. Recent advances in the semiconductor industry, as well as advances in laser technology, have now made laser-driven dielectric accelerators imminent. The grating-based accelerator is one proposed design for a dielectric laser-driven accelerator. This design, which was introduced by Plettner, consists of a pair of opposing transparent binary gratings, illustrated in Fig. 1. The teeth of the gratings serve as a phase mask, ensuring a phase synchronicity between the electromagnetic field and the moving particles. The current grating accelerator design has the drive laser incident perpendicular to the substrate, which poses a laser-structure alignment complication. The next iteration of grating structure fabrication seeks to monolithically create an array of grating structures by etching the grating's vacuum channel into a fused silica wafer. With this method it is possible to have the drive laser confined to the plane of the wafer, thus ensuring alignment of the laser-and-structure, the two grating halves, and subsequent accelerator components. There has been previous work using 2-dimensional finite difference time domain (2D-FDTD) calculations to evaluate the performance of the grating accelerator structure. However, this work approximates the grating as an infinite structure and does not accurately model a realizable structure. In this paper, we will present a 3-dimensional frequency-domain simulation of both the infinite and the finite grating accelerator structure. Additionally, we will present a new scheme for a focusing structure based on a perturbation of the accelerating structure. We will present simulations of this proposed focusing structure and quantify the quality of the focusing fields.

36 MATERIALS SCIENCE↗

Community Project for Accelerator Science and Simulation-3

The focus of the Rensselaer efforts for COMPASS-3 was the development of parallel mesh adaptation procedures for high-order unstructured meshes where elements must be curved to properly approximate the domain geometry. The procedures developed were integrated into the ACE3P accelerator modeling code. Areas of development included: High order curved mesh representations that can provide the orders of geometric approximation needed. A curved mesh adaptation procedure that can match an adaptively defined anisotropic mesh metric field. In-memory integration of these procedures with the Omega3P code to provide an effective parallel adaptive simulation work flow. Improved dynamic load balancing tools that account for the degrees of freedom associated with the various order mesh entities (vertices, edges, faces and regions).

42 ENGINEERING↗

Parallel quantum computing simulations via quantum accelerator platform virtualization

Quantum circuit execution is a central task in quantum computation. Due to inherent quantum-mechanical constraints, quantum computing workflows often involve a considerable number of independent measurements over a large set of slightly different quantum circuits. Here we discuss a simple model for parallelizing such quantum circuit executions that is based on introducing a large array of virtual quantum processing units (mapped to HPC nodes in our case) as a parallel quantum computing platform. Implemented within the XACC framework, the model can readily take advantage of its backend-agnostic features, enabling parallel quantum computing/simulation over any target backend supported by XACC. We illustrate the performance of this approach by demonstrating strong scaling in two pertinent domain science problems, namely in computing the gradients for the multi-contracted variational quantum eigensolver and in data-driven quantum circuit learning, where we vary the number of qubits and the number of circuit layers. Here, the latter simulation leverages the cuQuantum library to run efficiently on GPU-accelerated HPC platforms.

97 MATHEMATICS AND COMPUTING↗

The GENGA code: gravitational encounters in N-body simulations with GPU acceleration

We describe an open source GPU implementation of a hybrid symplectic N-body integrator, GENGA (Gravitational ENcounters with Gpu Acceleration), designed to integrate planet and planetesimal dynamics in the late stage of planet formation and stability analyses of planetary systems. GENGA uses a hybrid symplectic integrator to handle close encounters with very good energy conservation, which is essential in long-term planetary system integration. We extended the second-order hybrid integration scheme to higher orders. The GENGA code supports three simulation modes: integration of up to 2048 massive bodies, integration with up to a million test particles, or parallel integration of a large number of individual planetary systems. We compare the results of GENGA to Mercury and pkdgrav2 in terms of energy conservation and performance and find that the energy conservation of GENGA is comparable to Mercury and around two orders of magnitude better than pkdgrav2. GENGA runs up to 30 times faster than Mercury and up to 8 times faster than pkdgrav2. GENGA is written in CUDA C and runs on all NVIDIA GPUs with a computing capability of at least 2.0.

79 ASTRONOMY AND ASTROPHYSICS↗

Anisotropic hydrogen diffusion in α-Zr and Zircaloy predicted by accelerated kinetic Monte Carlo simulations

Here, this report presents an accelerated kinetic Monte Carlo (KMC) method to compute the diffusivity of hydrogen in hcp metals and alloys, considering both thermally activated hopping and quantum tunneling. The acceleration is achieved by replacing regular KMC jumps in trapping energy basins formed by neighboring tetrahedral interstitial sites, with analytical solutions for basin exiting time and probability. Parameterized by density functional theory (DFT) calculations, the accelerated KMC method is shown to be capable of efficiently calculating hydrogen diffusivity in α-Zr and Zircaloy, without altering the kinetics of long-range diffusion. Above room temperature, hydrogen diffusion in α-Zr and Zircaloy is dominated by thermal hopping, with negligible contribution from quantum tunneling. The diffusivity predicted by this DFT + KMC approach agrees well with that from previous independent experiments and theories, without using any data fitting. The diffusivity along < c > is found to be slightly higher than that along < a >, with the anisotropy saturated at about 1.20 at high temperatures, resolving contradictory results in previous experiments. Demonstrated using hydrogen diffusion in α-Zr, the same method can be extended for on-lattice diffusion in hcp metals, or systems with similar trapping basins.

36 MATERIALS SCIENCE↗

Self-consistent core-pedestal transport simulations with neural network accelerated models

Fusion whole device modeling simulations require comprehensive models that are simultaneously physically accurate, fast, robust, and predictive. In this paper we describe the development of two neural-network (NN) based models as a means to perform a snon-linear multivariate regression of theory-based models for the core turbulent transport fluxes, and the pedestal structure. Specifically, we find that a NN-based approach can be used to consistently reproduce the results of the TGLF and EPED1 theory-based models over a broad range of plasma regimes, and with a computational speedup of several orders of magnitudes. These models are then integrated into a predictive workflow that allows prediction with self-consistent core-pedestal coupling of the kinetic profiles within the last closed flux surface of the plasma. Finally, the NN paradigm is capable of breaking the speed-accuracy trade-off that is expected of traditional numerical physics models, and can provide the missing link towards self-consistent coupled core-pedestal whole device modeling simulations that are physically accurate and yet take only seconds to run.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Scaling methods for accelerating kinetic Monte Carlo simulations of chemical reaction networks

Various kinetic Monte Carlo algorithms become inefficient when some of the population sizes in a system are large, which gives rise to a large number of reaction events per unit time. In this work, we present a new acceleration algorithm based on adaptive and heterogeneous scaling of reaction rates and stoichiometric coefficients. The algorithm is conceptually related to the commonly used idea of accelerating a stochastic simulation by considering a subvolume λΩ (0 < λ < 1) within a system of interest, which reduces the number of reaction events per unit time occurring in a simulation by a factor 1/λ at the cost of greater error in unbiased estimates of first moments and biased overestimates of second moments. Our new approach offers two unique benefits. First, scaling is adaptive and heterogeneous, which eliminates the pitfall of overaggressive scaling. Second, there is no need for an a priori classification of populations as discrete or continuous (as in a hybrid method), which is problematic when discreteness of a chemical species changes during a simulation. The method requires specification of only a single algorithmic parameter, N c , a global critical population size above which populations are effectively scaled down to increase simulation efficiency. The method, which we term partial scaling, is implemented in the open-source BioNetGen software package. We demonstrate that partial scaling can significantly accelerate simulations without significant loss of accuracy for several published models of biological systems. Finally, these models characterize activation of the mitogen-activated protein kinase ERK, prion protein aggregation, and T-cell receptor signaling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cluster analysis of accelerated molecular dynamics simulations: A case study of the decahedron to icosahedron transition in Pt nanoparticles

Modern molecular-dynamics-based techniques are extremely powerful to investigate the dynamical evolution of materials. With the increase in sophistication of the simulation techniques and the ubiquity of massively parallel computing platforms, atomistic simulations now generate very large amounts of data, which has to be carefully analyzed in order to reveal key features of the underlying trajectories, including the nature and characteristics of the relevant reaction pathways. We show that clustering algorithms, such as the Perron Cluster Cluster Analysis, can provide reduced representations that greatly facilitate the interpretation of complex trajectories. To illustrate this point, clustering tools are used to identify the key kinetic steps in complex Accelerated Molecular Dynamics trajectories exhibiting shape uctuations in Pt nanoclusters. This analysis provides an easily-interpretable coarse representation of the reaction pathways in terms of a handful of clusters, in contrast to the raw trajectory that contains thousands of unique states and tens of thousands of transitions.

74 ATOMIC AND MOLECULAR PHYSICS↗

Requirements for Simulating Space Radiation With Particle Accelerators

Interplanetary space radiation consists of fully ionized nuclei of atomic elements with high energy for which only the few lowest energy ions can be stopped in shielding materials. The health risk from exposure to these ions and their secondary radiations generated in the materials of spacecraft and planetary surface enclosures is a major limiting factor in the management of space radiation risk. Accurate risk prediction depends on a knowledge of basic radiobiological mechanisms and how they are modified in the living tissues of a whole organism. To a large extent, this knowledge is not currently available. It is best developed at ground-based laboratories, using particle accelerator beams to simulate the components of space radiation. Different particles, in different energy regions, are required to study different biological effects, including beams of argon and iron nuclei in the energy range 600 to several thousand MeV/nucleon and carbon beams in the energy range of approximately 100 MeV/nucleon to approximately 1000 MeV/nucleon. Three facilities, one each in the United States, in Germany and in Japan, currently have the partial capability to satisfy these constraints. A facility has been proposed using the Brookhaven National Laboratory Booster Synchrotron in the United States; in conjunction with other on-site accelerators, it will be able to provide the full range of heavy ion beams and energies required. International cooperation in the use of these facilities is essential to the development of a safe international space program.

Schimmerling, W.↗

Time-dependent-bases with local CUR decomposition method for accelerating turbulent combustion simulations

Here, this study presents a novel reduced-order modeling framework, Time-Dependent Bases with Local CUR decomposition (TDB-L-CUR), designed to efficiently and accurately approximate the species transport equations in reacting flow simulations. The method extends the existing TDB-CUR approach for chemically reacting flows (Jung et al. Comput. Methods Appl. Mech. Engrg. 437 (2025) 117758), which leverages matrix decomposition techniques to form a global-in-space, time-dependent low-dimensional manifold. While TDB-CUR performs well in homogeneous systems, it may be less well-suited to spatially heterogeneous systems such as turbulent flames, where higher-rank approximations are typically required. The proposed TDB-L-CUR framework introduces two methodological extensions to the baseline approach. First, it applies unsupervised clustering to partition the physical domain into distinct regions, enabling spatially localized manifold construction, thereby reducing the rank required for the reduced-order representation. Second, it incorporates a computational singular perturbation (CSP)-based scheme for identifying and penalizing fast species, allowing for spatio-temporally adaptive mitigation of chemical stiffness. The proposed framework is validated on a hierarchy of test cases, including a one-dimensional premixed flame, a two-dimensional nonpremixed ignition case with vortex interaction, and a three-dimensional turbulent premixed flame. TDB-L-CUR significantly improves accuracy over TDB-CUR while further reducing computational cost. The fully on-the-fly formulation of TDB-L-CUR (i.e., requiring no offline training or prior knowledge) makes it a robust and scalable tool for reduced-order modeling of reactive flows.

Local manifold↗

Accelerating Ab Initio Simulation via Nested Monte Carlo and Machine Learned Reference Potentials

As a corollary of the rapid advances in computing, ab initio simulation is playing an increasingly important role in modeling materials at the atomic scale. Two strategies are possible, ab initio Monte Carlo (AIMC) and molecular dynamics (AIMD) simulation. The former benefits from exact sampling from the correct thermodynamic distribution, while the latter is typically more efficient with its collective all-atom coordinate updates. In this study, using a relatively simple test model comprised of helium and argon, we show that AIMC can be brought up to, and even above, the performance levels of AIMD via a hybrid nested sampling/machine learning (ML) strategy. Here, ML provides an accurate classical reference potential (up to three-body explicit interactions) that can pilot long collective Monte Carlo moves that are accepted or rejected in toto à la nested Monte Carlo (NMC); this is in contrast to the single move nature of a naive implementation. Our proposed method only requires a small up front expense from evaluating the ab initio energies and forces of (100) random configurations for training. Importantly, our method does not totally rely on the trained, assuredly imperfect, interaction. We show that high performance and exact sampling at the desired level of theory can be realized even when the trained interaction has appreciable differences from the ab initio potential. Remarkably, at the highest levels of performance realized via our approach, a pair of statistically uncorrelated atomic configurations can be generated with (1) ab initio calculations.

74 ATOMIC AND MOLECULAR PHYSICS↗