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Self-propelled colloidal swimmers move by pushing the adjacent fluid backwards. The resulting motion of an asymmetric body depends on the profile of pushing velocity over its surface. We describe a method of predicting the motion arising…

Soft Condensed Matter · Physics 2019-07-18 Thomas A. Witten , Aaron Mowitz

The use of the defect profile instead of the experimentally observed velocity profile for the search for similarity parameters has become firmly imbedded in the turbulent boundary layer literature. However, a search of the literature…

Fluid Dynamics · Physics 2015-10-20 David Weyburne

We consider the Laplace equation in the exterior of a thin filament in $\mathbb{R}^3$ and perform a detailed decomposition of a notion of slender body Neumann-to-Dirichlet (NtD) and Dirichlet-to-Neumann (DtN) maps along the filament…

Analysis of PDEs · Mathematics 2024-02-27 Laurel Ohm

In this paper, we study local regularity of the solutions to the Stokes equations near a curved boundary under no-slip or Navier boundary conditions. We extend previous boundary estimates near a flat boundary to that near a curved boundary,…

Analysis of PDEs · Mathematics 2025-10-23 Hui Chen , Su Liang , Tai-Peng Tsai

Riblets are a well-known passive drag reduction technique with the potential for as much as 9% reduction in the frictional drag force in laboratory settings, and proven benefits for large scale aircraft. However, less information is…

Fluid Dynamics · Physics 2024-09-10 Shuangjiu Fu , Shabnam Raayai-Ardakani

For a sperm cell-like flagellated swimmer in an unbounded domain, several numerical models of different fidelity are considered based on the Stokes flow approximation. The models include a Regularised Stokeslet Method and a 3D Finite…

Fluid Dynamics · Physics 2018-10-02 C. Rorai , M. Zaitsev , S. Karabasov

The dynamics of geometrically non-linear flexible filaments play an important role in a host of biological processes, from flagella-driven cell transport to the polymeric structure of complex fluids. Such problems have historically been…

In a recent paper [arXiv:1406.1320] Paris has made several comments concerning the author's recent work on the exactification of Stirling's approximation for the logarithm of the gamma function, $\ln \Gamma(z)$. Despite acknowledging that…

Classical Analysis and ODEs · Mathematics 2018-08-10 Victor Kowalenko

A model for the motion of slender vortex filaments is extended to include the effect of gravity. The model, initially introduced by Callegari and Ting (SIAM, J. of App. Math., (1978), vol. 35, pp. 148-175), is based on a matched asymptotic…

Fluid Dynamics · Physics 2024-05-16 Marie Rodal , Daniel Margerit , Rupert Klein

Accurate and economical modeling of near-surface transport processes is a standing challenge for various engineering and atmospheric boundary-layer flows. In this paper, we address this challenge by utilizing a stochastic one-dimensional…

Fluid Dynamics · Physics 2021-12-01 Marten Klein , Heiko Schmidt , David O. Lignell

We explore one-point and two-point statistics of the Navier-Stokes-alpha-beta regularization model at moderate Reynolds number in homogeneous isotropic turbulence. The results are compared to the limit cases of the Navier-Stokes-alpha model…

Fluid Dynamics · Physics 2014-08-14 Denis F. Hinz , Tae-Yeon Kim , Eliot Fried

A number of important observables exhibit logarithms in their perturbative description that are induced by emissions at widely separated rapidities. These include transverse-momentum ($q_T$) logarithms, logarithms involving heavy-quark or…

High Energy Physics - Phenomenology · Physics 2019-04-24 Markus A. Ebert , Ian Moult , Iain W. Stewart , Frank J. Tackmann , Gherardo Vita , Hua Xing Zhu

We study low-rank tensor-product B-spline (TPBS) models for regression tasks and investigate Dirichlet energy as a measure of smoothness. We show that TPBS models admit a closed-form expression for the Dirichlet energy, and reveal scenarios…

Machine Learning · Computer Science 2026-01-21 Paris A. Karakasis , Nicholas D. Sidiropoulos

B-spline models are a powerful way to represent scientific data sets with a functional approximation. However, these models can suffer from spurious oscillations when the data to be approximated are not uniformly distributed. Model…

Numerical Analysis · Mathematics 2023-01-04 David Lenz , Raine Yeh , Vijay Mahadevan , Iulian Grindeanu , Tom Peterka

To reduce the x-ray dose in computerized tomography (CT), many constrained optimization approaches have been proposed aiming at minimizing a regularizing function that measures lack of consistency with some prior knowledge about the object…

Medical Physics · Physics 2017-04-05 Edgar Garduño , Gabor T. Herman

Semiflexible slender filaments are ubiquitous in nature and cell biology, including in the cytoskeleton, where reorganization of actin filaments allows the cell to move and divide. Most methods for simulating semiflexible inextensible…

Numerical Analysis · Mathematics 2023-05-03 Ondrej Maxian , Brennan Sprinkle , Aleksandar Donev

Single-phase Stokes flow problems with prescribed boundary conditions can be formulated in terms of a boundary regularized integral equation that is completely free of singularities that exist in the traditional formulation. The usual…

Computational Physics · Physics 2019-02-11 Q. Sun , E. Klaseboer , B. C. Khoo , D. Y. C. Chan

The dynamics of a flexible filament sedimenting in a viscous fluid are explored analytically and numerically. Compared to the well-studied case of sedimenting rigid rods, the introduction of filament compliance is shown to cause a…

Fluid Dynamics · Physics 2013-11-04 Lei Li , Harishankar Manikantan , David Saintillan , Saverio E. Spagnolie

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

Advances in the expressivity of pretrained models have increased interest in the design of adaptation protocols which enable safe and effective transfer learning. Going beyond conventional linear probing (LP) and fine tuning (FT)…

Machine Learning · Computer Science 2023-03-24 Puja Trivedi , Danai Koutra , Jayaraman J. Thiagarajan
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