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Related papers: Regularized Stokeslet Surfaces

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We present a variation of the method of regularized Stokeslet (MRS) specialized for the case of forces and torques distributed over filaments in three dimensions. The new formulation is based on the exact solution of Stokes equation…

Numerical Analysis · Mathematics 2018-10-17 Ricardo Cortez

A linear stability analysis of an elastic surface immersed in a viscous fluid is presented. The coupled system is modeled using the method of regularized Stokeslets (MRS), a Lagrangian method for simulating fluid-structure interaction at…

Fluid Dynamics · Physics 2025-07-10 Dana Ferranti , Sarah D. Olson

We present a numerical method for computing the single layer (Stokeslet) and double layer (stresslet) integrals in Stokes flow. The method applies to smooth, closed surfaces in three dimensions, and achieves high accuracy both on and near…

Numerical Analysis · Mathematics 2019-03-22 Svetlana Tlupova , J. Thomas Beale

The method of regularized Stokeslets, based on the divergence-free exact solution to the equations of highly viscous flow due to a spatially-smoothed concentrated force, is widely employed in biological fluid mechanics. Many problems of…

Fluid Dynamics · Physics 2019-06-12 James Tyrrell , David J Smith , Rosemary J Dyson

The general system of images for regularized Stokeslets (GSIRS) developed by Cortez and Varela (2015) is used extensively to model Stokes flow phenomena such as microorganisms swimming near a boundary. Our collaborative team uses…

The method of regularised stokeslets is widely used in microscale biological fluid dynamics due to its ease of implementation, natural treatment of complex moving geometries, and removal of singular functions to integrate. The standard…

Numerical Analysis · Mathematics 2021-03-10 Meurig Gallagher , David Smith

Many problems in fluid dynamics are effectively modeled as Stokes flows - slow, viscous flows where the Reynolds number is small. Boundary integral equations are often used to solve these problems, where the fundamental solutions for the…

Numerical Analysis · Mathematics 2022-12-21 J. Thomas Beale , Christina Jones , Jillian Reale , Svetlana Tlupova

The method of regularized Stokeslets (MRS) is a numerical approach using regularized fundamental solutions to compute the flow due to an object in a viscous fluid where inertial effects can be neglected. The elastic object is represented as…

Numerical Analysis · Mathematics 2015-10-28 Varun Shankar , Sarah D. Olson

Slender-body approximations have been successfully used to explain many phenomena in low-Reynolds number fluid mechanics. These approximations typically use a line of singularity solutions to represent the flow. These singularities can be…

Fluid Dynamics · Physics 2021-09-17 Boan Zhao , Lyndon Koens

Flows in porous media in the low Reynolds number regime are often modeled by the Brinkman equations. Analytical solutions to these equations are limited to standard geometries. Finite volume or element schemes can be used in more…

Fluid Dynamics · Physics 2021-10-13 Suraj Kumar Kamarapu , Mehdi Jabbarzadeh , Henry Chien Fu

The method of regularized stokeslets is extensively used in biological fluid dynamics due to its conceptual simplicity and meshlessness. This simplicity carries a degree of cost in computational expense and accuracy because the number of…

Fluid Dynamics · Physics 2018-02-14 David J. Smith

We propose a variational regularization approach based on a multiscale representation called cylindrical shearlets aimed at dynamic imaging problems, especially dynamic tomography. The intuitive idea of our approach is to integrate a…

Numerical Analysis · Mathematics 2025-08-05 Tatiana A. Bubba , Tommi Heikkilä , Demetrio Labate , Luca Ratti

Regularization is used in many different areas of optimization when solutions are sought which not only minimize a given function, but also possess a certain degree of regularity. Popular applications are image denoising, sparse regression…

Optimization and Control · Mathematics 2021-11-15 Bennet Gebken , Katharina Bieker , Sebastian Peitz

Some prominent discretisation methods such as finite elements provide a way to approximate a function of $d$ variables from $n$ values it takes on the nodes $x_i$ of the corresponding mesh. The accuracy is $n^{-s_a/d}$ in $L^2$-norm, where…

Numerical Analysis · Mathematics 2024-07-19 Camille Pouchol , Marc Hoffmann

We prove a novel method for the embedding of a 3-fold rotationally symmetric sphere-type mesh onto a subset of the plane with 3-fold rotational symmetry. The embedding is free-boundary with the only additional constraint on the image set is…

Computational Geometry · Computer Science 2024-06-12 Tom Gilat , Ben Gilat

Boundary integral equation methods are widely used in the solution of many partial differential equations. The kernels that appear in these surface integrals are nearly singular when evaluated near the boundary, and straightforward…

Numerical Analysis · Mathematics 2025-07-02 Joseph Siebor , Svetlana Tlupova

We study in this paper a smoothness regularization method for functional linear regression and provide a unified treatment for both the prediction and estimation problems. By developing a tool on simultaneous diagonalization of two positive…

Statistics Theory · Mathematics 2012-11-13 Ming Yuan , T. Tony Cai

In this paper we consider finite element approaches to computing the mean curvature vector and normal at the vertices of piecewise linear triangulated surfaces. In particular, we adopt a stabilization technique which allows for first order…

Numerical Analysis · Mathematics 2017-03-17 Mirza Cenanovic , Peter Hansbo , Mats G. Larson

In the given paper the algorithm describing original and universal principles of a triangulation of a smooth molecular surface: solvent excluding solvent (SES), received by primary and secondary rolling, and solvent accessible surface (SAS)…

Chemical Physics · Physics 2013-03-19 Oleg Kupervasser , N. E. Wanner

There is growing body of learning problems for which it is natural to organize the parameters into matrix, so as to appropriately regularize the parameters under some matrix norm (in order to impose some more sophisticated prior knowledge).…

Machine Learning · Computer Science 2010-10-19 Sham M. Kakade , Shai Shalev-Shwartz , Ambuj Tewari
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