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At least 235 records · Page 13

GPU-accelerated red blood cells simulations with transport dissipative particle dynamics

Mesoscopic numerical simulations provide a unique approach for the quantification of the chemical influences on red blood cell functionalities. The transport Dissipative Particle Dynamics (tDPD) method can lead to such effective multiscale simulations due to its ability to simultaneously capture mesoscopic advection, diffusion, and reaction. In this paper, we present a GPU-accelerated red blood cell simulation package based on a tDPD adaptation of our red blood cell model, which can correctly recover the cell membrane viscosity, elasticity, bending stiffness, and cross-membrane chemical transport. The package essentially processes all computational workloads in parallel by GPU, and it incorporates multi-stream scheduling and non-blocking MPI communications to improve inter-node scalability. Our code is validated for accuracy and compared against the CPU counterpart for speed. Strong scaling and weak scaling are also presented to characterize scalability. We observe a speedup of on one GPU over all cores within a single node, and a weak scaling efficiency of across nodes. The program enables quick-turnaround and high-throughput numerical simulations for investigating chemical-driven red blood cell phenomena and disorders.

Computer Science↗

Low level coupling scheme between neutronics and thermal-hydraulics based on Anderson acceleration

The simulation of nuclear reactors is a multiphysics problem mixing, amongst other fields, neutron transport and thermal-hydraulics. The simplest and most used approach in multiphysics simulation is based on the coupling of single-physics codes in a black-box fashion. However, in order to reduce the computational time needed for such simulations, case-dependent optimizations are often required. In this paper, we aim at reducing the computational time required to solve a coupled neutronic/thermal-hydraulic steady-state problem on a simplified Pressurized Water Reactor (PWR) core. The idea is to deal simultaneously with the coupling of the energy groups of the deterministic neutronic description of the core and its thermal-hydraulic description with the Anderson acceleration. By doing so, the fission source terms are directly accelerated instead of the power map as done in most cases. The power method used to solve the k-eigenvalue problem inside the neutronic solver is thus accelerated with the Anderson acceleration. The numerical experimentations conducted in this work are performed using APOLLO3 and THEDI, and indicate that such coupling strategy improves the convergence rates in terms of number of iterations required and the total computational time. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Photodegradation accelerates ecosystem N cycling in a simulated California grassland

Abstract Photodegradation accelerates litter decay in arid grasslands where plant growth and litter decay are strongly controlled by precipitation and evapotranspiration. However, the effects of photodegradation on ecosystem C and N dynamics are not well understood. We examined the effects using an ecosystem biogeochemical model DayCent‐ UV with photodegradation explicitly represented and validated. The model was parameterized for a California grassland where photodegradation was documented to release CO 2 from litter. The model was parameterized with an inverse modeling approach using an extensive data set of six years of daily observed carbon and water gas exchange (gross primary production, ecosystem respiration, and evapotranspiration), soil temperature, and soil moisture. DayCent‐ UV correctly simulated the seasonal patterns of the observed gas exchange and closely simulated the inter‐annual variation in the gas exchange and biomass production rates. The simulations suggested that the inter‐annual variation is driven more by actual evapotranspiration than by precipitation because a large portion of precipitation is lost as runoff during wet years. Photodegradation in DayCent‐ UV accelerated C and N cycling, decreasing system C and N by 9.2% and 9.5% and C and N residence times by 9.4% and 18.2%. Accelerated N cycling made a greater fraction of system N available for plants, increasing net N mineralization and plant production for a given amount of system N. Increased net N mineralization was due to decreased immobilization by microbes in the aboveground organic matter. Photodegradation did not alter the control on plant production by evapotranspiration. These results suggest that at the ecosystem level, the central effect of photodegradation is to suppress microbial activity. We conclude that photodegradation accelerates N cycling at the expense of microbes in this grassland, making it more efficient in supporting plant growth for a given amount of N in the system.

54 ENVIRONMENTAL SCIENCES↗

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗

Impact of dynamics, entanglement and Markovian noise on the fidelity of few-qubit digital quantum simulation

Quantum algorithms have been proposed to accelerate the simulation of the chaotic dynamical systems that are ubiquitous in the physics of plasmas. Quantum computers without error correction might even use noise to their advantage to calculate the Lyapunov exponent by measuring the Loschmidt echo fidelity decay rate. For the first time, digital Hamiltonian simulations of the quantum sawtooth map, performed on the IBM-Q quantum hardware platform, show that the fidelity decay rate of a digital quantum simulation increases during the transition from dynamical localization to chaotic diffusion in the map. The observed error per CNOT gate increases by $1.5{\times }$ as the dynamics varies from localized to diffusive, while only changing the phases of virtual RZ gates and keeping the overall gate count constant. A gate-based Lindblad noise model that captures the effective change in relaxation and dephasing errors during gate operation qualitatively explains the effect of dynamics on fidelity as being due to the localization and entanglement of the states created. Specifically, highly delocalized states that are entangled with random phases show an increased sensitivity to dephasing and, on average, a similar sensitivity to relaxation as localized states. In contrast, delocalized unentangled states show an increased sensitivity to dephasing but a lower sensitivity to relaxation. This gate-based Lindblad model is shown to be a useful benchmarking tool by estimating the effective Lindblad coherence times during CNOT gates and finding a consistent $2\unicode{x2013}3{\times }$ shorter $T_2$ time than reported for idle qubits. Thus, the interplay of the dynamics of a simulation with the noise processes that are active can strongly influence the overall fidelity decay rate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Accelerated Fuel Qualification of Fast Modular Reactor Fuel in a Thermal Reactor: Modeling and Simulation Paired with Irradiation Testing

The accelerated fuel qualification (AFQ) methodology is applied by simulating accelerated fuel tests of the General Atomics Electromagnetic Systems’ fuel system for its 44-MW(electric) gas-cooled, fast-spectrum fast modular reactor (FMR). This fuel is comprised of UO 2 pellets in SiGA® cladding, a silicon carbide ceramic matrix composite. Fast reactors, like the FMR, offer many benefits, including high fuel utilization and flexibility, but may require a lengthy material design process if tests are performed using fast neutron irradiation alone. A thermal neutron irradiation can instead be used to rapidly test how well key components of the current material models extend to high burnup. Thermal neutrons produce a different radial power distribution within the pin than fast neutrons. However, the temperature and burnup values for the two neutron types are comparable, and the differences between the simulated fuel responses are relatively small, demonstrating the weak sensitivity of the physics-based fuel model calculations on the neutron type and the irradiation rate. Furthermore, the deformation of the SiGA cladding saturates after about 1 displacement per atom for both neutron spectra. In an accelerated fuel test, the irradiation time required to reach the target fuel burnup can be reduced by a factor of 3 by using a small rodlet with a 45% smaller pellet diameter while maintaining the same linear power. Therefore, the time for data collection up to high burnup can be significantly reduced while maintaining the same temperature profile, which largely determines the material response. Tests of fuel rodlets of standard and compact size will be carried out in the Idaho National Laboratory’s Advanced Test Reactor (ATR), including full size and compact rodlets with varying gap sizes. By applying physics-based mechanistic modeling and simulation in accordance with the AFQ methodology, this type of compact rodlet testing in a thermal test reactor captures the necessary phenomena to test fuel material models up to high burnup and to simulate the expected impact of fast neutron radiation on the fuel in FMR operations. Finally, this approach to testing fast reactor fuels in existing thermal test reactors, paired with advanced physics-based mechanistic modeling and simulation, is expected to be applicable to a range of advanced fuels and will decrease the overall fuel qualification timeframe from decades to years.

Advanced test reactor (ATR)↗

RE-INTEGRATE EMT Simulation Software: DAE Solvers and Automation

Existing electromagnetic transient (EMT) simulation tools face challenges in accelerating EMT simulations, especially for very large-scale power networks. To tackle this issue, next generation EMT simulation tools such as RE-INTEGRATE EMT are being researched upon. Such tools should be equipped with automation capabilities and advanced numerical differential-algebraic equation (DAE) solvers. In this paper, the DAE solvers incorporated within the RE-INTEGRATE EMT simulation tool are discussed. In particular, a modified ODEINT-based DAE solver and the ARKODE solver from SUN-DIALS are leveraged within RE-INTEGRATE EMT. In addition, the automation implemented within RE-INTEGRATE EMT to automate the DAE generation (replacing the need of manual discretization and assembling DAEs) is discussed. Different use cases were implemented using the RE-INTEGRATE EMT tool and were validated with respect to baseline simulations.

Marthi, Phani Ratna Vanamali [ORNL] (ORCID:0000000↗

Graphics processing unit accelerated three-dimensional model for the simulation of pulsed low-temperature plasmas

A 3-dimensional particle-in-cell/Monte Carlo collision simulation that is fully implemented on a graphics processing unit (GPU) is described and used to determine low-temperature plasma characteristics at high reduced electric field, E/n, in nitrogen gas. Details of implementation on the GPU using the NVIDIA Compute Unified Device Architecture framework are discussed with respect to efficient code execution. The software is capable of tracking around 10 × 10{sup 6} particles with dynamic weighting and a total mesh size larger than 10{sup 8} cells. Verification of the simulation is performed by comparing the electron energy distribution function and plasma transport parameters to known Boltzmann Equation (BE) solvers. Under the assumption of a uniform electric field and neglecting the build-up of positive ion space charge, the simulation agrees well with the BE solvers. The model is utilized to calculate plasma characteristics of a pulsed, parallel plate discharge. A photoionization model provides the simulation with additional electrons after the initial seeded electron density has drifted towards the anode. Comparison of the performance benefits between the GPU-implementation versus a CPU-implementation is considered, and a speed-up factor of 13 for a 3D relaxation Poisson solver is obtained. Furthermore, a factor 60 speed-up is realized for parallelization of the electron processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fully Implict Magneto-hydrodynamics Simulations of Coaxial Plasma Accelerators

The resistive Magneto-Hydrodynamic (MHD) model describes the behavior of a strongly ionized plasma in the presence of external electric and magnetic fields. We developed a fully implicit MHD simulation tool to solve the resistive MHD governing equations in the context of a cell-centered finite-volume scheme. The primary objective of this study is to use the fully-implicit algorithm to obtain insights into the plasma acceleration and jet formation processes in Coaxial Plasma accelerators; electromagnetic acceleration devices that utilize self-induced magnetic fields to accelerate thermal plasmas to large velocities. We also carry out plasma-surface simulations in order to study the impact interactions when these high velocity plasma jets impinge on target material surfaces. Scaling studies are carried out to establish some basic functional relationships between the target-stagnation conditions and the current discharged between the coaxial electrodes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

MO-DE-BRA-02: SIMAC: A Simulation Tool for Teaching Linear Accelerator Physics

Purpose: The first goal of this work is to develop software that can simulate the physics of linear accelerators (linac). The second goal is to show that this simulation tool is effective in teaching linac physics to medical physicists and linac service engineers. Methods: Linacs were modeled using analytical expressions that can correctly describe the physical response of a linac to parameter changes in real time. These expressions were programmed with a graphical user interface in order to produce an environment similar to that of linac service mode. The software, “SIMAC”, has been used as a learning aid in a professional development course 3 times (2014 – 2016) as well as in a physics graduate program. Exercises were developed to supplement the didactic components of the courses consisting of activites designed to reinforce the concepts of beam loading; the effect of steering coil currents on beam symmetry; and the relationship between beam energy and flatness. Results: SIMAC was used to teach 35 professionals (medical physicists; regulators; service engineers; 1 week course) as well as 20 graduate students (1 month project). In the student evaluations, 85% of the students rated the effectiveness of SIMAC as very good or outstanding, and 70% rated the software as the most effective part of the courses. Exercise results were collected showing that 100% of the students were able to use the software correctly. In exercises involving gross changes to linac operating points (i.e. energy changes) the majority of students were able to correctly perform these beam adjustments. Conclusion: Software simulation(SIMAC), can be used to effectively teach linac physics. In short courses, students were able to correctly make gross parameter adjustments that typically require much longer training times using conventional training methods.

60 APPLIED LIFE SCIENCES↗

Particle-in-cell simulation of laser wakefield accelerators with oblique lasers in quasicylindrical geometry

In the studies of optical injections in laser or beam-driven wakefield accelerators, there is a frequent demand for using obliquely propagating assistant lasers in particle-in-cell simulations. In conventional methods, this is only possible in either two- or three-dimensional Cartesian geometries, which have the drawbacks of either lack of fidelity for the actual situation or requiring a huge amount of computational resources. In this work, we develop a new method that uses an expression-defined oblique laser field to simulate such situations in quasicylindrical geometry particle-in-cell simulations, having the advantages of both maintaining good fidelity and saving computational resources. As an example, we use this method in the scissor-cross ionization injection scheme for the optimization of the injected beam quality. This method is widely applicable to particle injections with assistant lasers in wakefield accelerators, as long as the assistant lasers only influence the injected particles during the injection process. Published by the American Physical Society 2025

Ma, Minghao (ORCID:0009000602317775)↗

Large-eddy and unsteady RANS simulations of a shock-accelerated heavy gas cylinder

Two-dimensional numerical simulations of the Richtmyer–Meshkov unstable “shock-jet” problem are conducted using both large-eddy simulation (LES) and unsteady Reynolds-averaged Navier–Stokes (URANS) approaches in an arbitrary Lagrangian–Eulerian hydrodynamics code. Turbulence statistics are extracted from LES by running an ensemble of simulations with multimode perturbations to the initial conditions. Detailed grid convergence studies are conducted, and LES results are found to agree well with both experiment and high-order simulations conducted by Shankar et al. (Phys Fluids 23, 024102, 2011). URANS results using a k–L approach are found to be highly sensitive to initialization of the turbulence lengthscale L and to the time at which L becomes resolved on the computational mesh. As a result, it is observed that a gradient diffusion closure for turbulent species flux is a poor approximation at early times, and a new closure based on the mass-flux velocity is proposed for low-Reynolds-number mixing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Evaluation of Portable Acceleration Solutions for LArTPC Simulation Using Wire-Cell Toolkit

The Liquid Argon Time Projection Chamber (LArTPC) technology plays an essential role in many current and future neutrino experiments. Accurate and fast simulation is critical to developing efficient analysis algorithms and precise physics model projections. The speed of simulation becomes more important as Deep Learning algorithms are getting more widely used in LArTPC analysis and their training requires a large simulated dataset. Heterogeneous computing is an efficient way to delegate computationally intensive tasks to specialized hardware. However, as the landscape of compute accelerators quickly evolves, it becomes increasingly difficult to manually adapt the code to the latest hardware or software environments. A solution which is portable to multiple hardware architectures without substantially compromising performance would thus be very beneficial, especially for long-term projects such as the LArTPC simulations. In search of a portable, scalable and maintainable software solution for LArTPC simulations, we have started to explore high-level portable programming frameworks that support several hardware backends. In this paper, we present our experience porting the LArTPC simulation code in the Wire-Cell Toolkit to NVIDIA GPUs, first with the CUDA programming model and then with a portable library called Kokkos. Preliminary performance results on NVIDIA V100 GPUs and multi-core CPUs are presented, followed by a discussion of the factors affiecting the performance and plans for future improvements.

Yu, Haiwang↗

TeraChem protocol buffers ( TCPB ): Accelerating QM and QM/MM simulations with a client–server model

The routine use of electronic structures in many chemical simulation applications calls for efficient and easy ways to access electronic structure programs. Here, we describe how the graphics processing unit (GPU) accelerated electronic structure program TeraChem can be set up as an electronic structure server, to be easily accessed by third-party client programs. We exploit Google’s protocol buffer framework for data serialization and communication. The client interface, called TeraChem protocol buffers (TCPB), has been designed for ease of use and compatibility with multiple programming languages, such as C++, Fortran, and Python. To demonstrate the ease of coupling third-party programs with electronic structures using TCPB, we have incorporated the TCPB client into Amber for quantum mechanics/molecular mechanics (QM/MM) simulations. The TCPB interface saves time with GPU initialization and I/O operations, achieving a speedup of more than 2× compared to a prior file-based implementation for a QM region with ~250 basis functions. We demonstrate the practical application of TCPB by computing the free energy profile of p-hydroxybenzylidene-2,3-dimethylimidazolinone (p-HBDI - )—a model chromophore in green fluorescent proteins—on the first excited singlet state using Hamiltonian replica exchange for enhanced sampling. All calculations in this work have been performed with the non-commercial freely-available version of TeraChem, which is sufficient for many QM region sizes in common use.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulator for an Accelerator-Driven Subcritical Fissile Solution System

LANL has developed a process to generate a progressive family of system models for a fissile solution system. This family includes a dynamic system simulation comprised of coupled nonlinear differential equations describing the time evolution of the system. Neutron kinetics, radiolytic gas generation and transport, and core thermal hydraulics are included in the DSS. Extensions to explicit operation of cooling loops and radiolytic gas handling are embedded in these systems as is a stability model. The DSS may then be converted to an implementation in Visual Studio to provide a design team the ability to rapidly estimate system performance impacts from a variety of design decisions. This provides a method to assist in optimization of the system design. Once design has been generated in some detail the C++ version of the system model may then be implemented in a LabVIEW user interface to evaluate operator controls and instrumentation and operator recognition and response to off-normal events. Taken as a set of system models the DSS, Visual Studio, and LabVIEW progression provides a comprehensive set of design support tools.

42 ENGINEERING↗

The time dependent propensity function for acceleration of spatial stochastic simulation of reaction–diffusion systems

The inhomogeneous stochastic simulation algorithm (ISSA) is a fundamental method for spatial stochastic simulation. However, when diffusion events occur more frequently than reaction events, simulating the diffusion events by ISSA is quite costly. To reduce this cost, we propose to use the time dependent propensity function in each step. In this way we can avoid simulating individual diffusion events, and use the time interval between two adjacent reaction events as the simulation stepsize. We demonstrate that the new algorithm can achieve orders of magnitude efficiency gains over widely-used exact algorithms, scales well with increasing grid resolution, and maintains a high level of accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Simulation study of CO 2 laser-plasma interactions and self-modulated wakefield acceleration

3D numerical simulations of the interaction of a powerful CO 2 laser with hydrogen jets demonstrating the role of ionization on the characteristics of induced wakes are presented. Simulations using SPACE, a parallel relativistic Particle-in-Cell code, are performed in support of the plasma wakefield accelerator experiments being conducted at the Brookhaven National Laboratory (BNL) Accelerator Test Facility (ATF). A novelty of the SPACE code is its set of efficient atomic physics algorithms that compute ionization and recombination rates on the grid and transfer them to particles. The influence of ionization on the spectrum of pump laser has been studied for a range of gas densities.Simulations reproduce both Stokes and anti-Stokes shifts in the spectrum of pump laser, similar to those observed in experiments in the spectrum of probe. A good agreement has been achieved with the experiments on the effect of variation in gas density on Stokes/anti-Stokes intensity. In addition, self-injection and trapping of electrons into the self-modulated wakes has been observed and analyzed. Here, the experimentally validated code SPACE will be used for predictive simulations to guide future experiments at BNL ATF.

97 MATHEMATICS AND COMPUTING↗