Universal Translational and Rotational Mobility Expressions of Phoretic and Self-phoretic Particles with Arbitrary Interaction PotentialsThe mobility of externally-driven phoretic propulsion of particles is evaluated by simultaneously solving the solute conservation equation, interaction potential equation, and the modified Stokes…Arkava Ganguly, Souradeep Roychowdhury, Ankur Gupta·Feb 29, 2024SaveLearn
Graphics Processing Unit/Artificial Neural Network-accelerated large-eddy simulation of turbulent combustion: Application to swirling premixed flamesWithin the scope of reacting flow simulations, the real-time direct integration (DI) of stiff ordinary differential equations (ODE) for the computation of chemical kinetics stands as the primary…Min Zhang, Runze Mao, Han Li et al.·Feb 29, 2024SaveLearn
A Priori Uncertainty Quantification of Reacting Turbulence Closure Models using Bayesian Neural NetworksWhile many physics-based closure model forms have been posited for the sub-filter scale (SFS) in large eddy simulation (LES), vast amounts of data available from direct numerical simulation (DNS)…Graham Pash, Malik Hassanaly, Shashank Yellapantula·Feb 28, 2024SaveLearn
A comparative computational study of different formulations of the compressible Euler equations for mesoscale atmospheric flows in a finite volume frameworkWe consider three conservative forms of the mildly compressible Euler equations, called CE1, CE2 and CE3, with the goal of understanding which leads to the most accurate and robust pressure-based…Michele Girfoglio, Annalisa Quaini, Gianluigi Rozza·Feb 28, 2024SaveLearn
Data-driven nonlinear turbulent flow scaling with Buckingham Pi variablesNonlinear machine learning for turbulent flows can exhibit robust performance even outside the range of training data. This is achieved when machine-learning models can accommodate scale-invariant…Kai Fukami, Susumu Goto, Kunihiko Taira·Feb 28, 2024SaveLearn
Fast buffet onset prediction and optimization method based on a pre-trained flowfield prediction modelThe transonic buffet is a detrimental phenomenon occurs on supercritical airfoils and limits aircraft's operating envelope. Traditional methods for predicting buffet onset rely on multiple…Yunjia Yang, Runze Li, Yufei Zhang et al.·Feb 27, 2024SaveLearn
Neural Physics: Using AI Libraries to Develop Physics-Based Solvers for Incompressible Computational Fluid DynamicsNumerical discretisations of partial differential equations (PDEs) can be written as discrete convolutions, which, themselves, are a key tool in AI libraries and used in convolutional neural networks…Boyang Chen, Claire E. Heaney, Christopher C. Pain·Feb 27, 2024SaveLearn
3D Printing in Microfluidics: Experimental Optimization of Droplet Size and Generation Time through Flow Focusing, Phase, and Geometry VariationDroplet-based microfluidics systems have become widely used in recent years thanks to their advantages, varying from the possibility of handling small fluid volumes to directly synthesizing and…Adam Britel, Giulia Tomagra, Pietro Aprà et al.·Feb 27, 2024SaveLearn
Onset of Air Entrainment by a smooth plunging jet under atmospheric pressureThe onset of air entrainment by a smooth vertical liquid jet impacting a pool of the same liquid has been experimentally determined. The ranges of parameters covered complement those considered by…Alain Cartellier, Juan Lasheras·Feb 27, 2024SaveLearn
Non-monotonic surface tension leads to spontaneous symmetry breaking in a binary evaporating dropThe evaporation of water/1,2-hexanediol binary drops shows remarkable segregation dynamics, with hexanediol-rich spots forming at the rim, thus breaking axisymmetry. While the segregation of…Christian Diddens, Pim J. Dekker, Detlef Lohse·Feb 27, 2024SaveLearn
Understanding the training of PINNs for unsteady flow past a plunging foil through the lens of input subdomain level loss function gradientsRecently immersed boundary method-inspired physics-informed neural networks (PINNs) including the moving boundary-enabled PINNs (MB-PINNs) have shown the ability to accurately reconstruct velocity…Rahul Sundar, Didier Lucor, Sunetra Sarkar·Feb 27, 2024SaveLearn
Aerodynamic Prediction of a CRM High-lift Configuration using a modified three equation turbulence modeAerodynamic simulations were carried out in the study presented in this paper focusing on the stall performance of the High-Lift Common Research Model obtained from the fourth AIAA High-Lift…Shaoguang Zhang, Haoran Li, Yufei Zhang·Feb 27, 2024SaveLearn
Mesh-Agnostic Decoders for Supercritical Airfoil Prediction and Inverse DesignMesh-agnostic models have advantages in terms of processing unstructured spatial data and incorporating partial differential equations. Recently, they have been widely studied for constructing…Runze Li, Yufei Zhang, Haixin Chen·Feb 27, 2024SaveLearn
Spatial Distribution of Inertial Particles in Turbulent Taylor-Couette FlowThis study investigates the spatial distribution of inertial particles in turbulent Taylor-Couette flow. Direct numerical simulations are performed using a one-way coupled Eulerian-Lagrangian…Hao Jiang, Zhi-ming Lu, Bo-fu Wang et al.·Feb 27, 2024SaveLearn
The influence of the vorticity-scalar correlation on mixingWe investigate the role of the correlation between a scalar quantity and the vorticity in two-dimensional mixing at infinite P\'eclet number. We assess, using a diffusivity independent mixing-norm,…Xi-Yuan Yin, Wesley Agoua, Tong Wu et al.·Feb 26, 2024SaveLearn
Three Carleman routes to the quantum simulation of classical fluidsWe discuss the Carleman approach to the quantum simulation of classical fluids, as applied to i) Lattice Boltzmann (CLB), ii) Navier-Stokes (CNS) and iii) Grad (CG) formulations of fluid dynamics.…Sauro Succi, Claudio Sanavio, Riccardo Scatamacchia et al.·Feb 26, 2024SaveLearn
High-fidelity velocity and concentration measurements of turbulent buoyant jetsAccurate models of turbulent buoyant flows are essential for the design of nuclear reactors thermal hydraulics and passive safety systems. However, available models fail to fully capture the physics…Valentina Valori, Sunming Qin, Victor Petrov et al.·Feb 26, 2024SaveLearn
Model-based deep reinforcement learning for accelerated learning from flow simulationsIn recent years, deep reinforcement learning has emerged as a technique to solve closed-loop flow control problems. Employing simulation-based environments in reinforcement learning enables a priori…Andre Weiner, Janis Geise·Feb 26, 2024SaveLearn
Scaling and flow profiles in magnetically confined liquid-in-liquid channelsFerrofluids kept in place by permanent magnet quadrupoles can act as liquid walls to surround a second non-magnetic inside, resulting in a liquid fluidic channel with diameter size ranging from mm…Arvind Arun Dev, Florencia Sacarelli, G Bagheri et al.·Feb 26, 2024SaveLearn
Development of a Generalizable Data-driven Turbulence Model: Conditioned Field Inversion and Symbolic RegressionThis paper addresses the issue of predicting separated flows with Reynolds-averaged Navier-Stokes (RANS) turbulence models, which are essential for many engineering tasks. Traditional RANS models…Chenyu Wu, Shaoguang Zhang, Yufei Zhang·Feb 26, 2024SaveLearn
Flow birefringence of cellulose nanocrystal suspensions in three-dimensional flow fields: revisiting the stress-optic lawThis study systematically investigates the flow birefringence of cellulose nanocrystal (CNC) suspensions. The aim is to clarify the importance of the stress component along the camera's optical axis…Kento Nakamine, Yuto Yokoyama, William Kai Alexander Worby et al.·Feb 26, 2024SaveLearn
New approach method for solving nonlinear differential equations of blood flow with nanoparticle in presence of magnetic fieldIn this paper, effect of physical parameters in presence of magnetic field on heat transfer and flow of third grade non-Newtonian Nanofluid in a porous medium with annular cross sectional…Seyed Morteza Hamzeh Pahnehkolaei, Amirreza Kachabi, Milad Heydari Sipey et al.·Feb 25, 2024SaveLearn
Evaporation of acoustically levitated bicomponent droplets: mass and heat transfer characteristicsEvaporation of multicomponent droplets is important in a wide range of applications, albeit complex, and requires a careful investigation. We experimentally and numerically investigate the…Yuki Wakata, Xing Chao, Chao Sun et al.·Feb 25, 2024SaveLearn
Forward and inverse modeling of depth-of-field effects in background-oriented schlierenWe report a novel "cone-ray" model of background-oriented schlieren (BOS) imaging that accounts for depth-of-field effects. Reconstructions of the density field performed with this model are far more…Joseph P. Molnar, Elijah J. LaLonde, Christopher S. Combs et al.·Feb 25, 2024SaveLearn
Optimal frequency resolution for spectral proper orthogonal decompositionWe demonstrate that accurate computation of the spectral proper orthogonal decomposition (SPOD) critically depends on the choice of frequency resolution. Using both artificially generated data and…Liam Heidt, Tim Colonius·Feb 24, 2024SaveLearn