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Results from kinetic plasma simulation on Grizzly--IC Project: w17_eclosure [Slides]
Abstract not provided.
A pairwise nuclear fusion algorithm for weighted particle-in-cell plasma simulations
In this work, a pairwise nuclear fusion algorithm for arbitrarily weighted macroparticles in a particle-in-cell simulation is described. The method is benchmarked in situations with like-particles, D(d,n) 3 He, unlike-particles, D(t,n) 4 He, thermonuclear plasmas, beam-target fusion, and for large difference in macroparticle weights. Studies of the required number of macroparticles in thermonuclear plasmas show that 100–1000 macroparticles are required to achieve repeatability of yields around 10%, likewise 10 4 –10 5 for 1%, depending on the fusion interaction and ion temperature.
Challenges and opportunities in verification and validation of low temperature plasma simulations and experiments
This paper describes the verification and validation (V&V) framework developed for the stochastic Particle-in-Cell, Direct Simulation Monte Carlo code Aleph. An ideal framework for V&V from the viewpoint of the authors is described where a physics problem is defined, and relevant physics models and parameters to the defined problem are assessed and captured in a Phenomena Identification and Ranking Table (PIRT). Furthermore, numerous V&V examples guided by the PIRT for a simple gas discharge are shown to demonstrate the V&V process applied to a real-world simulation tool with the overall goal to demonstrably increase the confidence in the results for the simulation tool and its predictive capability. Although many examples are provided here to demonstrate elements of the framework, the primary goal of this work is to introduce this framework and not to provide a fully complete implementation, which would be a much longer document. Comparisons and contrasts are made to more usual approaches to V&V, and techniques new to the low-temperature plasma community are introduced. Specific challenges relating to the sufficiency of available data (e.g., cross sections), the limits of ad hoc validation approaches, the additional difficulty of utilizing a stochastic simulation tool, and the extreme cost of formal validation are discussed.
A corrected method for Coulomb scattering in arbitrarily weighted particle-in-cell plasma simulations
A physically and statistically accurate method to perform binary, pairwise Coulomb collisions for arbitrarily-weighted macroparticles in particle-in-cell simulations is described. The method is shown to conserve global energy and momentum on average and to produce physically accurate scattering frequencies. This is justified using the statistically expected values of the method and through a series of numerical tests showing that the method is valid independently of macroparticle weight. This novel method is required due to an error in previous work on binary scattering, initially by Nanbu and Yonemura [J. Comp. Phys. 145, 639 (1998)] and applied to subsequent work, that causes inaccuracies in the scattering frequencies for unequally weighted simulations; a problem that occurs both for scattering within the group and between different groups.
ContourNet: Salient Local Contour Identification for Blob Detection in Fusion Plasma Simulation Data
We present ContourNet, a deep learning approach to identify salient local isocontours as blobs in large-scale 5D gyrokinetic tokamak simulation data. Blobs-regions of high turbulence that run along the edge wall down toward the diverter and can damage the tokamak-are non-well-defined features but have been empirically localized by isocontours in 2D normalized fluctuating density fields. The key of our study is to train ContourNet to follow the empirical rules to detect blobs over the time-varying simulation data. The architecture of ContourNet is a convolutional neural segmentation network: the inputs are the density field and a rasterized isocontour; the output is a set of isocontour encircling blobs. At the training stage, we feed the network with manually identified isocontours and propagated labels. At the inference stage, we extract isocontours from the segmented blob regions. Results show that our approach can achieve both high accuracy and performance, which enables scientists to understand the blob dynamics influencing the confinement of the plasma.
Enabling Scalable Multifluid Plasma Simulations through Block Preconditioning.
Abstract not provided.
A block-structured nonuniform meshing technique for reducing the degrees-of-freedom in hybrid particle-in-cell plasma simulations
Not Available
Integrating batched sparse iterative solvers for the collision operator in fusion plasma simulations on GPUs
Not Available
Performance of the lithium metal infused trenches in the magnum PSI linear plasma simulator
Not Available
Automatic Particle Trajectory Classification in Plasma Simulations
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Incorporating Radiation Transport into Particle-Based Plasma Simulations.
Abstract not provided.
Optimizing Large-Scale Plasma Simulations on Persistent Memory-based Heterogeneous Memory with Effective Data Placement Across Memory Hierarchy
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A Kinetic Vlasov Model for Plasma Simulation Using Discontinuous Galerkin Method on Many-Core Architectures
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Noise and error analysis and optimization in particle-based kinetic plasma simulations.
Abstract not provided.