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Numerical simulation of the complex plasma dynamics associated with high power, high frequency microwave breakdown at high pressures, leading to the formation of filamentary plasma structures such as self-organized plasma arrays, is a…

Plasma Physics · Physics 2025-05-13 Pratik Ghosh , Bhaskar Chaudhury

We present two new Lagrangian methods for hydrodynamics, in a systematic comparison with moving-mesh, SPH, and stationary (non-moving) grid methods. The new methods are designed to simultaneously capture advantages of both smoothed-particle…

Cosmology and Nongalactic Astrophysics · Physics 2015-12-15 Philip F. Hopkins

We present a new approach to discretizing shape optimization problems that generalizes standard moving mesh methods to higher-order mesh deformations and that is naturally compatible with higher-order finite element discretizations of…

Numerical Analysis · Mathematics 2017-06-13 A. Paganini , F. Wechsung , P. E. Farrell

This paper studies adaptive first-order least-squares finite element methods for second-order elliptic partial differential equations in non-divergence form. Unlike the classical finite element method which uses weak formulations of PDEs…

Numerical Analysis · Mathematics 2019-06-28 Weifeng Qiu , Shun Zhang

Model-free deep reinforcement learning (DRL) methods suffer from poor sample efficiency. To overcome this limitation, this work introduces an adaptive reduced-order-model (ROM)-based reinforcement learning framework for active flow control.…

Machine Learning · Computer Science 2026-04-08 Zesheng Yao , Zhen-Hua Wan , Canjun Yang , Qingchao Xia , Mengqi Zhang

Parametric model order reduction (pMOR) is a powerful tool for accelerating finite element (FE) simulations while maintaining parametric dependencies. For geometric parameters, pMOR by matrix interpolation is a well-suited approach because…

Numerical Analysis · Mathematics 2025-12-18 Sebastian Resch-Schopper , Romain Rumpler , Gerhard Müller

This paper presents a proper generalized decomposition (PGD) based reduced-order model of hierarchical deep-learning neural networks (HiDeNN). The proposed HiDeNN-PGD method keeps both advantages of HiDeNN and PGD methods. The automatic…

Numerical Analysis · Mathematics 2022-01-12 Lei Zhang , Ye Lu , Shaoqiang Tang , Wing Kam Liu

This work introduces an adaptive mesh refinement technique for hierarchical hybrid grids with the goal to reach scalability and maintain excellent performance on massively parallel computer systems. On the block structured hierarchical…

Numerical Analysis · Mathematics 2025-08-11 Benjamin Mann , Ulrich Rüde

We develop new adaptive alternative weighted essentially non-oscillatory (A-WENO) schemes for hyperbolic systems of conservation laws. The new schemes employ the recently proposed local characteristic decomposition based central-upwind…

Numerical Analysis · Mathematics 2022-11-15 Alina Chertock , Shaoshuai Chu , Alexander Kurganov

Accurately, efficiently, and stably computing complex fluid flows and their evolution near solid boundaries over long horizons remains challenging. Conventional numerical solvers require fine grids and small time steps to resolve near-wall…

Machine Learning · Computer Science 2026-03-18 Chenglin Li , Hang Xu , Jianting Chen , Yanfei Zhang

A stable numerical solution of the steady Stokes problem requires compatibility between the choice of velocity and pressure approximation that has traditionally proven problematic for meshless methods. In this work, we present a…

Numerical Analysis · Mathematics 2016-11-15 Nathaniel Trask , Martin Maxey , Xiaozhe Hu

Accurate high-speed flow simulations of practical interest require numerical methods with high-resolution properties. In this paper, we present an extension and demonstration of the high-accuracy Gradient-based reconstruction and…

This paper develops high-order accurate entropy stable (ES) adaptive moving mesh finite difference schemes for the two- and three-dimensional special relativistic hydrodynamic (RHD) and magnetohydrodynamic (RMHD) equations, which is the…

Numerical Analysis · Mathematics 2022-02-28 Junming Duan , Huazhong Tang

Local meshless methods obtain higher convergence rates when RBF approximations are augmented with monomials up to a given order. If the order of the approximation method is spatially variable, the numerical solution is said to be p-refined.…

Numerical Analysis · Mathematics 2022-01-28 Mitja Jančič , Jure Slak , Gregor Kosec

We present a computationally efficient approach to solve the time-dependent Kohn-Sham equations in real-time using higher-order finite-element spatial discretization, applicable to both pseudopotential and all-electron calculations. To this…

Computational Physics · Physics 2019-10-02 Bikash Kanungo , Vikram Gavini

The smoothed particle hydrodynamics (SPH) method has been widely used to simulate incompressible and slightly compressible fluid flows. Adaptive refinement strategies to dynamically increase the resolution of the particles to capture sharp…

Fluid Dynamics · Physics 2024-07-31 Abhinav Muta , Pawan Negi , Prabhu Ramachandran

We develop a block-structured solver for high-fidelity simulation of flows in complex geometries, based on overlapping (Chimera) meshes. The key components of the algorithm are a baseline dissipation-free central discretization and…

Fluid Dynamics · Physics 2025-06-09 Andrea Di Mascio , Sergio Pirozzoli

This work presents a method to adaptively refine reduced-order models \emph{a posteriori} without requiring additional full-order-model solves. The technique is analogous to mesh-adaptive $h$-refinement: it enriches the reduced-basis space…

Numerical Analysis · Computer Science 2015-04-16 Kevin Carlberg

In this paper, we introduce a novel approach that combines multiresolution (MR) techniques with the flux reconstruction (FR) method to accurately and effciently simulate compressible flows. We achieve further enhancements in effciency…

Fluid Dynamics · Physics 2023-06-21 Yixuan Lian , Jinsheng Cai , Shucheng Pan

The overarching goal of this work is to develop an accurate, robust, and stable methodology for finite deformation modeling using strong-form peridynamics (PD) and the correspondence modeling framework. We adopt recently developed methods…

Numerical Analysis · Mathematics 2020-04-27 Masoud Behzadinasab , Nathaniel Trask , Yuri Bazilevs