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Related papers: A Low-rank Method for Parameter-dependent Fluid-st…

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Dispersion of low-density rigid particles with complex geometries is ubiquitous in both natural and industrial environments. We show that while explicit methods for coupling the incompressible Navier-Stokes equations and Newton's equations…

Computational Physics · Physics 2015-11-06 Uǧis Lācis , Kunihiko Taira , Shervin Bagheri

Parameter-dependent models arise in many contexts such as uncertainty quantification, sensitivity analysis, inverse problems or optimization. Parametric or uncertainty analyses usually require the evaluation of an output of a model for many…

Numerical Analysis · Mathematics 2018-10-22 Anthony Nouy

A unified fluid-structure interaction (FSI) formulation is presented for solid, liquid and mixed membranes. Nonlinear finite elements (FE) and the generalized-alpha scheme are used for the spatial and temporal discretization. The membrane…

Computational Physics · Physics 2018-12-31 Roger A. Sauer , Tobias Luginsland

This paper presents a method for the optimization of multi-component structures comprised of two and three materials considering large motion sliding contact and separation along interfaces. The structural geometry is defined by an explicit…

Optimization and Control · Mathematics 2017-01-24 Matthew Lawry , Kurt Maute

This paper proposes a dynamical Variable-separation method for solving parameter-dependent dynamical systems. To achieve this, we establish a dynamical low-rank approximation for the solutions of these dynamical systems by successively…

Numerical Analysis · Mathematics 2025-02-13 Liang Chen , Yaru Chen , Qiuqi Li , Tao Zhou

A variational formulation based on velocity and stress is developed for linear fluid-structure interaction (FSI) problems. The well-posedness and energy stability of this formulation are established. To discretize the problem, a…

Numerical Analysis · Mathematics 2024-04-23 Salim Meddahi

We present a parallel time-stepping method for fluid-structure interactions. The interaction between the incompressible Navier-Stokes equations and a hyperelastic solid is formulated in a fully monolithic framework. Discretization in space…

Numerical Analysis · Mathematics 2022-01-19 Nils Margenberg , Thomas Richter

Efficient structural reanalysis for high-rank modification plays an important role in engineering computations which require repeated evaluations of structural responses, such as structural optimization and probabilistic analysis. To…

Computational Engineering, Finance, and Science · Computer Science 2025-05-20 Wenxiong Li , Suiyin Chen , Huan Huang

(Rephrased) Non-conformance decision-making processes in high-precision manufacturing of engineering structures are often delayed due to numerical simulations that are needed for analyzing the defective parts and assemblies. Interfaces…

Numerical Analysis · Mathematics 2024-05-31 Kiran Sagar Kollepara

Time-dependent kinetic models are ubiquitous in computational science and engineering. The underlying integro-differential equations in these models are high-dimensional, comprised of a six--dimensional phase space, making simulations of…

Numerical Analysis · Mathematics 2025-06-23 Lukas Einkemmer , Katharina Kormann , Jonas Kusch , Ryan G. McClarren , Jing-Mei Qiu

In this work, we consider fluid-structure interaction simulation with nonlinear hyperelastic models in the solid part. We use a partitioned approach to deal with the coupled nonlinear fluid-structure interaction problems. We focus on…

Numerical Analysis · Mathematics 2013-12-20 Ulrich Langer , Huidong Yang

Low-rank approximation is a technique to approximate a tensor or a matrix with a reduced rank to reduce the memory required and computational cost for simulation. Its broad applications include dimension reduction, signal processing,…

Computational Physics · Physics 2019-06-25 Zhuogang Peng , Ryan G. McClarren , Martin Frank

We present an implementation of a fully variational formulation of an immersed method for fluid-structure interaction problems based on the finite element method. While typical implementation of immersed methods are characterized by the use…

Numerical Analysis · Mathematics 2015-04-10 Saswati Roy , Luca Heltai , Francesco Costanzo

In this paper we consider optimal control of nonlinear time-dependent fluid structure interactions. To determine a time-dependent control variable a BFGS algorithm is used, whereby gradient information is computed via a dual problem. To…

Optimization and Control · Mathematics 2020-08-11 L. Failer , T. Richter

In this document, some general results in approximation theory and matrix analysis with applications to sparse identification of time series models and nonlinear discrete-time dynamical systems are presented. The aforementioned theoretical…

Numerical Analysis · Mathematics 2021-08-04 Fredy Vides

The low-complexity assumption in linear systems can often be expressed as rank deficiency in data matrices with generalized Hankel structure. This makes it possible to denoise the data by estimating the underlying structured low-rank…

Systems and Control · Electrical Eng. & Systems 2021-11-10 Mingzhou Yin , Roy S. Smith

The low-rank approximation is a complexity reduction technique to approximate a tensor or a matrix with a reduced rank, which has been applied to the simulation of high dimensional problems to reduce the memory required and computational…

Computational Physics · Physics 2020-08-26 Zhuogang Peng , Ryan McClarren , Martin Frank

We consider a surface Stokes problem in stream function formulation on a simply connected oriented surface $\Gamma \subset \mathbb{R}^3$ without boundary. This formulation leads to a coupled system of two second order scalar surface partial…

Numerical Analysis · Mathematics 2019-10-22 Philip Brandner , Arnold Reusken

Low-rank approximation is a fundamental technique in modern data analysis, widely utilized across various fields such as signal processing, machine learning, and natural language processing. Despite its ubiquity, the mechanics of low-rank…

Machine Learning · Computer Science 2024-08-13 Jun Lu

Engineering and applied sciences use models of increasing complexity to simulate the behaviour of manufactured and physical systems. Propagation of uncertainties from the input to a response quantity of interest through such models may…

Computation · Statistics 2016-06-29 K. Konakli , B. Sudret