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At least 235 records · Page 13

COMPUTATIONAL MODELING OF IGNITION AND PREMIXED FLAME PROPAGATION INITIATED BY A PRE-CHAMBER TURBULENT JET

Addressing the pressing need for reduced carbon emissions, Turbulent Jet Ignition (TJI) emerges as a promising technology for ultra-lean combustion, offering enhanced thermal efficiencies and minimized cyclic variability in spark-ignited engines. To facilitate rapid testing and integration of this technology, a robust computational modeling framework is crucial. This study delves into the predictive capabilities of computational models for main-chamber ignition and premixed flame propagation using a single-cycle TJI rig measured by Biswas et al. (Applied Thermal Engineering, vol 106, 2016). Employing an open-source compressible flow simulation solver with Large Eddy Simulation (LES) for turbulence modeling, the investigation integrates the conventional Laminar Finite Rate Chemistry (LFRC) model alongside the transported Probability Density Method (PDF) for turbulence-chemistry interaction. A fully-consistent Eulerian Monte-Carlo Fields (EMCF) method is utilized to approximate the transported PDF, while Interaction by Exchange with Mean is employed to close micro-mixing terms in stochastic differential equations. A reduced chemical reaction mechanism with 21 species and 84 reactions (DRM-19) is used for solving chemical kinetics, and a double Gaussian energy deposition model is used to approximate the spark ignition in the pre-chamber. An unstructured O-grid mesh with 0.3 million cells in the prechamber and 1 million cells in the main chamber is employed. Results are divided into two phases: pre-chamber initialization and full TJI simulations. Validation of the predicted pre-chamber flame propagation and the lean ignition in the main-chamber is carried out by using available experimental data. Under quiescent conditions, both the LFRC and transported PDF methods largely underestimate the flame speed and subsequent pressure growth in the pre-chamber. A linear momentum forcing technique is applied to investigate the impact of initial turbulence in the pre-chamber, demonstrating a notable influence on flame propagation. Fine-tuning of the forcing coefficient reproduces the sudden pressure growth observed in the experiment. The experimentally validated pre-chamber simulation serves as the initial condition for the full TJI simulations. It is found that the LFRC model fails to predict lean-ignition in the main-chamber, resulting in a misfiring event. Incorporation of turbulence-chemistry interaction using the transported PDF method substantially improves the prediction of the ignition event in the main-chamber, achieving fair qualitative agreement and quantitative validation of combustion parameters within ±10% of the reported experimental data. The rich simulation results consisting of a full set of statistical description of the thermo-chemical states enable us to gain deep insights into the ignition mechanisms in the main chamber, which is limited when done experimentally. A novel dual ignition phenomenon is revealed in the TJI rig for the first time. Initially, a primary ignition kernel is formed at a downstream location which eventually detaches from the main jet. As the jet momentum decreases, a secondary ignition event follows, this time at a more upstream location which eventually combines with the primary ignition kernel to form a single connected flame front. Investigation of these ignition sequences in chemical composition space reveal distinct differences between the two. The primary ignition event in the main-chamber is followed by a large concentration of active radicals from the pre-chamber jet, accelerating the chain-branching steps, characterizing what has been referred to as flame ignition. In contrast, the secondary ignition occurs in the absence of active radicals in the pre-chamber jet, hence characterized as jet ignition. Further analysis of the effect of pre-chamber jet characteristics on lean ignition in the main-chamber is conducted by setting up cases with different initial pressure ratios (por) between the two chambers, a non-dimensional parameter, ranging from 1.2 to 3.2. As the initial pressure ratio increases, jet momentum increases, with dual ignition observed in cases above por= 2.2. Case with por= 3.2 lead to misfiring. The effect of ignition sequence on global combustion characteristics of TJI is analyzed. Dual ignition events lead to non-monotonicity in combustion characteristics such as global reaction progress variable, flame penetration, and global heat release rate. In dual ignition events, although the rate of fuel consumption and global heat release rate is initially lower, the secondary ignition leads to a sudden increase in flame surface area, resulting in a sudden jump and promoting the overall performance of the TJI system.

42 ENGINEERING↗

Numerical and experimental investigation of the flame kernel growth in a methane/air mixture near the lean flammability limit

Lean combustion has the potential to improve the thermal efficiency of spark-ignition engines, but it faces the significant challenge of increased cycle-to-cycle variation due to low mixture reactivity and unstable flame dynamics. Computational fluid dynamics (CFD) employing predictive models can guide engine design and optimize operating strategies for lean combustion. However, ignition and combustion models have rarely been validated at fuel-lean conditions, and a fundamental understanding of the early flame kernel growth process is also lacking for a successful sub-model development. Here, the present study develops a numerical simulation framework used to investigate early flame kernel growth in methane/air mixtures. A nanosecond-pulsed discharge (NPD) approach is employed to effectively decouple the flame kernel growth from the electrical discharge due to their difference in timescales, and equivalence ratios near the experimentally measured lean flammability limit (LFL) are selected to focus on challenging mixture conditions. Three numerical investigations, such as the choice of turbulence modeling, grid size, and grid control strategies, are examined to match both LFL and flame kernel structure measured from experiments. It is demonstrated that a quasi-direct numerical simulation (QDNS) with a fixed grid embedding of 10 μm can predict the LFL as φ CFD =0.61 and match the displacement speed of the kernel’s boundary marked in schlieren images. To predict the LFL and flame kernel shape, a fine grid (Δ≤12.5 μm) is needed to capture the consumption of formaldehyde (CH 2 O) in kernel’s reaction branches attached to the anode, and adaptive mesh refinement is replaced with the fixed embedding due to loss of simulation accuracy. Also, it is found that a large-eddy simulation (LES) using the Dynamic Structure model is not suitable for the NPD-induced flame kernel simulation because artificial sub-grid turbulent kinetic energy induced by shock dynamics alters the flow velocity calculation, resulting in divergence of LES from QDNS. Lastly, the simulation well matches the experimental data for the flame kernel evolution in three mixture conditions (φ = 0.7, 0.61, 0.55), showing toroidal flame kernel expansion and flame kernel growth/extinction.

33 ADVANCED PROPULSION SYSTEMS↗

Turbulent Acceleration of Interstellar Pickup Ions at the Heliospheric Termination Shock Forms the Global ENA Spectrum

The heliospheric energetic neutral atom spectrum observed by the Interstellar Boundary Explorer (IBEX) reveals that the heliosheath proton distribution is consistent with a power law. The origin of the spectrum is likely from interstellar pickup ions (PUIs) accelerated at the heliospheric termination shock (HTS). We present an explanation of the proton spectrum origin using a test particle simulation of PUIs accelerated at the HTS. PUIs experience preferential heating by the motional electric field in the shock foot, but do not develop a power-law tail without the presence of turbulence at wavenumbers (k) close to the PUI gyroradius scale (R g ). Voyager 2 observations of the magnetic field downstream of the HTS indicate a moderate amount of turbulence at kR g ≅ 1, (δB /B 0 ) 2 @ 0.01, which we find to be sufficient for producing a downstream suprathermal PUI tail but not at intensities observed by IBEX. Within the shock ramp, however, Voyager observed the turbulence power at much smaller scales to be nearly 100 times stronger, suggesting the possibility of strong turbulence at the PUI gyroradius scale. We show that a proton distribution can develop a power law downstream of the HTS consistent with IBEX observations if (δB /B 0 ) 2 ≳ 0.1 at kR g ≅ 1 in the shock foot. Shock drift acceleration of PUIs by the motional electric field is aided by interactions with turbulence upstream of the shock overshoot. Steepening of the IBEX proton spectrum in directions farther from the heliospheric nose suggests the HTS compression ratio and/or turbulence power weakens near the heliotail.

79 ASTRONOMY AND ASTROPHYSICS↗

High-Fidelity Simulation of the Light-to-Dense Stratification Transient in the HiRJET Facility

Density stratification in a large enclosure is a crucial phenomenon to heat transfer and sustainable passive heat removal of a sodium fast reactor during reactivity transients. However, engineering turbulence models were identified to have unsatisfactory performance in predicting propagation of a stratified front. Yet, the scarcity of high-resolution data for stratification hampers the development of models. To explor e applications of leveraging direct numerical simulation (DNS) data to support turbulence model development, this work conducted DNS using NekRS to study a long stratification transient in the High-Resolution Jet (HiRJET) experimental facility. Here, this work considers an experiment run where light fluid is injected into a tank containing a denser fluid with a relative density difference of 1.5%. Formation of the stratified layer is identified as impingement of the buoyant jet promoting mixing of the two fluids. Based on the transient statistics, transport of the concentration can be characterized by regions with dominating effects of turbulent mixing, buoyant dissipation, and molecular diffusion, respectively, as moving away from the elevation of jet impingement. Concentration near the stratified front also exhibits oscillation at Brunt-Väisälä frequency. Preliminary validation of the simulation showed encouraging agreement of the concentration distribution with the reference experiment.

buoyant mixing↗

Wind Farm Wakes and Farm-to-Farm Interactions: Lidar and Wind Tunnel Tests

Recent experimental and numerical evidence has shown that the cumulative wake generated from the overlapping of multiple wakes within a wind farm could reduce power performance and enhance fatigue loads of wind turbines installed in neighboring downstream wind farms and may also extend up to distances one order of magnitude larger than those typically considered for intra-farm wake interactions. Similar to individual wind turbine wakes, wind farm wakes have a velocity deficit and added turbulence intensity, both affected by the turbine rotor thrust forces and the incoming turbulence intensity. Therefore, the evolution of wind farm wakes will vary for different operational and atmospheric conditions. In this paper, lidar measurements collected during the American WAKE experimeNt (AWAKEN) and wind tunnel tests of wind farms reproduced by porous disks are leveraged to investigate wind farm wakes.

17 WIND ENERGY↗

Microtearing stability and turbulence in the pedestal: Linear gyrokinetics, reduced models, and nonlinear turbulent transport

Microtearing modes can play a crucial role in electron heat transport in tokamak plasmas, affecting both energy confinement and overall performance. This study investigates microtearing modes (MTM) stability and turbulence in a JET pedestal through gyrokinetic simulations using the Gene code, complemented by a reduced eigenvalue model. The focus is on how MTM properties depend on key plasma parameters, including collisionality and plasma beta β—the ratio of plasma pressure to magnetic pressure—the normalized toroidal wavenumber k y ρ s ⁠, where ρ s denotes the ion sound gyroradius (typically a few millimeters in edge plasmas) and isotope mass. Collisionality enhances MT growth rates, while increasing β leads to a shift from MTMs to kinetic-ballooning modes, typically for k y ρ s ⁠, where ρ s ≲ 0.2⁠. A purely collisionless branch of MTMs persists at low k y ρ s ⁠, where ρ s with distinctive properties including non-negligible particle flux and ion thermal transport. Isotope mass scans reveal modest reduction of MTM growth rates as ion mass decreases. Nonlinear simulations produce experimentally relevant transport levels. Numerical experiments turning off zonal flows and fields identify the critical role of zonal flows and zonal fields in regulating MTM turbulence. Their removal leads to a significant increase in electron heat flux. These findings provide new insight into MTM-driven transport and its impact on tokamak confinement and lay a foundation for reduced modeling and predictive capabilities.

Electrostatics↗

Large-Eddy Simulations of Marine Boundary Layer Clouds Associated with Cold-Air Outbreaks during the ACTIVATE Campaign. Part I: Case Setup and Sensitivities to Large-Scale Forcings

Large-eddy simulation (LES) is able to capture key boundary layer (BL) turbulence and cloud processes. Yet, large-scale forcing and surface turbulent fluxes of sensible and latent heat are often poorly prescribed for LESs. We derive these quantities from measurements and reanalysis obtained for two cold-air outbreak (CAO) events during Phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) in February–March 2020. We study the two contrasting CAO cases by performing LES and test the sensitivity of BL structure and clouds to large-scale forcings and turbulent heat fluxes. Profiles of atmospheric state and large-scale divergence and surface turbulent heat fluxes obtained from ERA5 data agree reasonably well with those derived from ACTIVATE field measurements for both cases at the sampling time and location. Therefore, we adopt the time-evolving heat fluxes, wind, and advective tendencies profiles from ERA5 data to drive the LES. We find that large-scale thermodynamic advective tendencies and wind relaxations are important for the LES to capture the evolving observed BL meteorological states characterized by the hourly ERA5 data and validated by the observations. We show that the divergence (or vertical velocity) is important in regulating the BL growth driven by surface heat fluxes in LESs. The evolution of liquid water path is largely affected by the evolution of surface heat fluxes. The liquid water path simulated in LES agrees reasonably well with the ACTIVATE measurements. This study paves the path to investigate aerosol–cloud–meteorology interactions using LES informed and evaluated by ACTIVATE field measurements.

54 ENVIRONMENTAL SCIENCES↗

Updates to Nek5000: RANS wall functions, NRC support, and documentation

As a key part of the U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program (NEAMS), the next generation of tools for nuclear reactor design are being developed. A primary metric for success of this program is the adoption of those tools by industry stakeholders. To help meet this metric for Nek5000, development efforts this year have focused on the expansion of the available Reynolds-averaged Navier-Stokes (RANS) turbulence models to include wall function models, continued support of the U.S. Nuclear Regulatory Commission in simulating a hydrogen mitigation benchmark experiment, and expansion of the Nek5000 documentation to enhance the code’s usability. The implementation of wall functions is intended to significantly decrease time to-solution for a wide range of problems and it has been identified as an important feature by stakeholders across the nuclear community. The initial implementation of standard and pressure corrected wall functions has been tested in Nek5000 on the classical problems of channel flow and a backward facing step. It has also been tested on a 2D molten salt fast reactor core and a T-junction. The recommended formulation of choosing y + = 30 as a boundary value combined with a Neumann-Neumann formulation of the boundary condition for k and τ produces the most consistent results compared to a wall resolved approach. The collaboration with the NRC is a continuing exercise that has been ongoing for multiple years. This year we have concluded investigations into appropriate inlet conditions, showing that fully developed turbulent conditions are adequate for the full PANDA domain. We have also concluded simulations for an unobstructed jet and are now refocusing to the original obstructed jet case. The expansion of the code documentation has also been an ongoing effort over the past few years to address feedback from the various stakeholders. The documentation now more fully covers many of the available features and closes identified SQA gaps. Finally we report on three training sessions that were offered over the past year in an effort to expand the Nek5000 user base.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Lagrangian large eddy simulations via physics-informed machine learning

High-Reynolds number homogeneous isotropic turbulence (HIT) is fully described within the Navier–Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as large eddy simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about effects of subgrid scales on the resolved scales. Here, we take an alternative approach and design LES heuristics stated in terms of Lagrangian particles moving with the flow. Our Lagrangian LES, thus L-LES, is described by equations generalizing the weakly compressible smoothed particle hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from direct numerical simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The subgrid-scale contributions are modeled separately with physical constraints to account for the effects from unresolved scales. We build the resulting model under the differentiable programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our L-LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Concept of a Convection–Cloud Chamber to Study Aerosol–Cloud–Drizzle Interactions

Understanding and quantifying the full chain of processes from aerosol activation to drizzle formation, and the associated feedbacks to the aerosol chemical and physical properties, all within a turbulent cloud are some of the toughest challenges in atmospheric chemistry and physics and are keys to the cloud–precipitation puzzle. This paper describes a concept for a new type of research facility consisting of a cloud chamber plus associated instrumentation and computational models, to explore aerosol–cloud interactions and processing, cloud optical properties, entrainment–cloud interactions, and quantitative assessment of drizzle onset. The envisioned design is for a 3 m × 3 m × 9 m chamber, such that the height is sufficient to achieve long lifetimes for aerosol processing and for significant drizzle growth by collision and coalescence. A suite of computational tools for simulating microphysical properties in the chamber provides a digital twin for designing the chamber and a range of example experiments. Theory and test results from novel remote sensing systems for exploring chemical and physical interactions and evolution of aerosols, cloud droplets, and drizzle within turbulent clouds are described. Testing of technology needed for the operation of a large-volume chamber, including aerosol generation methods and novel materials for water vapor boundary conditions, is described. Simulations suggest that spatially uniform turbulence and microphysical properties can be sustained in a steady state, with reasonable aerosol and water vapor fluxes, and that substantial drizzle can be produced through collision and coalescence of cloud droplets. Remaining challenges for more detailed engineering design and a discussion of possible first-light experiments are described.

54 ENVIRONMENTAL SCIENCES↗

Nonresonant particle acceleration in strong turbulence: Comparison to kinetic and MHD simulations

Collisionless, magnetized turbulence offers a promising framework for the generation of nonthermal high-energy particles in various astrophysical sites. Yet, the detailed mechanism that governs particle acceleration has remained subject to debate. By means of 2D and 3D particle-in-cell, as well as 3D (incompressible) magnetohydrodynamic (MHD) simulations, we test here a recent model of nonresonant particle acceleration in strongly magnetized turbulence, which ascribes the energization of particles to their continuous interaction with the random velocity flow of the turbulence, in the spirit of the original Fermi model. To do so, we compare, for a large number of particles that were tracked in the simulations, the predicted and the observed histories of particles momenta. The predicted history is that derived from the model, after extracting from the simulations, at each point along the particle trajectory, the three force terms that control acceleration: the acceleration of the field line velocity projected along the field line direction, its shear projected along the same direction, and its transverse compressive part. Overall, we find a clear correlation between the model predictions and the numerical experiments, indicating that this nonresonant model can successfully account for the bulk of particle energization through Fermi-type processes in strongly magnetized turbulence. Additionally we also observe that the parallel shear contribution tends to dominate the physics of energization in the particle-in-cell simulations, while in the magnetohydrodynamic incompressible simulation, both the parallel shear and the transverse compressive term provide about equal contributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Code for the manuscript "Lagrangian Large Eddy Simulations vis Physics-informed Machine Learning"

We would like to disclose a code based on Python/Pytorch, in which we implement the data-driven physics-informed machine learning of Lagrangian large eddy simulation that is described in the manuscript "Lagrangian Large Eddy Simulations via Physics-Informed Machine Learning ". High-Reynolds number Homogeneous Isotropic Turbulence is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as Large Eddy Simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about the effects of sub-grid scales on the resolved scales. Here, we take an alternative approach and design novel LES heuristics stated in terms of Lagrangian particles moving with the flow. Our \emph{Lagrangian LES}, thus L-LES, is described by equations generalizing the weakly compressible Smoothed Particle Hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from Direct Numerical Simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The sub-grid scale contributions are modeled separately with physical constraints to account for the effects from un-resolved scales. We build the resulting model under the Differentiable Programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our Lagrangian LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.

Tian, Yifeng↗

End-gas autoignition fraction and flame propagation rate in laser-ignited primary reference fuel mixtures at elevated temperature and pressure

Knock in spark-ignited (SI) engines is initiated by autoignition of the unburned gasses upstream of spark-ignited, propagating, turbulent premixed flames. Knock propensity of fuel/air mixtures is typically quantified using research octane number (RON), motor octane number (MON), or methane number (MN; for gaseous fuels), which are measured using single-cylinder, variable compression ratio engines. In this study, knock propensity of SI fuels was quantified via observations of end-gas autoignition (EGAI) in unburned gasses upstream of laser-ignited, premixed flames at elevated pressures and temperatures in a rapid compression machine. Stoichiometric primary reference fuel (PRF; n-heptane/isooctane) blends of varying reactivity (50 ≤ PRF ≤ 100) were ignited using an Nd:YAG laser over a range of temperatures and pressures, all in excess of 545 K and 16.1 bar. Laser ignition produced outwardly-propagating premixed flames. High-speed pressure measurements and schlieren images indicated the presence of EGAI. The fraction of the total heat release attributed to EGAI (i.e., EGAI fraction) varied with fuel reactivity (i.e., octane number) and the time-integrated temperature of the end-gas prior to ignition. Flame propagation rates, which were measured using schlieren images, were only weakly correlated with octane number but were affected by turbulence caused by variation in piston timing. Under conditions of low turbulence, measured flame propagation rates approached one-dimensional premixed laminar flame speed computations performed at the same conditions. Experiments were simulated with a three-dimensional CONVERGE™ model using reduced chemical kinetics (121 species, 538 reactions). The simulations accurately captured the measured flame propagation rates, as well as the variation in EGAI fraction with fuel reactivity and time-integrated end-gas temperature. The simulations also revealed low-temperature heat release as well as formaldehyde and hydrogen peroxide formation in the end-gas upstream of the propagating flame, which increased the temperature and degree of chain branching in the end-gas, ultimately leading to EGAI.

42 ENGINEERING↗

Investigating shear flow through continuum gyrokinetic simulations of limiter biasing in the Texas Helimak

Previous limiter-biasing experiments on the Texas Helimak, a simple magnetized torus, have been inconclusive on the effect of flow shear on turbulence levels. To explore this, the first gyrokinetic simulations of limiter biasing in the Helimak using the plasma physics code Gkeyll have been carried out, and results are presented here. For the scenarios considered, turbulence is mostly driven by the interchange instability, which depends on gradients of steady state density profiles. An analysis of both experimental and simulation data demonstrates that shear rates are mostly less than than local linear growth rates, and not all requirements for shear stabilization are met. Yet, the mostly vertical shear flow has an important effect on bulk transport and experimental steady-state density profiles, and changes to the gradients correspond to changes in turbulence levels.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Asymmetric fluctuations and self-folding of active interfaces

We study the structure and dynamics of the interface separating a passive fluid from a microtubule-based active fluid. Turbulent-like active flows power giant interfacial fluctuations, which exhibit pronounced asymmetry between regions of positive and negative curvature. Experiments, numerical simulations, and theoretical arguments reveal how the interface breaks up the spatial symmetry of the fundamental bend instability to generate local vortical flows that lead to asymmetric interface fluctuations. The magnitude of interface deformations increases with activity: In the high activity limit, the interface self-folds invaginating passive droplets and generating a foam-like phase, where active fluid is perforated with passive droplets. These results demonstrate how active stresses control the structure, dynamics, and break-up of soft, deformable, and reconfigurable liquid–liquid interfaces.

active fluid↗

Kinetic-ballooning-mode turbulence in low-average-magnetic-shear equilibria

In this work, kinetic-ballooning-mode (KBM) turbulence is studied via gyrokinetic flux-tube simulations in three magnetic equilibria that exhibit small average magnetic shear: the Helically Symmetric eXperiment (HSX), the helical-axis Heliotron-J and a circular tokamak geometry. For HSX, the onset of KBM being the dominant instability at low wavenumber occurs at a critical value of normalized plasma pressure $\beta ^{\rm KBM}_{\rm crit}$ that is an order of magnitude smaller than the magnetohydrodynamic (MHD) ballooning limit $\beta ^{\rm MHD}_{\rm crit}$ when a strong ion temperature gradient (ITG) is present. However, $\beta ^{\rm KBM}_{\rm crit}$ increases and approaches the MHD ballooning limit as the ITG tends to zero. For these configurations, $\beta ^{\rm KBM}_{\rm crit}$ also increases as the magnitude of the average magnetic shear increases, regardless of the sign of the normalized magnetic shear. Simulations of Heliotron-J and a circular axisymmetric geometry display behaviour similar to HSX with respect to $\beta ^{\rm KBM}_{\rm crit}$ . Despite large KBM growth rates at long wavelengths in HSX, saturation of KBM turbulence with $\beta > \beta _{\rm crit}^{\rm KBM}$ is achievable in HSX and results in lower heat transport relative to the electrostatic limit by a factor of roughly five. Nonlinear simulations also show that KBM transport dominates the dynamics when KBMs are destabilized linearly, even if KBM growth rates are subdominant to ITG growth rates.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Physics of Edge-Core Coupling by Inward Turbulence Propagation

The dynamics of edge-core coupling is critically important to the optimization of magnetically confined fusion plasmas. Since early proposals, there has been persistent speculation that inward propagation of turbulence from the boundary is a possible means to energize the edge-core coupling region. However, the detailed mechanism of this process has remained a mystery until recent experiments observed that regular, intense gradient relaxation events generated blob-void pairs very close to the last closed flux surface. Blobs ($\tilde{n}$ >0) propagate outward and detach from the bulk plasma, while voids ($\tilde{n}$ <0) propagate inward, and so stir the core plasma. Here, in this work, we demonstrate that this heretofore ignored process of void emission can drive a broad turbulent layer of width ∼100 𝜌 𝑠 , for typical parameters. The mechanism is the Cherenkov emission of drift waves from inward-propagating voids. The model shows promise to resolve several questions surrounding the shortfall problem and the strong turbulence in the edge-core coupling region.

drift waves↗

Peculiarities of adaptive phase correction of optical wave distortions under conditions of ‘strong’ intensity fluctuations

The reason for the loss of efficiency of adaptive phase correction in the propagation of optical waves in a turbulent atmosphere under conditions of ‘strong’ intensity fluctuations is experimentally explained for the first time. Based on the data from experiments conducted on both horizontal and vertical atmospheric paths, we have found that intensity fluctuations begin to significantly affect phase measurements when the coherence radius of the optical wave becomes less than the radius of the first Fresnel zone. Under these conditions, the main meter of adaptive optics systems, i. e. the Hartmann sensor, no longer provides correct measurements of the phase distribution in the presence of deep amplitude modulation. Based on the study of the behaviour of the mode components of the phase fluctuations reconstructed from the results of measurements in various operating regimes, we have found that, first of all, the amplitudes of the lowest modes of phase fluctuation expansion (tilts, defocusing, and astigmatism) are distorted, which, as the analysis shows, is very different from the regime of weak fluctuations. (atmospheric optics)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗