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An optimization method for chaotic turbulent flow
Evidence indicates that quantities-of-interest in some turbulent flows can be controlled
despite the overall chaotic dynamics. It is typically thought that this is via relatively …
despite the overall chaotic dynamics. It is typically thought that this is via relatively …
[HTML][HTML] Stochastic Galerkin particle methods for kinetic equations of plasmas with uncertainties
The study of uncertainty propagation is of fundamental importance in plasma physics
simulations. To this end, in the present work we propose a novel stochastic Galerkin (sG) …
simulations. To this end, in the present work we propose a novel stochastic Galerkin (sG) …
[HTML][HTML] Particle simulation methods for the Landau-Fokker-Planck equation with uncertain data
The design of particle simulation methods for collisional plasma physics has always
represented a challenge due to the unbounded total collisional cross section, which …
represented a challenge due to the unbounded total collisional cross section, which …
[PDF][PDF] Application of particle swarm optimization with ANFIS model for double scroll chaotic system
WA Wali - International Journal of Electrical and Computer …, 2021 - core.ac.uk
The predictions for the original chaos patterns can be used to correct the distorted chaos
pattern which has changed due to any changes whether from undesired disturbance or …
pattern which has changed due to any changes whether from undesired disturbance or …
Development of reduced-order models of the ion impact distribution function in magnetized plasma sheaths
MAJM Mustafa - 2023 - ideals.illinois.edu
In magnetic-confinement fusion devices, high-fidelity models of the energy-angle distribution
of the ions impacting on material walls are crucial for characterizing ion-surface interactions …
of the ions impacting on material walls are crucial for characterizing ion-surface interactions …
Regular sensitivity calculation and gradient-based optimization of chaotic dynamical systems
SW Chung - 2021 - ideals.illinois.edu
A gradient of a quantity-of-interest J with respect to problem parameters can augment the
utility of a predictive simulation. By itself, the gradient provides sensitivity information to …
utility of a predictive simulation. By itself, the gradient provides sensitivity information to …