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In this study, we propose a graph neural network (GNN) model for efficiently predicting the flow behavior of non-Newtonian fluids with free surface dynamics. The numerical analysis of non-Newtonian fluids presents significant challenges, as…

Fluid Dynamics · Physics 2025-09-30 Hyo-Jin Kim , Jaekwang Kim , Hyung-Jun Park

We consider fluid flows for which the linearized Navier-Stokes operator is strongly non-normal. The responses of such flows to external perturbations are spanned by a generically very large number of non-orthogonal eigenmodes. They are…

Fluid Dynamics · Physics 2025-07-11 Yves-Marie Ducimetière , François Gallaire

We present here a new stochastic modelling in the constitution of fluid flow reduced-order models. This framework introduces a spatially inhomogeneous random field to represent the unresolved small-scale velocity component. Such a…

Fluid Dynamics · Physics 2017-09-20 Valentin Resseguier , Etienne Mémin , Dominique Heitz , Bertrand Chapron

Proper-orthogonal decomposition (POD) based reduced-order models (ROM) of structurally dominant fluid flow can support a wide range of engineering applications. Yet, although they perform well for unsteady laminar flows, their…

Fluid Dynamics · Physics 2025-03-11 Haroon Imtiaz , Imran Akhtar , Muhammad R. Hajj

Modeling transition-continuum hypersonic flows poses significant challenges due to thermodynamic nonequilibrium and the associated breakdown of the continuum assumption. Standard continuum models such as the Navier-Stokes equations are…

Fluid Dynamics · Physics 2025-06-18 Mikolaj Kryger , Jonathan F. MacArt

Reduced-order models are central to motion planning and control of quadruped robots, yet existing templates are often hand-crafted for a specific locomotion modality. This motivates the need for automatic methods that extract task-specific,…

Robotics · Computer Science 2026-01-14 Gioele Buriani , Jingyue Liu , Maximilian Stölzle , Cosimo Della Santina , Jiatao Ding

We study the relaxation of a highly collisional, ultracold but nondegenerate gas of polar molecules. Confined within a harmonic trap, the gas is subject to fluid-gaseous coupled dynamics that lead to a breakdown of first-order…

Quantum Gases · Physics 2024-06-12 Reuben R. W. Wang , Daniel Messenger

Projection-based model reduction has become a popular approach to reduce the cost associated with integrating large-scale dynamical systems so they can be used in many-query settings such as optimization and uncertainty quantification. For…

Numerical Analysis · Mathematics 2020-08-26 Han Gao , Jian-Xun Wang , Matthew J. Zahr

Turbulent fluid flows exhibit a complex small-scale structure with frequently occurring extreme velocity gradients. Particles probing such swirling and straining regions respond with an intricate shape-dependent orientational dynamics,…

Fluid Dynamics · Physics 2020-11-30 Leonhard A. Leppin , Michael Wilczek

We investigate the break-up of Newtonian/viscoelastic droplets in a viscoelastic/Newtonian matrix under the hydrodynamic conditions of a confined shear flow. Our numerical approach is based on a combination of Lattice-Boltzmann models (LBM)…

Soft Condensed Matter · Physics 2016-11-15 Anupam Gupta , Mauro Sbragaglia

Non-affine parametric dependencies, nonlinearities and advection-dominated regimes of the model of interest can result in a slow Kolmogorov n-width decay, which precludes the realization of efficient reduced-order models based on linear…

Numerical Analysis · Mathematics 2022-03-02 Francesco Romor , Giovanni Stabile , Gianluigi Rozza

The ability to robustly and efficiently control the dynamics of nonlinear systems lies at the heart of many current technological challenges, ranging from drug delivery systems to ensuring flight safety. Most such scenarios are too complex…

Fluid Dynamics · Physics 2021-02-16 Radu Cimpeanu , Susana N. Gomes , Demetrios T. Papageorgiou

Maxwell models for viscoelastic flows are famous for their potential to unify elastic motions of solids with viscous motions of liquids in the continuum mechanics perspective. But the usual Maxwell models allow one to define well motions…

Numerical Analysis · Mathematics 2022-12-06 Sébastien Boyaval

A robust finite volume method for viscoelastic flow analysis on general unstructured meshes is developed. It is built upon a general-purpose stabilization framework for high Weissenberg number flows. The numerical framework provides full…

Fluid Dynamics · Physics 2020-12-08 Matthias Niethammer , Holger Marschall , Christian Kunkelmann , Dieter Bothe

The present paper develops a reduced-order model capable of modeling unsteady aerodynamic loads in the transonic regime using system identification techniques. The computational fluid dynamics (CFD) calculations are based on the Euler…

Fluid Dynamics · Physics 2023-07-20 Ana Cristina Neves Carloni , João Luiz F. Azevedo

The paper presents a Projection-Based Reduced-Order Model for simulations of high Reynolds turbulent flows. The PBROM are enhanced by incorporating various models of turbulent viscosity and residual closures to model the effects of…

Computational Engineering, Finance, and Science · Computer Science 2021-05-25 My Ha Dao , Hoang Huy Nguyen

We establish the long-time existence of large-data weak solutions to a system of nonlinear partial differential equations. The system of interest governs the motion of non-Newtonian fluids described by a simplified viscoelastic rate-type…

Analysis of PDEs · Mathematics 2017-10-02 Miroslav Bulíček , Josef Málek , Vít Průša , Endre Süli

We present and analyse a numerical method for understanding the low-inertia dynamics of an open, inextensible viscoelastic rod - a long and thin three dimensional object - representing the body of a long, thin microswimmer. Our model allows…

Numerical Analysis · Mathematics 2020-05-07 Thomas Ranner

An alternative step in understanding the flows of near wall drag-reducing turbulence can be examining the flow in a well-organized streamwise vortex with a laminar background. Herein, we studied the flow behaviors of the Giesekus…

Fluid Dynamics · Physics 2019-09-11 Tomohiro Nimura , Takuya Kawata , Takahiro Tsukahara

The spatiotemporal dynamics of turbulent flows is chaotic and difficult to predict. This makes the design of accurate and stable reduced-order models challenging. The overarching objective of this paper is to propose a nonlinear…

Fluid Dynamics · Physics 2022-11-23 Alberto Racca , Nguyen Anh Khoa Doan , Luca Magri