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Zhihong Lin

Publications and source records attributed to Zhihong Lin.

At least 19 recordsLinked to original sources

Minute-Scale High-Fidelity Gyrokinetic Simulations with Portability from Laptop to Supercomputer

Global gyrokinetic particle simulations remain computationally expensive, as they demand both adequate marker statistics and three-dimensional field solvers. In this work, we present a hybrid spectral method within the particle-in-Fourier (PIF) framework and implement it in the electrostatic model of GTC. Charge scatter and field gather are performed between particles and fields on a two-dimensional poloidal mesh, while the corresponding Poisson solver is discretized using radial finite differences and poloidal $m$-harmonics. Truncated spectral transforms are employed to connect multiple representations for fields, avoiding costly particle-grid operations for each individual $m$-harmonic within the particle loop. Benchmarks against conventional particle-in-cell (PIC) simulations successfully reproduce single-$n$ ion temperature gradient (ITG) mode structures and dispersion relations, as well as multi-$n$ nonlinear ITG transport and its regulation by zonal flows. Compared to conventional PIC, the proposed method reduces the effective problem size by more than a factor of 48 and achieves a speedup of over two orders of magnitude for single-$n$ cases. A 2000-step single-$n$ simulation with approximately 2 million markers completes in 78.2 seconds on a laptop GPU, while multi-$n$ turbulence simulation also completes within minutes. Furthermore, the elimination of toroidal particle-shift communication yields promising preliminary scaling performance on multiple NVIDIA A100 GPUs. The numerical scheme is broadly applicable for accelerating particle simulations on platforms ranging from laptops to supercomputers.

physics.plasm-ph

Low-dimensional geometry learning for turbulence prediction in optimized stellarators

The optimized stellarator is an attractive concept for which the averaged particle radial drift is zero, and the single particle loss can be significantly reduced. But for the reactor design, global physics such as turbulent transport also need to be optimized besides the confined single particle orbit, or properties estimated using local estimations and heuristic formulations. The first-principle global transport code is too computationally expensive to integrate into the optimization process. The fast surrogate global transport model based on machine learning is a good alternative choice, but the amount of data required to train the surrogate model is numerous due to the high degree-of-freedom of the stellarator design. The work shows that the stellarator design with quasi-helically(QH) symmetric geometry is approximately distributed in a low dimensional latent space, which can be explicitly found by deep learning. This discovery makes it possible to generate global gyrokinetic simulation data for training surrogate models to directly optimize the stellarator geometry for turbulent transport, energetic particle instability, and MHD modes. Using the low dimensional latent space and data analysis methods, the relation between linear zonal residues and axis-excursion is found, providing a simple guide to optimize low turbulent transport QH stellarators.

physics.plasm-ph

Gyrokinetic simulation of the effect of transient fueling on plasma turbulence in ADITYA-U tokamak

The gradient-driven microturbulence in ADITYA-U tokamak plasmas has been suppressed by injecting short gas puffs. The suppression of microturbulence increases the core temperature and subsequently the energy confinement time following the gas puff. The gas injection modifies the radial density profile, making it relatively flatter near the mid-radius. Global electrostatic gyrokinetic simulations show that this modification to the radial density profile due to gas injection suppresses the existing trapped electron mode (TEM). Simulation results show that the TEM-dominated turbulence suppression reduces the turbulence-driven heat transport, leading to an increase in core temperature. Applying multiple periodic gas-puffs leads to multiple periodic events of TEM suppression, improving the overall energy confinement time, and is used as an active control mechanism to influence microturbulence in ADITYA-U tokamak.

physics.plasm-ph

Design and Analysis Strategies for Pooling in High Throughput Screening: Application to the Search for a New Anti-Microbial

A major public health issue is the growing resistance of bacteria to antibiotics. An important part of the needed response is the discovery and development of new antimicrobial strategies. These require the screening of potential new drugs, typically accomplished using high-throughput screening (HTS). Traditionally, HTS is performed by examining one compound per well, but a more efficient strategy pools multiple compounds per well. In this work, we study several recently proposed pooling construction methods, as well as a variety of pooled high-throughput screening analysis methods, in order to provide guidance to practitioners on which methods to use. This is done in the context of an application of the methods to the search for new drugs to combat bacterial infection. We discuss both an extensive pilot study as well as a small screening campaign, and highlight both the successes and challenges of the pooling approach.

stat.AP

$T_i/T_e$ Dependence of Core Turbulence and Transport in DIII-D QH-Mode Plasmas

This study investigates the effect of the ion-to-electron temperature ratio ($T_i/T_e$) on microturbulence driven transport in Quiescent H-mode (QH-mode) plasmas in the DIII-D tokamak. Utilizing the Gyrokinetic Toroidal Code (GTC) and the QH-mode equilibrium, we perform linear and nonlinear simulations to analyze transport properties and instability dynamics under variations of $T_i$ and $T_e$. Our results demonstrate that decreasing $T_i/T_e$ leads to a relative destabilization of trapped electron modes (TEM) over ion temperature gradient (ITG) modes, with the transition between these regimes dictated by $T_i/T_e$. When the electron temperature is increased at fixed ion temperature, we observe an increase in transport saturation levels. In contrast, decreasing the ion temperature at fixed electron temperature results in more modest transport enhancement. The radial correlation length, which characterizes eddy size, increases with rising $T_e$ and decreases with falling $T_i$, consistent with the observed trends in turbulent transport. Additionally, we examine the impact of impurity addition on turbulence and growth rates, finding that impurity presence does not significantly alter transport quantities compared to the impurity-free case. Finally, investigating helium as an alternative main ion species, we find that helium plasmas exhibit higher linear growth rates but result in lower transport saturation levels than deuterium plasmas, suggesting potential confinement benefits. These findings provide quantitative insights into the temperature ratio dependence in QH-mode plasmas and highlight the role of temperature profiles and zonal flows in influencing plasma confinement.

physics.plasm-ph

Electromagnetic turbulence in EAST plasmas with internal transport barrier

In this study, global nonlinear electromagnetic gyrokinetic simulations are conducted to investigate turbulence in the Internal transport barrier (ITB) region of the EAST tokamak discharge with weakly reversed magnetic shear. Linear simulations reveal two dominant ion temperature gradient (ITG) modes: a higher frequency mode at the $q=1$ surface, which dominates in the electrostatic limit, and a lower frequency mode near the $q_{\min}$ surface, which prevails under the experimental $\beta$ (the ratio of plasma pressure to magnetic pressure). Finite $\beta$ effects effectively suppress higher frequency ITG modes, and once $\beta_i$ on axis exceeds 0.5\%, this ITG mode is no longer dominant, and the ITG mode near $q_{\min}$ surface becomes the primary instability. Therefore, electromagnetic effects play a crucial role in stabilizing ITG modes, and in causing the transition between the most unstable mode at different radial positions. The linear growth rate of the unstable mode in the electrostatic limit is approximately 1.25 times higher than that of the dominant mode in the electromagnetic case. However, in the electromagnetic nonlinear regime, the thermal ion heat conductivity is reduced by at least a factor of 4. This reduction primarily results from nonlinear electromagnetic effects enhancing the shearing effect of zonal flows, thereby further suppressing microturbulence. Finally, energetic particles exert a slight stabilizing effect on ITG turbulence due to dilution and finite $\beta$ contributions. It is emphasized that the electromagnetic effect on ITG with weak magnetic shear should be included to accurately calculate the transport coefficients.

physics.plasm-ph

Cross-scale Interaction between Microturbulence and Fishbone in Fusion Plasmas

Global gyrokinetic simulations are performed for the first time to investigate cross-scale interactions between electromagnetic ion temperature gradient (ITG) turbulence and fishbone instability in tokamak plasmas. The investigation of fluctuation response in the multiscale simulation including both instabilities indicates a strong impact of fishbone on ITG turbulence. Detailed analysis reveals that fishbone-driven zonal radial electric fields at nonlinear saturation significantly suppress electromagnetic ITG turbulence, reducing ion thermal transport close to the neoclassical level. The simulation results agree well with experimental observations that turbulence suppression during fishbone bursts. These findings advance understanding of multiscale interactions that enhance thermal confinement in fusion plasmas.

physics.plasm-ph

Geometry effects on zonal flow dynamics and turbulent transport in optimized stellarators

Global gyrokinetic simulations find a strong suppression of ion temperature gradient (ITG) turbulence by zonal flows in stellarators optimized for neoclassical transport. The reduction of the ITG transport by the zonal flows in quasi-helicalsymmetric (QH) and quasi-isodynamic (QI) stellarators are much larger than a quasi-axisymmetric (QA) stellarator or a tokamak, thanks to higher linear residual levels and lower nonlinear frequencies of the zonal flows in the QH and QI. The transport level and energy confinement time in the QH and QI are similar to the tokamak with the same size and temperature gradient, despite the much larger linear growth rates in the stellarators.

physics.plasm-ph

Zonal flow suppression of turbulent transport in the optimized stellarators W7-X and QSTK

We present a comparative study of transport in two optimized stellarator configurations: Wendelstein 7-X (W7-X) and a recent design called Quasi-Symmetric Turbulence Konzept (QSTK). Using global Gyrokinetic Toroidal Code (GTC), we explore the role of zonal flows (ZFs) in suppressing electrostatic Ion Temperature Gradient (ITG) driven turbulence in both configurations. The simulations reveal that ZFs significantly reduce ion heat transport in both W7-X and QSTK, with a lower value of heat flux on the latter configuration, as suggested by the apparently higher linear threshold (''critical'') gradients for ITG modes. The study also highlights that both stellarators exhibit similar mode structures. The results support the notion that linear stability measures, in combination with nonlinear stabilization by zonal flows, can play an important role in the suppression of nonlinear heat fluxes.

physics.plasm-ph

Gyrokinetic simulations of the effects of magnetic islands on microturbulence in KSTAR

Gyrokinetic simulations are utilized to study effects of magnetic islands on the ion temperature gradient (ITG) turbulence in the KSTAR tokamak with resonant magnetic perturbations. Simulations show that the transport is controlled by the nonlinear interactions between the ITG turbulence and self-generated vortex flows and zonal flows, leading to an anisotropic structure of fluctuation and transport on the poloidal plane and in the toroidal direction. Magnetic islands greatly enhance turbulent transport of both particle and heat. The turbulent transport exhibits variations in the toroidal direction, with transport through the resonant layer near the island X-point being enhanced when the X-point is located at the outer mid-plane. A quantitative agreement is shown between simulations and KSTAR experiments in terms of time frequency and perpendicular wavevector spectrum.

physics.plasm-ph

AI-Machine Learning-Enabled Tokamak Digital Twin

In addressing the Department of Energy's April, 2022 announcement of a Bold Decadal Vision for delivering a Fusion Pilot Plant by 2035, associated software tools need to be developed for the integration of real world engineering and supply chain data with advanced science models that are accelerated with Machine Learning. An associated research and development effort has been introduced here with promising early progress on the delivery of a realistic Digital Twin Tokamak that has benefited from accelerated advances by the Princeton University AI Deep Learning innovative near-real-time simulators accompanied by technological capabilities from the NVIDIA Omniverse, an open computing platform for building and operating applications that connect with leading scientific computing visualization software. Working with the CAD files for the GA/DIII-D tokamak including equilibrium evolution as an exemplar tokamak application using Omniverse, the Princeton-NVIDIA collaboration has integrated modern AI/HPC-enabled near-real-time kinetic dynamics to connect and accelerate state-of-the-art, synthetic, HPC simulators to model fusion devices and control systems. The overarching goal is to deliver an interactive scientific digital twin of an advanced MFE tokamak that enables near-real-time simulation workflows built with Omniverse to eventually help open doors to new capabilities for generating clean power for a better future.

physics.comp-ph

FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings via Deep Neural Networks

Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. Development of novel model reduction methods, coupled with detection of abnormal modes with plasma physics, opens a unique opportunity for building efficient models to identify plasma instabilities for real-time control. Our Fusion Transfer Learning (FTL) model demonstrates success in reconstructing nonlinear kink mode structures by learning from a limited amount of nonlinear simulation data. The knowledge transfer process leverages a pre-trained neural encoder-decoder network, initially trained on linear simulations, to effectively capture nonlinear dynamics. The low-dimensional embeddings extract the coherent structures of interest, while preserving the inherent dynamics of the complex system. Experimental results highlight FTL's capacity to capture transitional behaviors and dynamical features in plasma dynamics -- a task often challenging for conventional methods. The model developed in this study is generalizable and can be extended broadly through transfer learning to address various magnetohydrodynamics (MHD) modes.

physics.comp-ph

Vanishing of Dimits Shift in Realistic Fusion Plasmas with Negative Magnetic Shear

This study employs gyrokinetic simulations to investigate ion temperature gradient (ITG) turbulence in realistic fusion plasmas featuring reverse magnetic shear. Negative magnetic shear is found to suppress the ITG instability due to the scarcity of mode rational surfaces, as evidenced by a comparison of instabilities for different magnetic shears. This suppression effect remains observable in nonlinear turbulence with zonal flow artificially eliminated, where the emergence of turbulence solitons aligns with mode rational surface peaks. However, the suppression effect diminishes in the presence of self-consistently generated zonal flow, along with the occurance of turbulence solitons. The zonal flow is found to originated from a force driven process by the primary instability, instead of the conventional modulational instability. The study further reveals a remarkable phenomenon that the Dimits shift no longer exists for negative magnetic shear, which are attributed to the weakness of zonal flow around marginal stability. However, away from marginal stability, the turbulent transport is primarily regulated by the zonal flow regardless of different magnetic shears.

physics.plasm-ph

Helically-trapped electron mode in optimized stellarator

Global gyrokinetic simulations find a strong helically-trapped electron mode (HTEM) driven by density gradients in the optimized stellarator W7-X fusion experiment. The eigenmode structure localizes in the inner side of the torus with an unfavorable magnetic curvature and weak magnetic field, where there is a large fraction of helically-trapped electrons. The mode is excited mostly by the ion free energy and propagates in the ion direction with a linear frequency much smaller than the diamagnetic frequency. The instability saturates by nonlinear processes of turbulence spreading in the real space and spectral transfer from unstable to damped regions. The steady state HTEM turbulence drives a large particle flux that may have significant implications for the confinement of fusion fuel and removal of fusion ash in the stellarator reactor.

physics.plasm-ph

Global simulations of kinetic-magnetohydrodynamic processes with energetic electrons in tokamak plasmas

The energetic electrons (EEs) generated through auxiliary heating have been found to destabilize various Alfven eigenmodes (AEs) in recent experiments, which in turn lead to the EE transport and degrade the plasma energy confinement. In this work, we propose a global fluid-kinetic hybrid model for studying corresponding kinetic-magnetohydrodynamic (MHD) processes by coupling the drift-kinetic EEs to the Landau-fluid model of bulk plasmas in a non-perturbative manner. The numerical capability of Landau-fluid bulk plasmas is obtained based on a well-benchmarked eigenvalue code MAS [Multiscale Analysis of plasma Stabilities, J. Bao et al. Nucl. Fusion accepted 2023], and the EE responses to the electromagnetic fluctuations are analytically derived, which not only contribute to the MHD interchange drive and parallel current but also lead to the newly kinetic particle compression with the precessional drift resonance in the leading order. The hybrid model is casted into a nonlinear eigenvalue matrix equation and solved iteratively using Newton's method. By calibrating the EE precession frequency against the particle equation of motion in general geometry and applying more realistic trapped particle distribution in the poloidal plane, MAS simulations of EE-driven beta-induced Alfven eigenmodes (e-BAE) show excellent agreements with gyrokinetic particle-in-cell simulations, and the non-perturbative effects of EEs on e-BAE mode structure, growth rate and damping rate are demonstrated. With these efforts, the upgraded MAS greatly improves the computation efficiency for plasma problems related to deeply-trapped EEs, which is superior than initial-value simulations restricted by the stringent electron Courant condition regarding to the practical application of fast linear analysis.

physics.plasm-ph

MAS: A versatile Landau-fluid eigenvalue code for plasma stability analysis in general geometry

We have developed a new global eigenvalue code, Multiscale Analysis for plasma Stabilities (MAS), for studying plasma problems with wave toroidal mode number n and frequency omega in a broad range of interest in general tokamak geometry, based on a five-field Landau-fluid description of thermal plasmas. Beyond keeping the necessary plasma fluid response, we further retain the important kinetic effects including diamagnetic drift, ion finite Larmor radius, finite parallel electric field, ion and electron Landau resonances in a self-consistent and non-perturbative manner without sacrificing the attractive efficiency in computation. The physical capabilities of the code are evaluated and examined in the aspects of both theory and simulation. In theory, the comprehensive Landau-fluid model implemented in MAS can be reduced to the well-known ideal MHD model, electrostatic ion-fluid model, and drift-kinetic model in various limits, which clearly delineates the physics validity regime. In simulation, MAS has been well benchmarked with theory and other gyrokinetic and kinetic-MHD hybrid codes in a manner of adopting the unified physical and numerical framework, which covers the kinetic Alfven wave, ion sound wave, low-n kink, high-n ion temperature gradient mode and kinetic ballooning mode. Moreover, MAS is successfully applied to model the Alfven eigenmode (AE) activities in DIII-D discharge #159243, which faithfully captures the frequency sweeping of RSAE, the tunneling damping of TAE, as well as the polarization characteristics of KBAE and BAAE being consistent with former gyrokinetic theory and simulation. With respect to the key progress contributed to the community, MAS has the advantage of combining rich physics ingredients, realistic global geometry and high computation efficiency together for plasma stability analysis in linear regime.

physics.plasm-ph

Reconstruction of tokamak plasma safety factor profile using deep learning

In tokamak operations, accurate equilibrium reconstruction is essential for reliable real-time control and realistic post-shot instability analysis. The safety factor (q) profile defines the magnetic field line pitch angle, which is the central element in equilibrium reconstruction. The motional Stark effect (MSE) diagnostic has been a standard measurement for the magnetic field line pitch angle in tokamaks that are equipped with neutral beams. However, the MSE data are not always available due to experimental constraints, especially in future devices without neutral beams. Here we develop a deep learning-based surrogate model of the gyrokinetic toroidal code for q profile reconstruction (SGTC-QR) that can reconstruct the q profile with the measurements without MSE to mimic the traditional equilibrium reconstruction with the MSE constraint. The model demonstrates promising performance, and the sub-millisecond inference time is compatible with the real-time plasma control system.

physics.plasm-ph

Camera Adaptation for Fundus-Image-Based CVD Risk Estimation

Recent studies have validated the association between cardiovascular disease (CVD) risk and retinal fundus images. Combining deep learning (DL) and portable fundus cameras will enable CVD risk estimation in various scenarios and improve healthcare democratization. However, there are still significant issues to be solved. One of the top priority issues is the different camera differences between the databases for research material and the samples in the production environment. Most high-quality retinography databases ready for research are collected from high-end fundus cameras, and there is a significant domain discrepancy between different cameras. To fully explore the domain discrepancy issue, we first collect a Fundus Camera Paired (FCP) dataset containing pair-wise fundus images captured by the high-end Topcon retinal camera and the low-end Mediwork portable fundus camera of the same patients. Then, we propose a cross-laterality feature alignment pre-training scheme and a self-attention camera adaptor module to improve the model robustness. The cross-laterality feature alignment training encourages the model to learn common knowledge from the same patient's left and right fundus images and improve model generalization. Meanwhile, the device adaptation module learns feature transformation from the target domain to the source domain. We conduct comprehensive experiments on both the UK Biobank database and our FCP data. The experimental results show that the CVD risk regression accuracy and the result consistency over two cameras are improved with our proposed method. The code is available here: \url{https://github.com/linzhlalala/CVD-risk-based-on-retinal-fundus-images}

cs.CV