相关论文: Comparing spontaneous and pellet-triggered ELMs vi…
The localized deposition of the energy of a laser pulse, as it ablates a solid target, introduces high thermal pressure gradients in the plasma. The thermal expansion of this laser-heated plasma into the ambient medium (ionized residual…
We focus on the process of plasma acceleration in the presence of non-negligible thermal effects, wherein a driver of relativistic electrons perturbs a warm neutral plasma and generates a wakefield structure. We study the acceleration…
An effective disruption mitigation system in a tokamak reactor should limit the exposure of the wall to localized heat losses and to the impact of high current runaway electron beams, and avoid excessive forces on the structure. We evaluate…
The outflows from gamma ray bursts, active galactic nuclei and relativistic jets in general interact with the surrounding media through collisionless shocks. With three dimensional relativistic particle-in-cell simulations we investigate…
The Extended Discrete Element Method (XDEM) is an innovative numerical simulation technique that extends the dynamics of granular materials known as Discrete Element Method (DEM) by additional properties such as the thermodynamic state,…
Accurate prediction of physical fields is critical in various engineering applications, including thermal management in electronic systems, airfoil shape optimization in aerospace, and flow field control in hypersonic vehicles. This study…
Tokamak plasmas with strong negative triangularity (NT) shaping typically exhibit fundamentally different edge behavior than conventional L-mode or H-mode plasmas. Over the entire DIII-D database, plasmas with sufficiently negative…
A new modular code called BOUT++ is presented, which simulates 3D fluid equations in curvilinear coordinates. Although aimed at simulating Edge Localised Modes (ELMs) in tokamak X-point geometry, the code is able to simulate a wide range of…
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…
Extreme Learning Machines (ELM) provide a fast alternative to traditional gradient-based learning in neural networks, offering rapid training and robust generalization capabilities. Its theoretical basis shows its universal approximation…
We present a data-driven reduced-order modeling of the space-charge dynamics for electromagnetic particle-in-cell (EMPIC) plasma simulations based on dynamic mode decomposition (DMD). The dynamics of the charged particles in kinetic plasma…
The magnetohydrodynamic-kinetic (MHD-kinetic) hybrid model [Park et. al., 1992] has been widely applied in studying energetic particles (EPs) problems in fusion plasmas for past decades. The pressure-coupling scheme or the current-coupling…
Deep learning (DL) models are piquing high interest and scaling at an unprecedented rate. To this end, a handful of tiled accelerators have been proposed to support such large-scale training tasks. However, these accelerators often…
The conventional deep learning paradigm often involves training a deep model on a server and then deploying the model or its distilled ones to resource-limited edge devices. Usually, the models shall remain fixed once deployed (at least for…
We have applied a double decoupled localized level Anderson-Newns Hamiltonian to the analysis of surface effects upon the ionized fraction $\mathcal{R}_{+}$ of sputtered atoms from a metal surface. Electronic excitations, induced in the…
This review describes recent advances by the authors and others on the topic of incorporating experimental data into molecular simulations through maximum entropy methods. Methods which incorporate experimental data improve accuracy in…
Accurate and efficient modeling of soft-tissue interactions is fundamental for advancing surgical simulation, surgical robotics, and model-based surgical automation. To achieve real-time latency, classical Finite Element Method (FEM)…
Deploying Large Language Models (LLMs) on edge devices remains challenging due to their quadratically increasing computations with the sequence length. Existing studies for dynamic attention pruning are designed for hardware with massively…
This study compares the penetration characteristics of impact-induced jets with those of laser-induced jets, focusing on the underlying penetration mechanism rather than device performance for needle-free injection. Using an impact-induced…
Small magnetic fluctuations ($B_1/B_0 \sim 10^{-4}$) are intrinsically present in a magnetic confinement plasma due to turbulent currents. While the perpendicular transport of particles and heat is typically dominated by fluctuations of the…