High Fidelity Large Eddy Simulation of Reactive Supercritial Fuel Jet-in-Cross-Flow using GPU Acceleration
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Sankaran, Ramanan↗
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Particle-In-Cell Simulations of High Current Density Electron Beams in the Scorpius Linear Induction Accelerator
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Engineering - Particle accelerators↗
Simulation of diatomic gas-wall interaction and accommodation coefficients for negative ion sources and accelerators
Particle-wall interactions determine in different ways the operating conditions of plasma sources, ion accelerators, and beams operating in vacuum. For instance, a contribution to gas heating is given by ion neutralization at walls; beam losses and stray particle production—detrimental for high current negative ion systems such as beam sources for fusion—are caused by collisional processes with residual gas, with the gas density profile that is determined by the scattering of neutral particles at the walls. This paper shows that Molecular Dynamics (MD) studies at the nano-scale can provide accommodation parameters for gas-wall interactions, such as the momentum accommodation coefficient and energy accommodation coefficient: in non-isothermal flows (such as the neutral gas in the accelerator, coming from the plasma source), these affect the gas density gradients and influence efficiency and losses in particular of negative ion accelerators. For ideal surfaces, the computation also provides the angular distribution of scattered particles. Classical MD method has been applied to the case of diatomic hydrogen molecules. Single collision events, against a frozen wall or a fully thermal lattice, have been simulated by using probe molecules. Different modelling approximations are compared.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
TADSim: Discrete Event-based Performance Prediction for Temperature Accelerated Dynamics
Next-generation high-performance computing will require more scalable and flexible performance prediction tools to evaluate software--hardware co-design choices relevant to scientific applications and hardware architectures. Here, we present a new class of tools called application simulators—parameterized fast-running proxies of large-scale scientific applications using parallel discrete event simulation. Parameterized choices for the algorithmic method and hardware options provide a rich space for design exploration and allow us to quickly find well-performing software--hardware combinations. We demonstrate our approach with a TADSim simulator that models the temperature-accelerated dynamics (TAD) method, an algorithmically complex and parameter-rich member of the accelerated molecular dynamics (AMD) family of molecular dynamics methods. The essence of the TAD application is captured without the computational expense and resource usage of the full code. We accomplish this by identifying the time-intensive elements, quantifying algorithm steps in terms of those elements, abstracting them out, and replacing them by the passage of time. We use TADSim to quickly characterize the runtime performance and algorithmic behavior for the otherwise long-running simulation code. We extend TADSim to model algorithm extensions, such as speculative spawning of the compute-bound stages, and predict performance improvements without having to implement such a method. Validation against the actual TAD code shows close agreement for the evolution of an example physical system, a silver surface. Finally, focused parameter scans have allowed us to study algorithm parameter choices over far more scenarios than would be possible with the actual simulation. This has led to interesting performance-related insights and suggested extensions.
97 MATHEMATICS AND COMPUTING↗
Accelerated weight histogram method for exploring free energy landscapes
Calculating free energies is an important and notoriously difficult task for molecular simulations. The rapid increase in computational power has made it possible to probe increasingly complex systems, yet extracting accurate free energies from these simulations remains a major challenge. Fully exploring the free energy landscape of, say, a biological macromolecule typically requires sampling large conformational changes and slow transitions. Often, the only feasible way to study such a system is to simulate it using an enhanced sampling method. The accelerated weight histogram (AWH) method is a new, efficient extended ensemble sampling technique which adaptively biases the simulation to promote exploration of the free energy landscape. The AWH method uses a probability weight histogram which allows for efficient free energy updates and results in an easy discretization procedure. A major advantage of the method is its general formulation, making it a powerful platform for developing further extensions and analyzing its relation to already existing methods. Here, we demonstrate its efficiency and general applicability by calculating the potential of mean force along a reaction coordinate for both a single dimension and multiple dimensions. We make use of a non-uniform, free energy dependent target distribution in reaction coordinate space so that computational efforts are not wasted on physically irrelevant regions. We present numerical results for molecular dynamics simulations of lithium acetate in solution and chignolin, a 10-residue long peptide that folds into a β-hairpin. We further present practical guidelines for setting up and running an AWH simulation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
FPGA-Accelerated Range-Limited Molecular Dynamics
Long timescale Molecular Dynamics (MD) simulation of small molecules is crucial in drug design and basic science. To accelerate a small data set that is executed for a large number of iterations, high-efficiency is required. Recent work in this domain has demonstrated that among COTS devices only FPGA-centric clusters can scale beyond a few processors. The problem addressed here is that, as the number of on-chip processors has increased from fewer than 10 into the hundreds, previous intra-chip routing solutions are no longer viable. We find, however, that through various design innovations, high efficiency can be maintained. These include replacing the previous broadcast networks with ring-routing and then augmenting the rings with out-of-order and caching mechanisms. Others are adding a level of hierarchical filtering and memory recycling. Two novel optimized architectures emerge, together with a number of variations. These are validated, analyzed, and evaluated. We find that in the domain of interest speed-ups over GPUs are achieved. Finally, the potential impact is that this system promises to be the basis for scalable long timescale MD with commodity clusters.
97 MATHEMATICS AND COMPUTING↗
Temporal resolution criterion for correctly simulating relativistic electron motion in a high-intensity laser field
Particle-in-cell codes are now standard tools for studying ultra-intense laser-plasma interactions. Motivated by direct laser acceleration of electrons in sub-critical plasmas, we examine temporal resolution requirements that must be satisfied to accurately calculate electron dynamics in strong laser fields. Using the motion of a single electron in a perfect plane electromagnetic wave as a test problem, we show surprising deterioration of the numerical accuracy with increasing wave amplitude a{sub 0} for a given time-step. We go on to show analytically that the time-step must be significantly less than λ/ca{sub 0} to achieve good accuracy. We thus propose adaptive electron sub-cycling as an efficient remedy.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Cosmic ray acceleration at perpendicular shocks in supernova remnants
Supernova remnants (SNRs) are believed to accelerate particles up to high energies through the mechanism of diffusive shock acceleration (DSA). Except for direct plasma simulations, all modeling efforts must rely on a given form of the diffusion coefficient, a key parameter that embodies the interactions of energetic charged particles with magnetic turbulence. The so-called Bohm limit is commonly employed. In this paper, we revisit the question of acceleration at perpendicular shocks, by employing a realistic model of perpendicular diffusion. Our coefficient reduces to a power law in momentum for low momenta (of index α), but becomes independent of the particle momentum at high momenta (reaching a constant value κ{sub ∞} above some characteristic momentum p {sub c}). We first provide simple analytical expressions of the maximum momentum that can be reached at a given time with this coefficient. Then we perform time-dependent numerical simulations to investigate the shape of the particle distribution that can be obtained when the particle pressure back-reacts on the flow. We observe that for a given index α and injection level, the shock modifications are similar for different possible values of p {sub c}, whereas the particle spectra differ markedly. Of particular interest, low values of p {sub c} tend to remove the concavity once thought to be typical of non-linear DSA, and result in steep spectra, as required by recent high-energy observations of Galactic SNRs.
79 ASTRONOMY AND ASTROPHYSICS↗
Strong-field QED experiments using the BELLA PW laser dual beamlines
The petawatt (PW) laser facility of the Berkeley Lab Laser Accelerator (BELLA) Center has recently commissioned its second laser pulse transport line. This new beamline can be operated in parallel with the first beamline and enables strong-field quantum electrodynamics (SF-QED) experiments at BELLA. In this paper, we present an overview of the upgraded BELLA PW facility with a SF-QED experimental layout in which intense laser pulses collide with GeV-class laser-wakefield-accelerated electron beams. We present simulation results showing that experiments will allow the study of laser-particle interactions from the classical to the SF-QED regime with a nonlinear quantum parameter of up to χ ~2. Additionally, we show that experiments will enable the study and production of GeV-class, mrad-divergence positron beams via the Breit–Wheeler process. Graphical abstract: [Figure not available: see fulltext.].
43 PARTICLE ACCELERATORS↗
2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant
The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.
97 MATHEMATICS AND COMPUTING↗
Kinetic Monte Carlo Framework for Coupled Degradation and Dehydration of Anion Exchange Membranes
Kinetic Monte Carlo (kMC) simulations, augmented with temporal-acceleration schemes, can efficiently handle stiff reaction-transport networks when fast processes rapidly relax to quasi-equilibrium on a fixed lattice. However, in glassy anion-exchange membranes (AEM), rare and irreversible chemical degradation events continuously reshape the nanoscale morphology, and the associated hydration and transport degrees of freedom remain far from a well-defined local equilibrium. This combination of evolving state space and nonequilibrated fast dynamics lies outside the scope of existing kMC acceleration frameworks. Here, to address this challenge, we introduce an auxiliary-particle kinetic Monte Carlo (AP-kMC) scheme. In AP-kMC, short-lived mobile particles spawned at degradation sites execute hop, water-elimination, and decay moves, enforcing rapid local relaxation of the hydration structure while preserving the stochastic rules of kMC. Parameterized with molecular-dynamics morphologies and experimental solution degradation kinetics, AP-kMC reproduces the evolution of ion-exchange capacity, water uptake, and conductivity, and reveals a feedback loop in which poorly hydrated sites degrade first and each degradation event induces further local dehydration. The resulting thinning and fragmentation of water channels cause loss of hydrophilic percolation and abrupt conductivity collapse well before complete charge loss. AP-kMC thus reframes AEM durability as a coupled degradation–drying–percolation problem and provides a transferable strategy to simulate reactive, out-of-equilibrium polymer electrolytes where local solvation controls reactivity.
organic↗
Adsorption Hysteresis Under Control: Tuning Host–Guest Interactions via a Genetic Algorithm
Mesoporous adsorbent materials offer a large volumetric capacity; however, cyclic adsorption/desorption processes in these systems often suffer from hysteresis and may require a significant pressure swing to access this capacity. To mitigate hysteresis, a proposed strategy is to include nucleation sites on the walls of the mesoporous material to facilitate droplet and bubble formation, lowering the free energy barriers to the respective phase transitions. It is unclear, however, what combination of adsorbate− adsorbent interactions and spatial patterning would be beneficial for a given application, considering that improvements to some sorption properties may come at the expense of other attributes. To understand these interconnected observables, we examine two model systems, planar-slit and cylindrical pores with tunable interaction sites, using GPU-accelerated transition matrix Monte Carlo simulations. The simulations provide a free energy map of the pressure−adsorption space in a matter of minutes, which we use to track adsorption isotherm characteristics as a function of adsorbent properties. We then leverage the rapid acquisition of simulation data to construct a genetic algorithm to iteratively modify interaction sites of the slit-pore wall to minimize the hysteresis of this system without sacrificing uptake. We find that the adsorption branch of the isotherm is easily modulated via the average host−guest interaction strength, but desorption is only adjustable if there is a suitable bubble nucleation site. Within the context of a slit-pore system, we identify relative interaction strengths and patch sizes required to gain control over both branches of the hysteresis loop.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Diffusion-assisted growth of periodic patterns on metal surfaces
Periodic patterns formed on various solid surfaces could seriously affect the properties of materials. Understanding the underlying mechanism is a key step to apply and control pattern formation in many fields. In this work, periodic patterns induced by low energy plasma exposures on tungsten surfaces are observed and related new formation mechanisms are developed. Results from experiments and computer simulations demonstrate that atom diffusion accelerated by low energy and high flux exposures is the dominant mechanism for pattern formation. Additionally, a similar pattern formation has been confirmed by plasma exposure experiments on molybdenum. Based on this mechanism, patterns with controllable size and shape have been successfully prepared on tungsten surface by adjusting plasma exposure parameters, which may provide a new understanding of pattern formation and related surface damage in tungsten induced by plasma exposures.
36 MATERIALS SCIENCE↗
Irradiation instability at the inner edges of accretion disks
An instability can potentially operate in highly irradiated disks where the disk sharply transitions from being radially transparent to opaque (the 'transition region'). Such conditions may exist at the inner edges of transitional disks around T Tauri stars and accretion disks around active galactic nuclei. We derive the criterion for this instability, which we term the 'irradiation instability', or IRI. We also present the linear growth rate as a function of β, the ratio between radiation force and gravity, and c{sub s}, the sound speed of the disk, obtained using two methods: a semi-analytic analysis of the linearized equations and a numerical simulation using the GPU-accelerated hydrodynamical code PEnGUIn. In particular, we find that IRI occurs at β ∼ 0.1 if the transition region extends as wide as ∼0.05r, and at higher β values if it is wider. This threshold value applies to c{sub s} ranging from 3% of the Keplerian orbital speed to 5%, and becomes higher if c{sub s} is lower. Furthermore, in the nonlinear evolution of the instability, disks with a large β and small c{sub s} exhibit 'clumping', extreme local surface density enhancements that can reach over 10 times the initial disk surface density.
79 ASTRONOMY AND ASTROPHYSICS↗
Accelerating Thermochemical Equilibrium Calculations for Nuclear Reactor Applications
Thermochemical properties play a key role in modeling and simulation of several key phenomena in nuclear reactors. There has been an increasing interest in incorporating CALPHAD-based formulations in multiphysics simulations including for Molten Salt Reactors where knowledge of phase evolution of the salt and the chemical potentials of various elements are of utmost importance in source term analyses and redox control. However, the size of such simulations is often limited by the high computational cost of full thermodynamic equilibrium calculations. This work discusses the current efforts aimed at accelerating thermochemical equilibrium calculations for multiphysics simulations performed using the open-source finite element / finite volume code Multiphysics Object Oriented Simulation Environment (MOOSE) [1]. While several methods have been proposed for accelerating phase equilibrium calculations [2], most focus on relatively small systems and often rely on a- priori knowledge of the state-space of the system. Nuclear materials, however, are often multi-component systems owing to the evolution of composition under irradiation and an approach based on a-priori mapping of phase diagram is often not enough. This work is aimed at demonstrating an on-the-fly surrogate modeling framework that uses active learning to reduce the number of full equilibrium calculations that must be performed. By combining with efficient coupling approaches, the surrogate framework helps in reducing the computational cost of thermodynamic equilibrium informed multiphysics simulations of nuclear materials. The performance is benchmarked against full coupling with the thermochemistry library Thermochimica [3]. This work uses a machine learning based approach for constructing surrogate models to predict the stable phases in a multicomponent system. The surrogates were constructed using neural networks and Gaussian process classification. In this work, we compare the relative performance of the two methods. We also demonstrate the use of caching previous calculations by interpolating the values from nearest neighbors. References [1] Lindsay, A.D., et al. "2.0 – MOOSE: Enabling massively parallel multiphysics simulation", SoftwareX, 20 (2022): 101202. [2] Roos, W.A. and Zietsman J.H. "Accelerating complex chemical equilibrium calculations – A Review", Calphad, 77 (2022): 102380. [3] Piro, M.H.A., et al. "The thermochemistry library Thermochimica", Computational Materials Science, 67 (2013): 266-272.
36 MATERIALS SCIENCE↗
On a Critical Acceleration Scale of Dark Matter in ΛCDM and Dynamical Dark Energy
Abstract Universal acceleration a 0 emerges in various empirical laws, yet its fundamental nature remains unclear. Using Illustris and Virgo N -body simulations, we focus on the velocity and acceleration fluctuations in collisionless dark matter involving long-range gravity. For comparison, in the kinetic theory of gases, molecules undergo random elastic collisions involving short-range interactions, where only velocity fluctuations are relevant. Hierarchical structure formation proceeds through the merging of smaller halos to form larger halos, which facilitates a continuous energy cascade from small to large halos at a constant rate ε u ≈ −10 −7 m 2 s −3 . Velocity fluctuations involve a critical velocity u c ∝ (1 + z ) −3/4 . Acceleration fluctuations involve a critical acceleration a c ∝ (1 + z ) 3/4 . Two critical quantities are related by the rate of energy cascade ε u ≈ − a c u c /[2(3 π ) 2 ], where factor 3 π is from the angle of incidence during merging. With critical velocity u c on the order of 300 km s −1 at z = 0, the critical acceleration is determined to be a c 0 ≡ a c ( z = 0) ≈ 10 −10 m s −2 , suggesting a c might explain the universal acceleration a 0 ≈ 10 −10 m s −2 in the empirical Tully–Fisher relation or modified Newtonian dynamics. The redshift evolution a c ∝ (1 + z ) 3/4 is in good agreement with Magneticum and EAGLE simulations and in reasonable agreement with limited observations. This suggests a larger a 0 at a higher redshift such that galaxies of fixed mass rotate faster at a higher redshift. Note that for dark energy (DE) density ρ DE 0 ≈ a c 0 2 / G = 1 0 − 10 J m −3 , we postulate an entropic origin of the DE from acceleration fluctuations of dark matter, analogous to the gas pressure from velocity fluctuations. This leads to a dynamical DE coupled to the structure evolution involving a relatively constant DE density followed by a slow weakening phase, suggesting possible deviations from the standard ΛCDM paradigm.
N-body simulations↗
Nonlinear and adaptive estimation techniques in reentry
The development and testing of nonlinear and adaptive estimators for reentry (e.g. space shuttle) navigation and model parameter estimation or identification are reported. Of particular interest is the identifcation of vehicle lift and drag characteristics in real time. Several nonlinear filters were developed and simulated. Adaptive filters for the real time identification of vehicle lift and drag characteristics, and unmodelable acceleration, were also developed and tested by simulation. The simulations feature an uncertain system environment with rather arbitrary model errors, thus providing a definitive test of estimator performance. It was found that nonlinear effects are indeed significant in reentry trajectory estimation and a nonlinear filter is demonstrated which successfully tracks through nonlinearities without degrading the information content of the data. Under the same conditions the usual extended Kalman filter diverges and is useless. The J-adaptive filter is shown to successfully track errors in the modeled vehicle lift and drag characteristics. The same filter concept is also shown to track successfully through rather arbitrary model errors, including lift and drag errors, vehicle mass errors, atmospheric density errors, and wind gust errors.
Jazwinski, A. H.↗
ESTIMATION OF THE WAKEFIELD RESONANT FREQUENCY USING DIFFERENT SIMULATION TOOLS
Reliable and fast wakefield calculations are important for beam dynamics and THz generation in accelerators. We compare approaches and limitations with different available simulation tools and compare results. As an example, we analyse a cylindrical corrugated waveguide with narrower and wider radii of 5 and 6 mm, and aperture width and periodicity of 1 and 2 mm using ABCI by KEK and ANSYS HFSS simulation software. First, ABCI was used to determine the resonant frequency of the cylindri-cal corrugated waveguide with different lengths. The corresponding results were taken as a reference to exam-ine the simulation method in the ANSYS HFSS environ-ment. The eigenmode solver of ANSYS HFSS was used to determine different resonant frequencies. This was fol-lowed by examining a cylindrical corrugated waveguide that was implemented having a length of 17 mm for dif-ferent conductor settings. The corresponding waveguide was fed by a plane wave having a resonant frequency that satisfies the intersection of the light line and dispersion curve of the corresponding mode. The analysis showed that the maximum loss factor was achieved at 39.20 and 40.07 GHz using ANSYS HFSS simulation data for differ-ent conductors, whereas ABCI resulted in 38.50 GHz. The talk will present the results gathered by different simula-tion setups implemented in ANSYS HFSS.
Unutmaz, Muhammed [SLAC National Accelerator Labor↗