流体动力学

We propose a graph-based, multi-fidelity learning framework for the prediction of stationary Navier--Stokes solutions in non-parametrized two-dimensional geometries. The method is designed to guide the learning process through successive…

Wind farm parameterizations are crucial for quantifying the wind-farm atmosphere interaction, where wind turbines are typically modeled as elevated momentum sinks and sources of turbulence kinetic energy (TKE). These quantities must be…

Small bubbles rising in a chain can self-organize into regular patterns upon reaching a liquid's free surface. This phenomenon is investigated through direct numerical simulations. By varying the bubble release period, distinct branching…

Anomalous dissipation, the persistence of a finite mean kinetic energy dissipation as the Reynolds number tends to infinity, occurs in flows with sufficiently spatially rough velocity fields. Compressible turbulence adds further anomalous…

Rivulets and droplets are naturally appearing shapes when small amounts of liquid are deposited on a partially wettable substrate. Here we study, by means of numerical simulations, the dewetting dynamics of a ring-rivulet on substrates with…

This study investigates the flow evolution around a sinusoidal pitching NACA 0012 airfoil, defined by the National Advisory Committee for Aeronautics (NACA), undergoing deep dynamic stall using a wall-resolved large eddy simulation (LES)…

A numerical investigation of the flow evolution over a pitching NACA 0012 airfoil incurring in deep dynamic stall phenomena is presented. The experimental data at Reynolds number Re = 135 000 and reduced frequency k = 0.1, provided by Lee…

A physics-based machine learning framework is developed to compute the aerodynamic forces and moment for a pitching NACA0012 airfoil incurring in light and deep dynamic stall. Three deep neural network frameworks of increasing complexity…

We investigate the effect of rotor velocity induction on the distribution of particles impinging on rotor blades and model the delayed response of a particle to the rotor-induced velocity field. We consider as reference a wind turbine rotor…

Variational multiscale (VMS) methods offer a robust framework for handling under-resolved flow scales without resorting to problem-specific turbulence models. Here, we propose and assess a dynamic, term-by-term VMS stabilized formulation…

The effect of Kolmogorov-size spherical particles on homogeneous and isotropic turbulence is investigated using particle-resolved direct numerical simulations at a Taylor-scale Reynolds number of $150$. Four monodisperse suspensions of…

We propose a modified suspension balance model (SBM) for the flow of red blood cells (RBCs) and other deformable particle suspensions in confined geometries. Specifically, the method includes the hydrodynamic lift force generated by…

Turbulent flows laden with small bubbles are ubiquitous in many natural and industrial environments. From the point of view of numerical modeling, to be able to handle a very large number of small bubbles in direct numerical simulations,…

Flapping wings are the primary means by which dragonflies generate forces, but they are susceptible to damage due to their inherent fragility. The damage results in a reduction in wing area and a distortion of the original wing, which in…

We investigate how the rotational nature of turbulence affects learned mappings between quantities governed by the Navier-Stokes equations. By varying the degree of anisotropy in a turbulence dataset, we explore how statistical symmetry…

We propose a Navier-Stokes-driven analysis of the mean and fluctuating wall shear stress (WSS) applied to turbulent channel flow data from direct numerical simulations at friction Reynolds numbers up to $Re_\tau\approx 2000$. Starting from…

In these notes, we emphasize Theorems rather than Theories concerning turbulent fluid motion. Such theorems can be viewed as constraints on the theoretical predictions and expectations of some of the greatest scientific minds of the 20th…

Micro-swimmer locomotion in heterogeneous media is increasingly relevant in biological physics due to the prevalence of microorganisms in complex environments. A model for such porous media is the Brinkman fluid which accounts for a sparse…

Physics-Informed Neural Networks (PINNs) solve forward PDEs by minimizing residual losses from the governing equations with initial and boundary conditions, but they often struggle with discontinuities such as shocks. In contrast, finite…

Active components incorporated in materials generate motion by inducing conformational changes in response to external fields. Magnetic fields are particularly interesting as they can actuate materials remotely. Millimeter-sized ferrofluid…