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In ideal MHD, the magnetic flux is advected by the plasma motion, freezing flux-surfaces into the flow. An MHD equilibrium is reached when the flow relaxes and force balance is achieved. We ask what classes of MHD equilibria can be accessed…

Plasma Physics · Physics 2020-07-15 David Pfefferlé , Lyle Noakes , Yao Zhou

The mathematical formulation, basic concept and numerical implementation of a new meshless method for solving three dimensional fluid flow and related heat transfer problems are presented in this paper. Moving least squares approximation is…

Computational Physics · Physics 2018-09-10 Cheng-An Wang , Hamou Sadat , Christian Prax

In supervised learning using kernel methods, we often encounter a large-scale finite-sum minimization over a reproducing kernel Hilbert space (RKHS). Large-scale finite-sum problems can be solved using efficient variants of Newton method,…

Machine Learning · Computer Science 2022-06-07 Ting-Jui Chang , Shahin Shahrampour

We present a methodology for simulating three-dimensional flow of incompressible viscoplastic fluids modelled by generalised Newtonian rheological equations. It is implemented in a highly efficient framework for massively parallelisable…

Fluid Dynamics · Physics 2019-09-17 Knut Sverdrup , Ann Almgren , Nikolaos Nikiforakis

This paper presents reproducing kernel Hilbert spaces method to obtain the numerical solution for partial differential equation constrained optimization problem.

Optimization and Control · Mathematics 2016-11-09 Majid Darehmiraki

Kernel methods approximate nonlinear maps in a data-driven manner by projecting the target map onto a finite-dimensional Hilbert space called the solution space. Traditionally, this space is a subspace of a fixed ambient reproducing kernel…

Numerical Analysis · Mathematics 2026-01-30 Tamás Dózsa , Andrea Angino , Zoltán Szabó , József Bokor , Matthias Voigt

We construct a Wasserstein gradient flow of the maximum mean discrepancy (MMD) and study its convergence properties. The MMD is an integral probability metric defined for a reproducing kernel Hilbert space (RKHS), and serves as a metric on…

Machine Learning · Statistics 2019-12-04 Michael Arbel , Anna Korba , Adil Salim , Arthur Gretton

The aim is to justify rigorously the so-called reduced magnetohydrodynamic model (abbreviated as RMHD), which is widely used in fusion, space and astrophysical plasmas. Motivated by physics, the focus is on plasmas that are simultaneously…

Analysis of PDEs · Mathematics 2025-06-30 Nicolas Besse , Christophe Cheverry

In this paper, a novel immersed boundary method is developed, validated, and applied. Through devising a second-order three-step flow reconstruction scheme, the proposed method is able to enforce the Dirichlet, Neumann, Robin, and Cauchy…

Fluid Dynamics · Physics 2018-09-10 Huangrui Mo , Fue-Sang Lien , Fan Zhang , Duane S. Cronin

In this paper, Optimal Homotopy Perturbation Method (OHPM) is employed to determine an analytic approximate solutions for nonlinear MHD Jeffery-Hamel flow and heat transfer problem. The Navier-Stokes equations, taking into account Maxwell's…

Numerical Analysis · Mathematics 2015-07-13 Vasile Marinca , Remus-Daniel Ene

In this paper, we present an efficient algorithm for solving a class of chance constrained optimization under non-parametric uncertainty. Our algorithm is built on the possibility of representing arbitrary distributions as functions in…

Robotics · Computer Science 2018-11-26 Bharath Gopalakrishnan , Arun Kumar Singh , K. Madhava Krishna , Dinesh Manocha

This paper develops a frequentist solution to the functional calibration problem, where the value of a calibration parameter in a computer model is allowed to vary with the value of control variables in the physical system. The need of…

Methodology · Statistics 2021-07-20 Rui Tuo , Shiyuan He , Arash Pourhabib , Yu Ding , Jianhua Z. Huang

Ideal systems like MHD and Euler flow may develop singularities in vorticity (w = curl v). Viscosity and resistivity are dissipative regularizations. We propose a minimal, local, conservative, nonlinear, dispersive regularization of…

Fluid Dynamics · Physics 2016-11-15 Govind S. Krishnaswami , Sonakshi Sachdev , Anantanarayanan Thyagaraja

We consider a two-dimensional MHD model describing the evolution of viscous, compressible and electrically conducting fluids under the action of vertical magnetic field without resistivity. Existence of global weak solutions is established…

Analysis of PDEs · Mathematics 2019-07-02 Yang Li , Yongzhong Sun

This paper derives error bounds for regression in continuous time over subsets of certain types of Riemannian manifolds.The regression problem is typically driven by a nonlinear evolution law taking values on the manifold, and it is cast as…

Dynamical Systems · Mathematics 2022-09-09 Nathan Powell , Jia Guo , Sai Tej Parachuri , John Burns , Boone Estes , Andrew Kurdila

This paper is concerned with a fourth order nonlinear dispersive partial differential equation for closed curve flow on a K\"ahler manifold. The main results is that the initial value problem has a solution locally in time if the K\"ahler…

Analysis of PDEs · Mathematics 2016-06-16 Eiji Onodera

The Holomorphic Embedding Load flow Method (HELM) employs complex analysis to solve the load flow problem. It guarantees finding the correct solution when it exists, and identifying when a solution does not exist. The method, however, is…

Optimization and Control · Mathematics 2020-02-27 Majid Heidarifar , Panagiotis Andrianesis , Michael Caramanis

This article is concerned with an approximate analytical solution for the time fractional Kudryashov Sinelshchikov equation by using the reproducing kernel Hilbert space method. The main tools of this method are reproducing kernel theory,…

Numerical Analysis · Mathematics 2024-12-19 Gayatri Das , S. Saha Ray

The evolution of piecewise constant distributions of a conserved quantity related to the frozen-in canonical vorticity in effectively two-dimensional incompressible ideal EMHD flows is analytically investigated by the Hamiltonian method.…

Plasma Physics · Physics 2007-05-23 V. P. Ruban , S. L. Senchenko

Data-driven dimensionality reduction methods such as proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) have proven to be useful for exploring complex phenomena within fluid dynamics and beyond. A well-known…

Fluid Dynamics · Physics 2022-12-27 Elena Marensi , Gökhan Yalnız , Björn Hof , Nazmi Burak Budanur