Related papers: Plasma Confinement State Classification in Fusion …
Materials synthesis platforms that are designed for autonomous experimentation are capable of collecting multimodal diagnostic data that can be utilized for feedback to optimize material properties. Pulsed laser deposition (PLD) is emerging…
In the day-to-day operations of healthcare institutions, a multitude of Personally Identifiable Information (PII) data exchanges occur, exposing the data to a spectrum of cybersecurity threats. This study introduces a federated learning…
Parameter-efficient fine-tuning (PEFT) allows model builders to capture the task-specific parameters into adapters, which are a fraction of the size of the original base model. Popularity of PEFT technique for fine-tuning has led to the…
The equilibrium of a finite-beta cylindrical RFP plasma in the presence of saturated-amplitude tearing modes is investigated. The singularities arising from the perturbative analysis of the MHD force balance equation JxB=grad(p) are…
Deep Neural Networks (DNNs) face interpretability challenges due to their opaque internal representations. While Feature Map Convergence Evaluation (FMCE) quantifies module-level convergence via Feature Map Convergence Scores (FMCS), it…
Using a range of fusion power plant (FPP) concepts, we demonstrate that spin-polarized fuel (SPF) can significantly enhance net electric power output, often by many multiples. Notably, the electric power gain from SPF generally exceeds the…
Federated edge learning (FEEL) is a widely adopted framework for training an artificial intelligence (AI) model distributively at edge devices to leverage their data while preserving their data privacy. The execution of a power-hungry…
Examining energization of kinetic plasmas in phase space is a growing topic of interest, owing to the wealth of data in phase space compared to traditional bulk energization diagnostics. Via the field-particle correlation (FPC) technique…
State machine formalisms equipped with hierarchy and parallelism allow to compactly model complex system behaviours. Such models can then be transformed into executable code or inputs for model-based testing and verification techniques.…
Combined electric power system and High-Altitude Electromagnetic Pulse (HEMP) models are being developed to determine the effect of a HEMP on the US power grid. The work relies primarily on deterministic methods; however, it is…
We present the first measurements of reaction-in-flight (RIF) neutrons in an inertial confinement fusion system. The experiments were carried out at the National Ignition Facility, using both Low Foot and High Foot drives and cryogenic…
Deep neural networks are behind many of the recent successes in machine learning applications. However, these models can produce overconfident decisions while encountering out-of-distribution (OOD) examples or making a wrong prediction.…
Phase space matching between two plasma-accelerator (PA) stages and between a PA and a traditional accelerator component is a critical issue for emittance preservation of beams accelerated by PAs. The drastic differences of the transverse…
With the increased availability of condition monitoring data and the increased complexity of explicit system physics-based models, the application of data-driven approaches for fault detection and isolation has recently grown. While…
The paper presents a 1D2V electrostatic PIC model with a drift-kinetic description of all particle types aiming at simulating classical longitudinal plasma transport in axially symmetric open traps. The model generalizes the semi-implicit…
Centrifugal confinement fusion, a promising alternative to toroidal confinement devices like tokamaks and stellarators, leverages supersonic plasma rotation within a magnetic mirror configuration to achieve simplified coil design,…
The Cellular Potts Model (CPM) is a lattice based modeling technique which is widely used for simulating cellular patterns such as foams or biological tissues. Despite its realism and generality, the standard Monte Carlo algorithm used in…
SPARC_LAB is a facility designed for the production of FEL radiation and the exploration of advanced acceleration techniques using a high brightness electron photo-injector. Specifically, particle-driven plasma wakefield acceleration (PWFA)…
This Thesis present the process of development very low sensitivity to background radiation n-g scintillation detectors with close to 100% efficiency to corpuscular diagnostic of thermonuclear plasma. The detectors developed using this…
Electric propulsion is now a sucessfull method for primary propulsion of deep space long duration missions and for geosyncronous satellite attitude control. Closed Drift Plasma Thruster, so called Hall Thruster or SPT (stationary plasma…