RF plasma simulation of gas core reactor.
Induction plasma device of continuous operation to simulate NASA designed gas core space propulsion reactor
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Induction plasma device of continuous operation to simulate NASA designed gas core space propulsion reactor
Large-scale simulations or scientific experiments produce petabytes of data per run. This poses massive challenges for I/O and storage when scientific analysis workflows are run manually offline. Unsupervised deep learning-based techniques to extract patterns and non-linear relations from these large amounts of data provide a way to build scientific understanding from raw data, reducing the need for manual pre-selection of analysis steps, but require exascale compute and memory to process the full dataset available. In this paper, we demonstrate a heterogeneous streaming workflow in which plasma simulation data is streamed directly to a Machine Learning (ML) application training a model on the simulation data in-transit, completely circumventing the capacity-constrained filesystem bottleneck. This workflow employs openPMD to provide a high level interface to describe scientific data and also uses ADIOS2, to transfer volumes of data that exceed the capabilities of the filesystem. We employ experience replay to avoid catastrophic forgetting in learning from this non-steady state process in a continual manner and adapt it to improve model convergence while learning in-transit. As a proof-of-concept, we approach the ill-posed inverse problem of predicting particle dynamics from radiation in a particle-incell (PIConGPU) simulation of the Kelvin-Helmholtz instability (KHI). We detail hardware-software co-design challenges as we scale PIConGPU to full Frontier, the Top-1 system as of June 2024 Top500 list.
Induction plasma device of continuous operation to simulate NASA designed gas core space propulsion reactor
Quantum computers may one day enable the efficient simulation of strongly coupled plasmas that lie beyond the reach of classical computation in regimes where quantum effects are important and the scale separation is large. Here, in this article, we take a first step toward efficient simulation of quantum plasmas by demonstrating linear plasma wave propagation on a superconducting quantum chip. Using high-fidelity and highly expressive device-native gates, combined with an error-mitigation technique, we simulate the scattering of laser pulses from inhomogeneous plasmas. Our approach is made feasible by the identification of a suitable local spin model whose excitations mimic plasma waves, and whose circuit implementation requires a lower gate count than other proposed approaches that would require a future fault-tolerant quantum computer. This work opens avenues to study more complicated phenomena that cannot be simulated efficiently on classical computers, such as nonlinear quantum dynamics when strongly coupled plasmas are driven out of equilibrium.
The Darwin model of electromagnetic interaction is presented as a self-consistent theory, and is shown to be an excellent approximation to the Maxwell theory for slow electromagnetic waves. Since the fast waves of the Maxwell theory are absent, it is convenient for use in the computer simulation of the electromagnetic dynamics of nonrelativistic plasma.
Significant progress has been made in the design, construction and operation of induction coupled devices which simulate the open cycle Gas Core Nuclear Rocket. These devices incorporate solid feed of the plasma forming material (uranium and uranium simulating materials), permeable walls, seeding of the propellant, and transpiration cooled, choked flow nozzles. Operating parameters and performance data of devices employing these design features are discussed. A uranium plasma experiment is included. In addition, operating data of several devices which compare theoretical and actual performance at a variety of powers, pressures, frequencies, and sizes are discussed.
Self-consistent modeling of turbulence-driven transport is critical for optimizing confinement in magnetically confined fusion plasmas, such as tokamaks and stellarators. In particular, capturing the long-term co-evolution of turbulence, flow, and background plasma profiles remains computationally challenging. Direct numerical simulation of these multiscale, highly nonlinear processes is often demanding and impractical for real-time control or design optimization. To address this bottleneck, we investigate transformer-based neural operator partial differential equation surrogates for emulating the dynamics of drift-wave turbulence bifurcation mediated by zonal flows, using the modified Hasegawa–Wakatani (MHW) model as a prototypical system. We find that the finetuned neural operator model has excellent performance in capturing the multi-spatiotemporal-scales of MHW turbulence bifurcation and is robust to testing on rare and out-of-distribution dynamics. Specifically, we demonstrate that a single unified model accurately predicts both quasi-steady-state turbulence and a wide range of dynamical transition processes, such as nonlinear saturation, spontaneous suppression of turbulence, and the emergence of macroscopic zonal flows, over time horizons vastly exceeding the local turbulence correlation time. This computationally efficient approach establishes a strong foundation for fast, AI-based modeling of complex, multiscale phenomena in magnetized fusion plasmas.
Experiments were conducted to develop test configurations and technology necessary to simulate the thermal environment and fuel region expected to exist in in-reactor tests of small models of nuclear light bulb configurations. Particular emphasis was directed at rf plasma tests of approximately full-scale models of an in-reactor cell suitable for tests in Los Alamos Scientific Laboratory's Nuclear Furnace. The in-reactor tests will involve vortex-stabilized fissioning uranium plasmas of approximately 200-kW power, 500-atm pressure and equivalent black-body radiating temperatures between 3220 and 3510 K.
After decades of laboratory investigations that provided invaluable measurements and insight, the physics behind the transition from spot to plume modes in hollow cathodes remains one of the longest standing theoretical problems in electric propulsion. This has prohibited the development of ab initio models that allow for the prediction of the transition across different cathodes and operating conditions. Since the beginning of its development over a decade ago, simulations with the 2-D axisymmetric Orificed Cathode (OrCa2D) code have helped elucidate a wide range of processes in hollow cathode discharges. However, the code has never been used to investigate the onset of plume mode. We present results from the first OrCa2D simulations of a 25-A LaB6 cathode for a range of flow rates (5-20 sccm) in which transition from spot to plume modes is known to occur. The cathode in this study was one of the two technologies considered for the 12.5 kW Hall Effect Rocket with Magnetic Shielding (HERMeS) and operates nominally at 21 A and 14.8 sccm. The simulations capture the characteristic rise of the peak-to-peak amplitude in the keeper voltage oscillations and underscore the significance of the plume neutral gas in the transition. The plasma inside the cathode is found to be relatively quiescent throughout the transition, in agreement with previous experimental observations. The computed keeper voltage fluctuations at low flow rates (<8 sccm) are found to be driven by oscillations of the same frequency in the plasma plume with the following main characteristics: (1) they are of low frequency (<10 kHz), and associated with small longitudinal motion in the direction of the applied magnetic field, (2) they occur in a region of the plume where the neutral gas provided by the cathode has been fully depleted, and (3) they have a (small) wave velocity of about 100 m/s, which is at least ~10 smaller than the drift, thermal and acoustic speeds of the ions. At 8 sccm, when the transition to the large-amplitude oscillations begins, the ionization frequency in the neutral-depleted plume region ranges ~2-100 kHz. The frequency of the oscillations in the plasma (and keeper voltage) is found to be equal to the ionization frequency (~5 kHz) at the center of this region. The findings suggest that the transition to plume mode is driven by ionization processes in the near-plume of the cathode, in line with previous conjectures that were based solely on laboratory observations.
Numerical simulations have been conducted to assess the erosion rates at the pole covers of the magnetically shielded miniature (MaSMi) Hall thruster. MaSMi is part of the Ascendant Sub-kW Transcelestial Electric Propulsion System (ASTRAEUS), whose design requirements demand a xenon throughput of 100 kg, thus enabling deep space missions using SmallSats. The results of our simulations show that the proposed thickness of the graphite pole covers will not be completely eroded at end of life. We find that the erosion rates are larger near the corners of the covers, which are directly exposed to the plasma in the acceleration channel.
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The theory of Eldridge and Feix (1962) is presently applied to characterize the rate of heat flow between two one-dimensional particle species. Formulas derived assuming initial Maxwellian distributions, while complex, are judged applicable to simulators. Tests of the theory by simulations using Langdon and Birdsall's (1985) standard code yield results which indicate that heat flow between species may become rapid when the actual (not necessarily the intended) temperatures differ: thereby presenting a substantial hazard.
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A cylindrical particle-in-cell (PIC) plasma simulation code applicable to plasma densities encountered in low Earth orbit (LEO) is described. The simulated geometries include that of a plain disk and a disk surrounded by a dielectric. Both configurations are mounted upon a ground plate in contact with a plasma environment. Techniques allowing simulation of dielectric charging using PIC time scales are discussed. Current versus voltage characteristic curves are calculated and the results are compared to experimental data.