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Robust tensor principal component analysis (RTPCA) aims to separate the low-rank and sparse components from multi-dimensional data, making it an essential technique in the signal processing and computer vision fields. Recently emerging…

Computer Vision and Pattern Recognition · Computer Science 2025-01-20 Lanlan Feng , Ce Zhu , Yipeng Liu , Saiprasad Ravishankar , Longxiu Huang

A scalable algorithm for solving compact banded linear systems on distributed memory architectures is presented. The proposed method factorizes the original system into two levels of memory hierarchies, and solves it using parallel cyclic…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-02-05 Hang Song , Kristen V. Matsuno , Jacob R. West , Akshay Subramaniam , Aditya S. Ghate , Sanjiva K. Lele

FASTEST-3D is an MPI-parallel finite-volume flow solver based on block-structured meshes that has been developed at the University of Erlangen-Nuremberg since the early 1990s. It can be used to solve the laminar or turbulent incompressible…

Performance · Computer Science 2013-03-20 Christoph Scheit , Georg Hager , Jan Treibig , Stefan Becker , Gerhard Wellein

We use a data-driven approach to model a three-dimensional turbulent flow using cutting-edge Deep Learning techniques. The deep learning framework incorporates physical constraints on the flow, such as preserving incompressibility and…

Fluid Dynamics · Physics 2021-12-08 Mohammadreza Momenifar , Enmao Diao , Vahid Tarokh , Andrew D. Bragg

This paper presents a new method capable of reconstructing datasets with great precision and very low computational cost using a novel variant of the singular value decomposition (SVD) algorithm that has been named low-cost SVD (lcSVD).…

Computational Engineering, Finance, and Science · Computer Science 2023-11-20 Ashton Hetherington , Soledad Le Clainche

We employ a resolvent-based methodology to estimate velocity and pressure fluctuations within turbulent channel flows at friction Reynolds numbers of approximately 180, 550 and 1000 using measurements of shear stress and pressure at the…

Fluid Dynamics · Physics 2021-10-04 Filipe R. Amaral , André V. G. Cavalieri , Eduardo Martini , Peter Jordan , Aaron Towne

We present a discrete filter for subgrid-scale (SGS) model, coupled with the discretization corrected particle strength exchange (DC-PSE) method for the simulation of three-dimensional viscous incompressible flow, at high Reynolds flows.…

Fluid Dynamics · Physics 2024-08-13 Anas Obeidat

A resolvent-based reduced-order representation is used to capture time-averaged second-order statistics in turbulent channel flow. The recently-proposed decomposition of the resolvent operator into two distinct families related to the…

Fluid Dynamics · Physics 2020-08-26 Ryan M. McMullen , Kevin Rosenberg , Beverley J. McKeon

A data-driven algorithm is proposed that employs sparse data from velocity and/or scalar sensors to forecast the future evolution of three dimensional turbulent flows. The algorithm combines time-delayed embedding together with Koopman…

Fluid Dynamics · Physics 2026-03-04 George Papadakis , Shengqi Lu

This work applies Resolvent Analysis (RA) to study the dynamics of a hydrogen-air slot flame with a Reynolds number of 5500, a Karlovitz number of 20, and an equivalence ratio of 0.4. Direct Numerical Simulations (DNS) data are analyzed…

This paper presents a robust, adaptive numerical scheme for simulating high density ratio and high shear multiphase flows on locally refined Cartesian grids that adapt to the evolving interfaces and track regions of high vorticity. The…

Computational Physics · Physics 2019-09-04 Nishant Nangia , Boyce E. Griffith , Neelesh A. Patankar , Amneet Pal Singh Bhalla

We consider estimation and control of the cylinder wake at low Reynolds numbers. A particular focus is on the development of efficient numerical algorithms to design optimal linear feedback controllers when there are many inputs…

Optimization and Control · Mathematics 2022-05-11 Bo Jin , Simon J. Illingworth , Richard D. Sandberg

Three amplification mechanisms present in turbulent jets, namely lift-up, Kelvin-Helmholtz, and Orr, are characterized via global resolvent analysis and spectral proper orthogonal decomposition (SPOD) over a range of Mach numbers. The…

In this work, we develop a neural-physics solver based on finite volume method (FVM), namely NeuralFVM, for turbulent flows by implementing the standard $k$-$\omega$ model designed for efficient Graphics Processing Unit (GPU) execution. The…

We evaluate an efficient overset grid method for two-dimensional and three-dimensional particulate flows for small numbers of particles at finite Reynolds number. The rigid particles are discretised using moving overset grids overlaid on a…

Computational Physics · Physics 2017-05-24 A. R. Koblitz , S. Lovett , N. Nikiforakis , W. D. Henshaw

A Skeleton-stabilized ImmersoGeometric Analysis technique is proposed for incompressible viscous flow problems with moderate Reynolds number. The proposed formulation fits within the framework of the finite cell method, where essential…

Neural operators are promising surrogates for dynamical systems but when trained with standard L2 losses they tend to oversmooth fine-scale turbulent structures. Here, we show that combining operator learning with generative modeling…

This investigation aims to assess the effect of different types of actuator forcing on the feedback loop of an under-expanded Mach 1.27 planar impinging jet using a resolvent framework. To this end, we employ a Large Eddy Simulation…

Fluid Dynamics · Physics 2022-04-18 Qiong Liu , Chitrarth Prasad , Datta V. Gaitonde

The present paper addresses the numerical solution of turbulent flows with high-order discontinuous Galerkin methods for discretizing the incompressible Navier-Stokes equations. The efficiency of high-order methods when applied to…

Fluid Dynamics · Physics 2018-08-29 Niklas Fehn , Wolfgang A. Wall , Martin Kronbichler

The main objective of this work is to develop a unified framework that can be used as a lens to quantitatively assess and augment a wide range of coarse-grained models of turbulence, viz. large eddy simulations (LES), hybrid…

Fluid Dynamics · Physics 2023-01-25 Aniruddhe Pradhan , Karthik Duraisamy