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Using ai-GCMC simulations,operandoWAXS, and kinetics analysis, we found that the high-rate performance of Sb as an alloy anode in Na-ion batteries is due to the presence of an amorphous intermediate phase formed during sodiation and desodiation.
In this work, a generalized linear dispersion relation of electromagnetic slab universal modes is derived, taking into account arbitrary ion charge state, electron finite Larmor radius (FLR) effects, and Debye shielding effects. As a consequence, it provides more accurate predictions and is applicable to a wider range of plasmas. We find that electron FLR effects have a weakly stabilizing effect on the slab universal instability in electron–ion plasma, while Debye shielding strongly stabilizes this instability when λ D approaches ρ i (λ D is the Debye length and ρi is the ion gyroradius). In particular, we examine the stability criterion for this instability in electron–positron pair plasmas and find that the instability persists in this simplest plasma system as long as the pair plasma number density exceeds the critical value n c = B 2 /(8πm e c 2 ).
Symbolic regression (SR) with a multi-gene genetic program has been used to elucidate new empirical equations describing diffusion in Lennard-Jones (LJ) fluids. Some examples include equations to predict self-diffusion in pure LJ fluids and equations describing the finite-size correction for self-diffusion in binary LJ fluids. The performance of the SR-obtained equations was compared to that of both the existing empirical equations in the literature and to the results from artificial neural net (ANN) models recently reported. It is found that the SR equations have improved predictive performance in comparison to the existing empirical equations, even though employing a smaller number of adjustable parameters, but show an overall reduced performance in comparison to more extensive ANNs.
The triangular mesh-based gyrokinetic scheme enables comprehensive axis-to-edge studies across the entire plasma volume. Our approach employs triangular finite elements with first-derivative continuity (C1), building on previous work to facilitate gyrokinetic simulations. Additionally, we have adopted the mixed variable/pullback scheme for gyrokinetic electromagnetic particle simulations. The filter-free treatment in the poloidal cross-section with triangular meshes introduces unique features and challenges compared to previous treatments using structured meshes. Our implementation has been validated through benchmarks using ITPA-toroidicity-induced Alfvén eigenmode parameters, showing its capability in moderate to small electron skin depth regimes. Additional examinations using experimental parameters confirm its applicability to realistic plasma conditions.
Abstract Magnetized high energy density physics offers new opportunities for observing magnetic field-related physics for the first time in the laser–plasma context. We focus on one such phenomenon, which is the ability of a laser-irradiated magnetized plasma to amplify a seed magnetic field. We performed a series of fully kinetic 3D simulations of magnetic field amplification by a picosecond-scale relativistic laser pulse of intensity 4.2 × 10 18 W cm −2 incident on a thin overdense target. We observe axial magnetic field amplification from an initial 0.1 kT seed to 1.5 kT over a volume of several cubic microns, persisting hundreds of femtoseconds longer than the laser pulse duration. The magnetic field amplification is driven by electrons in the return current gaining favorable orbital angular momentum from the seed magnetic field. This mechanism is robust to laser polarization and delivers order-of-magnitude amplification over a range of simulation parameters.
Dedicated electron heat transport experiments have been carried out in L- and H-mode Deuterium plasmas of the JET-ILW tokamak to identify the amount of electron heat carried by electron-scale electron temperature gradient (ETG) modes. Ion cyclotron resonance heating at different positions has been used to probe the response of the electron temperature inverse gradient length R/L Te to changes in electron heat flux qe, while different amounts of neutral beam heating allowed to scan the ratio of ion to electron temperature T e /T i , which is a key parameter for the onset of ETGs. Results indicate a steepening of the normalized qe vs R/L Te curve above R/LT e ~ 8 for T e /T i ≤ 1, suggestive of the ETG onset. Ion-scale gyro-kinetic (GK) simulations match the ion heat flux and the low-R/L Te part of the qe curve, but do not reproduce such steepening at high R/L Te . Multi-scale GK simulations covering both ion and electron scales and including one impurity bundling light and heavy species indicate an ETG contribution only for R/L Te values larger than the experimental ones. Sensitivity studies of such result are difficult to achieve due to limitation in numerical resources. The quasi-linear TGLF model has been used for sensitivity studies. With the same bundled impurity as the GK multi-scale, TGLF shows the qe steepening at much larger R/L Te values than in experiment, but when using the real mix of light impurities neglecting the heavy impurities, TGLF gets closer to the experimental results. Profile simulations with TGLF including both light and heavy impurities show over-prediction of T e profiles and in some cases also of density, but good T i predictions, confirming issues with the model electron stiffness for these plasmas.
The interaction of Alfvén eigenmodes (AEs) and energetic particles is one of many important factors determining the success of future tokamaks. In JET, eight in-vessel antennas were installed to actively probe stable AEs with frequencies ranging 25–250 kHz and toroidal mode numbers |n| < 20. During the 2019–2020 deuterium campaign, almost 7500 resonances and their frequencies f 0 , net damping rates γ < 0, and toroidal mode numbers were measured in almost 800 plasma discharges. From a statistical analysis of this database, continuum and radiative damping are inferred to increase with edge safety factor, edge magnetic shear, and when including non-ideal effects. Both stable AE observations and their associated damping rates are found to decrease with |n|. Active antenna excitation is also found to be ineffective in H-mode as opposed to L-mode; this is likely due to the increased edge density gradient’s effect on accessibility and ELM-related noise’s impact on mode identification. A novel measurement is reported of a marginally stable, edge-localized ellipticity-induced AE probed by the antennas during high-power auxiliary heating (ion cyclotron resonance heating and neutral beam injection) up to 25 MW. NOVA-K kinetic-MHD simulations show good agreement with experimental measurements of f 0 , γ, and n, indicating the dominance of continuum and electron Landau damping in this case. Similar experimental and computational studies are planned for the recent hydrogen and ongoing tritium campaigns, in preparation for the upcoming DT campaign.
Gyrokinetic and kinetic-MHD simulations are performed for the fishbone instability in the DIII-D discharge #178631, chosen for validation of first-principles simulations to predict the energetic particle (EP) transport in an ITER prefusion baseline scenario. Fishbone modes are found to generate zonal flows, which dominate the fishbone saturation. The underlying mechanisms of the two-way fishbone-zonal flows nonlinear interplay are discussed in details. Numerical and analytical analyses identify the fishbone-induced EP redistribution as the dominant generation mechanism for zonal flows. The zonal flows modify the nonlinear dynamics of phase space zonal structures, which reduces the amount of EPs able to resonate with the mode, leading to an early fishbone saturation. Simulation results including zonal flows agree quantitatively with DIII-D experimental measurements of the fishbone saturation amplitude and EP transport, supporting this novel saturation mechanism by self- generated zonal flows. Moreover, the wave-particle mode-locking mechanism is shown to determine quantitatively the fishbone frequency down-chirping, as evident in GTC simulation results in agreement with predictions from analytical theory. Finally, the
fishbone-induced zonal flows are possibly responsible for the formation of an ion-ITB in the DIII-D discharge. Based on the low EP transport and the large zonal flow shearing rates associated with the fishbone instability in gyrokinetic simulations of the ITER scenario, it is conjectured that high performance scenarios could be designed in ITER burning plasmas through fishbone-induced ITBs.
We review the physics of energetic particles (EPs) in magnetically confined burning fusion plasmas with focus on advances since the last update of the ITER Physics Basis (Fasoli et al 2007 Nucl. Fusion 47 S264). Topics include basic EP physics, EP generation, diagnostics of EPs and instabilities, the interaction of EPs and thermal plasma instabilities, EP-driven instabilities, energetic particle modes (EPMs), and turbulence, linear and nonlinear stability and simulation of EP-driven instabilities and EPMs, 3D effects, scenario optimization strategies based on EP phase-space control, EPs in reduced field scenarios in ITER before DT, and the physics of runaway electrons. We describe the simulation and modeling of EPs in fusion plasmas, including instability drive and damping as well as EP transport, with a range of approaches from first-principles to reduced models, including gyrokinetic simulations, kinetic-MHD models, gyrofluid models, reduced models, and semi-analytical approaches.
Fast ion phase-space flow, driven by Alfven eigenmodes (AEs), is measured by an imaging neutral particle analyzer in the DIII-D tokamak. The flow firstly appears near the minimum safety factor at the injection energy of neutral beams, and then moves radially inward and outward by gaining and losing energy, respectively. The flow trajectories in phase space align well with the intersection lines of the constant magnetic moment surfaces and constant E – (ω/n)P ζ surfaces, where E, P ζ are energy and toroidal canonical momentum of ions; ω and n are angular frequencies and toroidal mode numbers of AEs. It is found that the flow is so destructive that the thermalization of fast ions is no longer observed in regions of strong interaction. Here, the measured phase-space flow is consistent with nonlinear hybrid kinetic-magnetohydrodynamics simulation. Calculations of the relatively narrow phase-space islands reveal that fast ions must transition between different flow trajectories to experience large-scale phase-space transport.
The suppression and excitation of Alfvén eigenmodes have been experimentally obtained, for the first time, by means of externally applied 3D perturbative fields with different spatial spectra in a tokamak plasma. The applied perturbation causes an internal fast-ion redistribution that modifies the phase-space gradients responsible for driving the modes, determining, ultimately their existence. Hybrid kinetic-magnetohydrodynamic simulations reveal an edge resonant transport layer activated by the 3D perturbative field as the responsible mechanism for the fast-ion redistribution. Finally, the results presented here may help to control fast-ion driven Alfvénic instabilities in future burning plasmas with a significant fusion born alpha particle population.
Particle-in-cell (PIC) algorithms are widely used for the simulation of kinetic plasmas. PIC algorithms account for the interaction between charged particles in a plasma and the electromagnetic field in ambient space, including self-field interactions. The objective of this article is to study the error in charged particle trajectories present in finite-element (FE)-based PIC algorithms on unstructured meshes. We study how the trajectory error behaves according to the FE mesh resolution and the matrix solver employed in the FE algorithm. The study is performed by considering a trajectory established by a parabolic electric potential and an axial magnetic force acting on the charged particle. Under a proper choice combination of electric and magnetic field parameters, the 2-D particle trajectories comprise closed orbits. Numerical errors cause small perturbations on the trajectories, with cumulative effects. As a result, the resulting orbital trajectories exhibit distortions including spurious apsidal precession. These distortions provide a clear imprint of the numerical error. Here, we also study the numerical error in a quantitative fashion by computing the distance norm between the trajectories obtained by the exact fields and numerical fields.
Growing environmental concerns and demand for a better fuel economy are driving forces that motivate the research for more advanced engines. Multi-mode combustion strategies have gained attention for their potential to provide high thermal efficiency and low emissions for light-duty applications. These strategies target optimizing the engine performance by correlating different combustion modes to load operating conditions. The extension from boosted spark ignition (SI) mode at high loads to advanced compression ignition (ACI) mode at low loads can be achieved by increasing the compression ratio and utilizing intake air heating. Further, in order to enable an accurate control of intake charge condition for ACI mode and rapid mode-switches, it is essential to gain fundamental insights into the autoignition process. Within the scope of ACI, homogeneous charge compression ignition (HCCI) mode is of significant interest. It is known for its potential benefits, operation at low fuel consumption, low NOx, and particulate matter (PM) emissions. In the present work, a virtual Cooperative Fuel Research (CFR) engine model is used to analyze fuel effects on ACI combustion. In particular, the effect of fuel octane sensitivity (S) (at constant Research Octane Number (RON)) on autoignition propensity is assessed under beyond-RON (BRON) and beyond-MON (BMON) ACI conditions. The three-dimensional CFR engine computational fluid dynamics (CFD) model employs a finite-rate chemistry approach with a multi-zone binning strategy to capture autoignition. Two binary blends with Research Octane Number (RON) of 90 are chosen for this study: primary reference fuel (PRF) with S = 0 and toluene–heptane (TH) blend with S = 10.8, representing paraffinic and aromatic gasoline surrogates. Reduced mechanisms for these blends are generated from a detailed gasoline surrogate kinetic mechanism. Simulation results with the reduced mechanisms are validated against experimental data from an in-house CFR engine, with respect to in-cylinder pressure, heat release rate, and combustion phasing. Thereafter, the sensitivity of combustion behavior to ACI operating condition (BRON versus BMON), air-fuel ratio (λ = 2 and 3), and engine speed (600 and 900 rpm) is analyzed for both fuels. It is shown that the sensitivity of a fuel’s autoignition characteristics to λ and engine speed significantly differs at BRON and BMON conditions. Moreover, this sensitivity is found to vary among fuels, despite the same RON. It is also observed that the presence of low-temperature heat release (LTHR) under BRON condition leads to more sequential autoignition and longer combustion duration than BMON condition. Finally, the study indicates that the octane index (OI) fails to capture the trend in the variation of autoignition propensity with S under the BMON condition.
A microscale model is presented in this study to simulate electrode kinetics of the oxygen electrode in a solid oxide electrolyzer cell (SOEC). Two mixed ionic/electronic conducting structures are examined for the oxygen producing electrode in this work: single layer porous lanthanum strontium cobalt ferrite (LSCF), and bilayer LSCF/SCT (strontium cobalt tantalum oxide) structures. A yttrium-stabilized zirconia (YSZ) electrolyte separates the hydrogen and oxygen electrodes, as well as a gadolinium doped-ceria (GDC) buffer layer on the oxygen electrode side. Electrochemical reactions occurring at the two-phase boundaries (2PBs) and three-phase boundaries (3PBs) of single-layer LSCF and bilayer LSCF/SCT oxygen electrodes are modeled under various SOEC voltages with lattice oxygen stoichiometry as the key output. The results reveal that there exists a competition in electrode kinetics between 2PBs and 3PBs, but 3PBs are the primary reactive sites for single-layer LSCF oxygen electrode under high voltages. These locations experience the greatest oxygen stoichiometry variations and are therefore the most likely locations for dimensional changes. By applying an active SCT layer over LSCF, the 2PBs become activated to compete with the 3PBs, thus alleviating oxygen stoichiometry variations and reducing the likelihood of dimensional change. This strategy could reduce lattice structural expansion, proving to be valuable for electrode-electrolyte delamination prevention and will be the focus of future work.
Collisions of supersonic flows occur frequently in astrophysics, and the resulting shock waves are responsible for the properties of many astrophysical phenomena, such as supernova remnants, Gamma Ray Bursts and jets from Active Galactic Nuclei. Because of the low density of astrophysical plasmas, the mean free path due to Coulomb collisions is typically very large; therefore, most shock waves in astrophysics are “collisionless” and form due to plasma instabilities and self-generated magnetic fields. Laboratory experiments at DOE high energy density (HED) facilities can achieve the conditions necessary for the formation of collisionless shocks and will provide a unique avenue for studying the nonlinear physics of shock waves. This project investigates the parameters and experimental configurations needed for the creation of collisionless shocks in the laboratory experiments. This study is being performed with state of the art 3D kinetic plasma simulations. Recent advances in ab-initio particle-in-cell (PIC) simulations of astrophysical shocks enable us to simulate shock formation on timescales and in geometries relevant to the laboratory experiments. The main goal of the proposal is to ascertain which signatures of shock physics can be extracted from the realistic experiments, accounting for limitations imposed by finite spatial and time scales in the lab. To aid the interpretation of current and future experimental data, PIC simulation data have been analyzed using the same diagnostic techniques as used in the laboratory, such as proton radiography and neutronics, to unambiguously predict the experimental signatures of relevant collisionless shock phenomena.
This project seeks to develop novel x-ray sources based on high-power short-pulse lasers with unique advantages, including small spot size, flexible configuration, and tailorable spectra. Kinetic plasma simulations using the VPIC particle in cell code will be performed to support the R&D goals of this project. If successful, this effort will allow LANL to deploy flexible, compact x-ray sources for static tomographic radiography and dynamic multi-axis radiography at our firing sites and facilities such as pRad and U1a. The higher resolution, shorter pulse duration, and tunability of our proposed sources will enable new applications in the weapons program and broader scientific community. This effort advances the LANL FY22 Strategic Investment Plan priority of “[r]adiographic tools for dynamic and static imaging with improved spatial and temporal resolution, sensitivity, and dose.”
Understanding techniques to strengthen the nuclear safeguards regime is crucial in preventing nuclear proliferation due to recent advancements in the nuclear energy industry such as Generation IV reactors and microreactors. Prior to the construction of a nuclear power plant, it is necessary to understand the proliferation potential of the plant's reactor. Digital twins serve as a unique solution to recognizing reactor behavior indicative of nuclear proliferation. A digital twin is defined as a virtual model that works in unison to represent a physical asset, with a transference of data between the virtual and physical assets [1]. This work serves as validation for training a digital twin on synthetic data fabricated via means of Serpent reactor physics and point kinetics equations simulations. In this case this work is based on parameters of Idaho State University's AGN-201 reactor. The synthetic data can then be utilized to train machine learning models in the future to further investigate the utility of these methods. The accuracy of the predicted data is measured against real operational data to verify the reliability of the synthetic data creation methods and decide whether these methods should be used in the future to inform inspectors of a reactor's proliferation potential.