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Particle-based methods are a practical tool in computational fluid dynamics, and novel types of methods have been proposed. However, widely developed Lagrangian-type formulations suffer from the nonuniform distribution of particles, which…

Fluid Dynamics · Physics 2025-03-26 Takeharu Matsuda , Satoshi Ii

We consider the problem of finding optimal shapes of fluid domains. The fluid obeys the Navier--Stokes equations. Inside a holdall container we use a phase field approach using diffuse interfaces to describe the domain of free flow. We…

Optimization and Control · Mathematics 2014-05-15 Harald Garcke , Claudia Hecht , Michael Hinze , Christian Kahle

We present a new meshless method for scalar diffusion equations which is motivated by their compatible discretizations on primal-dual grids. Unlike the latter though, our approach is truly meshless because it only requires the graph of…

Numerical Analysis · Mathematics 2016-10-21 Nathaniel Trask , Mauro Perego , Pavel Bochev

Measuring scattered light is central to many laser-based gas diagnostic techniques, e.g., coherent anti-Stokes Raman spectroscopy (CARS) and filtered Rayleigh scattering (FRS). To produce quantitative measurements with such techniques, a…

Computational Physics · Physics 2020-05-18 Gregory J. Hunt , Cody R. Ground , Robin L. Hunt

We present a scheme implementing an a posteriori refinement strategy in the context of a high-order meshless method for problems involving point singularities and fluid-solid interfaces. The generalized moving least squares (GMLS)…

Computational Physics · Physics 2019-07-24 Wei Hu , Nathaniel Trask , Xiaozhe Hu , Wenxiao Pan

For finite-dimensional problems, stochastic approximation methods have long been used to solve stochastic optimization problems. Their application to infinite-dimensional problems is less understood, particularly for nonconvex objectives.…

Optimization and Control · Mathematics 2021-01-14 Caroline Geiersbach , Teresa Scarinci

Wall-based spanwise forcing has been experimentally used with success by Auteri et al. (Phys. Fluids vol. 22, 2010, 115103) to obtain large reductions of turbulent skin-friction drag and considerable energy savings in a pipe flow. The…

Fluid Dynamics · Physics 2024-01-23 Emanuele Gallorini , Maurizio Quadrio

A semi-implicit fractional-step method that uses a staggered node layout and radial basis function-finite differences (RBF-FD) to solve the incompressible Navier-Stokes equations is developed. Polyharmonic splines (PHS) with polynomial…

Fluid Dynamics · Physics 2022-12-15 Tianyi Chu , Oliver T. Schmidt

This paper presents a simple, efficient, and high-order accurate sliding-mesh interface approach to the spectral difference (SD) method. We demonstrate the approach by solving the two-dimensional compressible Navier-Stokes equations on…

Numerical Analysis · Mathematics 2015-05-20 Bin Zhang , Chunlei Liang

The permeability of complex porous materials can be obtained via direct flow simulation, which provides the most accurate results, but is very computationally expensive. In particular, the simulation convergence time scales poorly as…

We propose a stochastic variance-reduced cubic regularized Newton method for non-convex optimization. At the core of our algorithm is a novel semi-stochastic gradient along with a semi-stochastic Hessian, which are specifically designed for…

Machine Learning · Computer Science 2018-02-14 Dongruo Zhou , Pan Xu , Quanquan Gu

In this paper, we propose a new nonuniform mesh method to simulate acoustic scattering problems in two dimensional periodic structures with non-periodic incident fields numerically. As existing methods are difficult to extend to higher…

Numerical Analysis · Mathematics 2022-03-14 Tilo Arens , Ruming Zhang

There are many application papers that solve elliptic boundary value problems by meshless methods, and they use various forms of generalized stiffness matrices that approximate derivatives of functions from values at scattered nodes…

Numerical Analysis · Mathematics 2016-12-23 Robert Schaback

The non-smooth finite-sum minimization is a fundamental problem in machine learning. This paper develops a distributed stochastic proximal-gradient algorithm with random reshuffling to solve the finite-sum minimization over time-varying…

Optimization and Control · Mathematics 2022-10-11 Xia Jiang , Xianlin Zeng , Jian Sun , Jie Chen , Lihua Xie

We consider an elliptic partial differential equation in non-divergence form with a random diffusion matrix and random forcing term. To address this, we propose a mixed-type continuous finite element discretization in the physical domain,…

Numerical Analysis · Mathematics 2025-12-04 Amireh Mousavi

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

We introduce a geometric stencil selection algorithm for Laplacian in 3D that significantly improves octant-based selection considered earlier. The goal of the algorithm is to choose a small subset from a set of irregular points surrounding…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov , Dang Thi Oanh , Ngo Manh Tuong

In this paper, we propose a novel unstructured mesh control volume method to deal with the space fractional derivative on arbitrarily shaped convex domains, which to the best of our knowledge is a new contribution to the literature.…

Numerical Analysis · Mathematics 2024-12-20 Libo Feng , Fawang Liu , Ian Turner

We suggest a method for simultaneously generating high order quadrature weights for integrals over Lipschitz domains and their boundaries that requires neither meshing nor moment computation. The weights are determined on pre-defined…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov , Bruno Degli Esposti

Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for large scattered (unordered) datasets in d-dimensional space. This approach is useful for a higher…

Numerical Analysis · Computer Science 2018-06-21 Zuzana Majdisova , Vaclav Skala