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At least 1,153 records · Page 64

A Spin-Light Polarimeter for Multi-GeV Longitudinally Polarized Electron Beams

The physics program at the upgraded Jefferson Lab (JLab) and the physics program envisioned for the proposed electron-ion collider (EIC) include large efforts to search for interactions beyond the Standard Model (SM) using parity violation in electroweak interactions. These experiments need precision electron polarimetry with an uncertainty of <; 0.5 %. The spin dependent Synchrotron radiation, called "spin-light," can be used to monitor the electron beam polarization. Here, we develop a conceptual design for a "spin-light" polarimeter that can be used at a high intensity, multi-GeV electron accelerator. We have also built a Geant4 based simulation for a prototype device and report some of the results from these simulations

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Validation of edge turbulence codes against the TCV-X21 diverted L-mode reference case

Self-consistent full-size turbulent-transport simulations of the divertor and scrape-off-layer (SOL) of existing tokamaks have recently become feasible. This enables the direct comparison of turbulence simulations against experimental measurements. In this work, we perform a series of diverted ohmic L-mode discharges on the tokamak à configuration variable (TCV) tokamak, building a first-of-a-kind dataset for the validation of edge turbulence models. This dataset, referred to as TCV-X21, contains measurements from five diagnostic systems from the outboard midplane (OMP) to the divertor targets—giving a total of 45 one- and two-dimensional comparison observables in two toroidal magnetic field directions. The experimental dataset is used to validate three flux-driven 3D fluid-turbulence models—GBS, GRILLIX and TOKAM3X. With each model, we perform simulations of the TCV-X21 scenario, individually tuning the particle and power source rates to achieve a reasonable match of the upstream separatrix value of density and electron temperature. We find that the simulations match the experimental profiles for most observables at the OMP—both in terms of profile shape and absolute magnitude—while a comparatively poorer agreement is found towards the divertor targets. The match between simulation and experiment is seen to be sensitive to the value of the resistivity, the heat conductivities, the power injection rate and the choice of sheath boundary conditions. Additionally, despite targeting a sheath-limited regime, the discrepancy between simulations and experiment also suggests that the neutral dynamics should be included. The results of this validation show that turbulence models are able to perform simulations of existing devices and achieve reasonable agreement with experimental measurements. Where disagreement is found, the validation helps to identify how the models can be improved. By publicly releasing the experimental dataset and validation analysis, this work should help to guide and accelerate the development of predictive turbulence simulations of the edge and SOL.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Massively parallel phase-field simulations targeting exascale

The interface thickness in the phase-field (PF) method limits its simulation scales. Consequently, large-scale PF simulations become prohibitively expensive for resolving the extremely fine microstructures that typically form during rapid solidification processing. This challenge is significant in predicting microstructure evolution in metal additive manufacturing and has been identified by the United States Department of Energy’s Exascale Computing Project. Here, to address this, we develop a multi-GPU and MPI-based massively parallel simulation code, utilizing state-of-the-art algorithms, software, and libraries, for large-scale three-dimensional (3D) PF simulations. We report the first GPU-parallel PF simulations on Frontier (currently the second TOP500 exascale cluster) and Summit machines, taking dendritic growth as an example problem. We evaluate the parallel performance of our implementation using scaling studies with more than 24 000 GPUs (among the largest known computations to date) and the acceleration performance using large-scale simulations of dendritic growth in 3D. Finally, massively parallel GPUs in these supercomputers enabled the first coupled multiscale simulations of laser melting and subsequent dendritic solidification on the scale of a full melt-pool, demonstrating the feasibility of performing PF simulations with a point total over 2 billion grid points within an acceptable time.

Exascale↗

FASDA: An FPGA-Aided, Scalable and Distributed Accelerator for Range-Limited Molecular Dynamics

Conducting long-term simulations of small molecules using Molecular Dynamics (MD) is crucial in drug design. However, traditional methods to accelerate the process including ASICs or GPUs, have limitations. ASICs are difficult to access, while publicly accessible GPU packages for MD have issues with more GPUs when processing small molecules, causing decreased performance. Conversely, FPGAs are renowned for their scalability and have been commonly used as accelerators for various applications, making them suitable for the task. Moreover, with the availability of FPGAs in the cloud, pharmaceutical developers can now access FPGA devices. The only missing piece is a design deployed for MD acceleration. Therefore, we present FASDA, the first FPGA-based MD accelerator available for community development. FASDA is designed to evaluate range-limited MD, which is the most resource-intensive and computationally demanding component in MD. It outperforms the state of-the-art GPU solution by 4.67x, significantly reducing the time for MD in drug design.

Wu, Chunshu↗

Revisiting the thermal effect on shock wave propagation in weakly ionized plasmas

Many researchers have investigated shock propagation in weakly ionized plasmas and observed the following anomalous effects: shock acceleration, shock recovery, shock weakening, shock spreading, and splitting. It was generally accepted that the thermal effect can explain most of the experimental results. However, little attention was paid to the shock recovery. In this paper, the shock wave propagation in weakly ionized plasmas is studied by fluid simulation. It is found that the shock acceleration, weakening, and splitting appear after it enters the plasma (thermal) region. The shock splits into two parts right after it leaves the thermal region. The distance between the splitted shocks keeps decreasing until they recover to one. This paper can explain a whole set of features of the shock wave propagation in weakly ionized plasmas. It is also found that both the shock curvature and the splitting present the same photoacoustic deflection (PAD) signals, so they cannot be distinguished by the PAD experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Induced core formation time in subcritical magnetic clouds by large-scale trans-Alfvénic flows

We clarify the mechanism of accelerated core formation by large-scale nonlinear flows in subcritical magnetic clouds by finding a semi-analytical formula for the core formation time and describing the physical processes that lead to them. Recent numerical simulations show that nonlinear flows induce rapid ambipolar diffusion that leads to localized supercritical regions that can collapse. Here, we employ non-ideal magnetohydrodynamic simulations including ambipolar diffusion for gravitationally stratified sheets threaded by vertical magnetic fields. One of the horizontal dimensions is eliminated, resulting in a simpler two-dimensional simulation that can clarify the basic process of accelerated core formation. A parameter study of simulations shows that the core formation time is inversely proportional to the square of the flow speed when the flow speed is greater than the Alfvén speed. We find a semi-analytical formula that explains this numerical result. The formula also predicts that the core formation time is about three times shorter than that with no turbulence, when the turbulent speed is comparable to the Alfvén speed.

79 ASTRONOMY AND ASTROPHYSICS↗

Verification and Validation of Spectral Element Code for Supercritical CO2 Flow in Vertical Heated Tubes

The investigation of heat transfer in supercritical CO2 (sCO2) has garnered considerable attention in recent decades, given sCO2's potential as a promising working fluid for advanced power conversion cycles. Despite previous research efforts, there are still gaps in our understanding of sCO2 heat transfer, particularly in conditions associated with heat transfer deterioration. To delve into sCO2 heat transfer more comprehensively, we propose employing the high-fidelity computational fluid dynamics code NekRS to simulate sCO2 flow using the large eddy simulation technique. Through graphics processing unit acceleration, NekRS achieves a higher computational speed than traditional CPU-based systems. However, before using NekRS in practical applications involving sCO2, it is imperative to perform verification and validation. Here, this paper presents our efforts to verify and validate the NekRS code's capability for simulating sCO2 using heated vertical tubes, where heat transfer deterioration usually happens. To accommodate the unique properties of sCO2, we have modified the NekRS code by integrating third-party property modules, such as REFPROP and PROPATH. Our simulations are compared with experimental and numerical data from the literature, instilling confidence in leveraging NekRS for future engineering applications. Our simulations also reveal that the accuracy of the property module significantly impacts the results, with REFPROP outperforming PROPATH for sCO2 properties. Additionally, we observed that, depending on the flow direction, buoyancy can either enhance or suppress turbulence in sCO2 flow. In upward flow, under certain conditions, the suppressed turbulence leads to heat transfer deterioration, resulting in elevated wall temperatures.

NekRS↗

Celeritas R&D Report: Accelerating Geant4

Celeritas is a new Monte Carlo (MC) detector simulation code designed for computationally intensive applications on high-performance heterogeneous architectures. In the past two years Celeritas has advanced from prototyping a Graphics Processing Unit (GPU)-based single physics model in infinite medium to implementing a full set of electromagnetic (EM) physics processes in complex geometries. The current release of Celeritas, version 0.4, has incorporated full device-based navigation, an event loop in the presence of magnetic fields, and detector hit scoring. New functionality incorporates a scheduler to offload electromagnetic physics to the GPU within a Geant4-driven simulation, enabling straightforward integration of Celeritas into the high energy physics (HEP) experimental frameworks CMSSW and ATLAS FullSimLight. On the Perlmutter supercomputer, Celeritas performs EM physics between 3× and 18× faster using the machine’s Nvidia GPUs compared to using only CPUs, corresponding to an electrical power efficiency up to a factor of 5. When running a multithreaded Geant4 ATLAS test beam application with full hadronic physics, using Celeritas to accelerate the EM physics results in an overall simulation speedup of 1.7–2.2× on GPU and 1.2× on CPU. In a CMS test application using tt¯ events and the prototype Run 4 configuration, compared to Geant4 CPU, Celeritas with a Nvidia A100 improves overall throughput up to a factor of 2.7× but cannot be efficiently shared with more than 8 cores.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

TH-A-18C-09: Ultra-Fast Monte Carlo Simulation for Cone Beam CT Imaging of Brain Trauma

Purpose: Application of cone-beam CT (CBCT) to low-contrast soft tissue imaging, such as in detection of traumatic brain injury, is challenged by high levels of scatter. A fast, accurate scatter correction method based on Monte Carlo (MC) estimation is developed for application in high-quality CBCT imaging of acute brain injury. Methods: The correction involves MC scatter estimation executed on an NVIDIA GTX 780 GPU (MC-GPU), with baseline simulation speed of ~1e7 photons/sec. MC-GPU is accelerated by a novel, GPU-optimized implementation of variance reduction (VR) techniques (forced detection and photon splitting). The number of simulated tracks and projections is reduced for additional speed-up. Residual noise is removed and the missing scatter projections are estimated via kernel smoothing (KS) in projection plane and across gantry angles. The method is assessed using CBCT images of a head phantom presenting a realistic simulation of fresh intracranial hemorrhage (100 kVp, 180 mAs, 720 projections, source-detector distance 700 mm, source-axis distance 480 mm). Results: For a fixed run-time of ~1 sec/projection, GPU-optimized VR reduces the noise in MC-GPU scatter estimates by a factor of 4. For scatter correction, MC-GPU with VR is executed with 4-fold angular downsampling and 1e5 photons/projection, yielding 3.5 minute run-time per scan, and de-noised with optimized KS. Corrected CBCT images demonstrate uniformity improvement of 18 HU and contrast improvement of 26 HU compared to no correction, and a 52% increase in contrast-tonoise ratio in simulated hemorrhage compared to “oracle” constant fraction correction. Conclusion: Acceleration of MC-GPU achieved through GPU-optimized variance reduction and kernel smoothing yields an efficient (<5 min/scan) and accurate scatter correction that does not rely on additional hardware or simplifying assumptions about the scatter distribution. The method is undergoing implementation in a novel CBCT dedicated to brain trauma imaging at the point of care in sports and military applications. Research grant from Carestream Health. JY is an employee of Carestream Health.

60 APPLIED LIFE SCIENCES↗

On the integration of molecular dynamics, data science, and experiments for studying solvent effects on catalysis

Computational workflows that combine molecular dynamics (MD) simulations and emerging data-centric (DC) methods can accelerate the screening and analysis of solvent systems experimentally and computationally. Here, MD simulations provide atomic positions and velocities of reactant, solvent, and catalyst materials that can be manipulated into data representations that in turn can be used by DC techniques to conduct predictive modeling, feature extraction, and experimental design. For liquid-phase catalytic applications, emerging DC techniques such as Convolutional and Graph Neural Networks (CNN/GNN), Topological Data Analysis (TDA), and Active Learning (AL) can leverage MD and experimental data to quickly predict solvent effects on reaction outcomes. For instance, in recent studies, 3D solvent environments obtained with MD have been exploited by CNNs to predict experimental reaction rates for homogeneous acid-catalyzed lignocellulosic processes. In this perspective, we discuss basic principles of DC methods and how these can be combined with MD to enable high-throughput screening of solvent selection for diverse catalysis applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Vacuum acceleration of electrons in a dynamic laser pulse

A planar laser pulse propagating in vacuum can exhibit an extremely large ponderomotive force. This force, however, cannot impart net energy to an electron: As the pulse overtakes the electron, the initial impulse from its rising edge is completely undone by an equal and opposite impulse from its trailing edge. Here we show that planar-like “flying focus” pulses can break this symmetry, imparting relativistic energies to electrons. The intensity peak of a flying focus—a moving focal point resulting from a chirped laser pulse focused by a chromatic lens—can travel at any subluminal velocity, forward or backward. As a result, an electron can gain enough momentum in the rising edge of the intensity peak to outrun and avoid the trailing edge. Accelerating the intensity peak can further boost the momentum gain. Furthermore, theory and simulations demonstrate that these dynamic intensity peaks can backwards accelerate electrons to the MeV energies required for radiation and electron diffraction probes of high-energy-density materials.

43 PARTICLE ACCELERATORS↗

Quasi-monoenergetic ion acceleration and neutron generation from laser-driven transverse collisionless shocks

Experiments using the OMEGA EP laser system were performed to study collisionless shock acceleration of ions driven by the interaction of a relativistically intense laser pulse with underdense plasma. The energy spectrum of accelerated ions in the direction transverse to laser propagation is measured to have several narrow-band peaks which are quasi-monoenergetic with a typical energy bandwidth of 3%. In deuterium plasmas, these ions generate a significant number of fast fusion neutrons. Particle-in-cell simulations confirm that these ions were accelerated by the interaction of transverse shocks and that the appearance of quasi-monoenergetic spectral features depends on the growth of an ion-electron two-stream instability during the interaction.

Kordell, P. (ORCID:0000000321456317)↗

optimas v0.1

optimas is a Python library that can coordinate a large number of numerical simulations on high-performance computing resources, with the aim of optimizing a given simulation result. More specifically, this library is currently used for design optimization of laser-plasma particle accelerators. In this context, the performance of particle accelerator designs are often evaluated with large-scale simulation codes, and many separate simulations need to be run - with different design parameters - in order to find the most performant design. optimas facilitates this process by providing a convenient interface to advanced optimizers (e.g. Bayesian optimization), and by coordinating the execution of the different simulations on HPC resources. (This is done by leveraging the library libensemble.) Compared to other open-source optimization libraries (e.g. Ax), optimas is more tailored towards execution on DOE HPC resources (e.g. Perlmutter, Summit, etc.) and is specialized for the type of simulation codes and workflows that are used in the community of laser-plasma acceleration.

Lehe, Remi↗

Gauging the Impact of Cosmic-ray Feedback on the Stellar Initial Mass Function

Cosmic rays (CRs) drive ionization and influence gas dynamics in molecular clouds (MCs), potentially impacting the resulting star formation outcomes. Although previous simulations of individual star formation have included methods for CR transport (CRT), none have been large enough to resolve the stellar initial mass function (IMF). We conduct numerical simulations following the collapse of a 20,000 M ⊙ MC and the subsequent star formation including CRT, both with and without CRs accelerated by winds from the young massive stars, and compare against a non-CRT simulation. We show that after the first massive stars form, the cavity produced by feedback is more pronounced in the CRT simulations because the external CRs are able to propagate inward and compress the gas into higher-density structures. This increases the subsequent star formation in the cloud; by the end of the simulation, the star formation efficiency (SFE) in the CRT simulation including stellar wind CRs is 43% higher than the non-CRT simulation. The IMF is also top-heavy in comparison, with a slope above 1 M ⊙ that is shallower by ∼20%. These effects are also present in the simulation without wind-accelerated CRs, but they are not as pronounced; the SFE is only 16% higher than the non-CRT simulation, and the IMF high-mass slope is shallower by ∼10%. These results may explain some of the observed top-heavy IMFs, which typically occur in high-CR environments such as the Galactic center.

Fitz Axen, Margot [Oak Ridge National Laboratory (↗

HACC: Simulating sky surveys on state-of-the-art supercomputing architectures

Current and future surveys of large-scale cosmic structure are associated with a massive and complex datastream to study, characterize, and ultimately understand the physics behind the two major components of the ‘Dark Universe’, dark energy and dark matter. In addition, the surveys also probe primordial perturbations and carry out fundamental measurements, such as determining the sum of neutrino masses. Large-scale simulations of structure formation in the Universe play a critical role in the interpretation of the data and extraction of the physics of interest. Just as survey instruments continue to grow in size and complexity, so do the supercomputers that enable these simulations. In this paper, we report on HACC (Hardware/Hybrid Accelerated Cosmology Code), a recently developed and evolving cosmology N-body code framework, designed to run efficiently on diverse computing architectures and to scale to millions of cores and beyond. HACC can run on all current supercomputer architectures and supports a variety of programming models and algorithms. It has been demonstrated at scale on Cell- and GPU-accelerated systems, standard multi-core node clusters, and Blue Gene systems. HACC’s design allows for ease of portability, and at the same time, high levels of sustained performance on the fastest supercomputers available. We present a description of the design philosophy of HACC, the underlying algorithms and code structure, and outline implementation details for several specific architectures. We show selected accuracy and performance results from some of the largest high resolution cosmological simulations so far performed, including benchmarks evolving more than 3.6 trillion particles.

79 ASTRONOMY AND ASTROPHYSICS↗

Hydrostatic and Non‐Hydrostatic Baroclinic Instability in the Dynamical Core of the DOE Global Climate Model

Abstract The dynamical core of the Department of Energy global climate model is used to understand the role of non‐hydrostatic dynamics in the simulation of dry and moist baroclinic waves. To reduce computational cost, the Diabatic Acceleration and REscaling approach is adopted. Scale analysis and numerical simulations suggest that the model solution is not distorted by the change of spherical metric terms due to the change of Earth radius, neither are the inter‐scale interactions strongly altered as indicated by the analysis of spectral flux. Compared with hydrostatic simulations, the onset of baroclinic instability is delayed under non‐hydrostatic dynamics as the associated weaker vertical motions tend to increase the critical wavelength and narrow the range of waves that can be baroclinically unstable. During the development of baroclinic waves, non‐hydrostatic dynamics tends to induce vertical motions in the upper troposphere, accelerating the eastward propagation of upper‐level ridges through their impact on local vorticity tendency. These processes reduce the westward tilt of the vertical ridge axes and suppress the conversion of mean flow available potential energy to eddy kinetic energy, leading to weaker baroclinic eddies than in hydrostatic simulations. The contrasts between hydrostatic and non‐hydrostatic settings hold in supplemental experiments that vary the background flow Rossby number, the amount of water vapor content and vertical resolution. We also find that mesoscale and smaller‐scale activities can be considerably under‐represented when the vertical resolution is limited to that typically used in global climate models.

54 ENVIRONMENTAL SCIENCES↗

Numerical simulations of the ablative Rayleigh-Taylor instability in planar inertial-confinement-fusion targets using the FastRad3D code

The ablative Rayleigh-Taylor (RT) instability is a central issue in the performance of laser-accelerated inertial-confinement-fusion targets. Historically, the accurate numerical simulation of this instability has been a challenging task for many radiation hydrodynamics codes, particularly when it comes to capturing the ablatively stabilized region of the linear dispersion spectrum and modeling ab initio perturbations. Here, we present recent results from two-dimensional numerical simulations of the ablative RT instability in planar laser-ablated foils that were performed using the Eulerian code FastRad3D. Our study considers polystyrene, (cryogenic) deuterium-tritium, and beryllium target materials, quarter- and third-micron laser light, and low and high laser intensities. An initial single-mode surface perturbation is modeled in our simulations as a small modulation to the target mass density and the ablative RT growth-rate is calculated from the time history of areal-mass variations once the target reaches a steady-state acceleration. By performing a sequence of such simulations with different perturbation wavelengths, we generate a discrete dispersion spectrum for each of our examples and find that in all cases the linear RT growth-rate γ is well described by an expression of the form γ=α [kg/(1+ϵ kLm)]1/2−βkVa, where k is the perturbation wavenumber, g is the acceleration of the target, Lm is the minimum density scale-length, Va is the ablation velocity, and ϵ is either one or zero. The dimensionless coefficients α and β in the above formula depend on the particular target and laser parameters and are determined from two-dimensional simulation results through the use of a nonlinear curve-fitting procedure. While our findings are generally consistent with those of Betti et al. (Phys. Plasmas 5, 1446 (1998)), the ablative RT growth-rates predicted in this investigation are somewhat smaller than the values previously reported for the same target and laser parameters. It is speculated that differences in the equation-of-state and opacity models are largely responsible for the discrepancy. Resolution of this issue awaits the development of better experimental diagnostics capable of measuring small-wavelength (5–20 μm) perturbation growth due to the ablative RT instability in the linear regime.

Bates, J. W. (ORCID:0000000188087240)↗

GPU Acceleration of a Diagnostic Wind Solver

Reducing QUIC-Fire simulation runtimes is crucial in enabling simulation ensembles to guide science-driven prescribed fire planning in regions of complex terrain. Utilizing GPUs through OpenACC and Kokkos frameworks to accelerate generation of 3D windfields in QUIC-Fire would provide substantial speedup to the runtime of the code. Using GPUs for the Successive Over-Relaxation (SOR) algorithm utilized in QUIC-Fire will require deriving a ‘four colored’ version of the well explored ‘Red-Black’ SOR parallelization scheme. This effort could open the door for utilizing GPUs in other portions of the QUIC-Fire algorithm, increasing its viability in more complex and larger domains.

58 GEOSCIENCES↗