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This 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 approach, with a fixed inner wall Reynolds…

Fluid Dynamics · Physics 2024-02-28 Hao Jiang , Zhi-ming Lu , Bo-fu Wang , Xiao-hui Meng , Jie Shen , Kai Leong Chong

Scale-resolving simulations of high Reynolds number incompressible flows are often limited by the Courant-Friedrichs-Lewy (CFL) stability restriction imposed by explicit time-stepping schemes, resulting in small time step sizes and long…

Fluid Dynamics · Physics 2026-04-20 Henrik Wüstenberg , Alexandra Liosi , Spencer J. Sherwin , Joaquim Peiró , David Moxey

Machine learning has great potential for efficient reconstruction and prediction of flow fields. However, existing datasets may have highly diversified labels for different flow scenarios, which are not applicable for training a model. To…

Fluid Dynamics · Physics 2023-11-28 Bonan Xu , Yuanye Zhou , Xin Bian

Torque-driven microscale swimming robots, or microrotors, hold significant potential in biomedical applications such as targeted drug delivery, minimally invasive surgery, and micromanipulation. This paper addresses the challenge of…

Optimization and Control · Mathematics 2024-09-10 Jake Buzhardt , Phanindra Tallapragada

Computational fluid dynamics (CFD) simulations play an important role in engineering science and applications, however, it is not applicable for problems requiring a large number of repeated calculations. Accordingly, many reduced-order…

Fluid Dynamics · Physics 2026-05-28 Shan Ding , Yongfu Tian , Rui Yang

The present study focuses on the assessment of the performance of a Finite Volume Method based, particle-resolved simulation approach to predict the flow through a model packed-bed consisting of 21 layers of spheres arranged in the body…

The behavior of particles driven through a narrow constriction is investigated in experiment and simulation. The system of particles adapts to the confining potentials and the interaction energies by a self-consistent arrangement of the…

Soft Condensed Matter · Physics 2008-10-15 P. Henseler , A. Erbe , M. Köppl , P. Leiderer , P. Nielaba

Efficient sampling from constraint manifolds, and thereby generating a diverse set of solutions for feasibility problems, is a fundamental challenge. We consider the case where a problem is factored, that is, the underlying nonlinear…

Robotics · Computer Science 2021-03-30 Joaquim Ortiz-Haro , Valentin N. Hartmann , Ozgur S. Oguz , Marc Toussaint

Size segregation in bedload transport is studied numerically with a coupled fluid-discrete element model. Starting from an initial deposit of small spherical particles on top of a large particle bed, the segregation dynamics of the bed is…

Spontaneous segregation of run-and-tumble particles with different velocities in microchannels is investigated by numerical simulations. Self-propelled particles are known to accumulate in the proximity of walls. Here we show how fast…

Soft Condensed Matter · Physics 2014-09-05 Andrea Costanzo , Jens Elgeti , Thorsten Auth , Gerhard Gompper , Marisol Ripoll

Simulation of turbulent flows at high Reynolds number is a computationally challenging task relevant to a large number of engineering and scientific applications in diverse fields such as climate science, aerodynamics, and combustion.…

Computational Physics · Physics 2020-10-06 Jaideep Pathak , Mustafa Mustafa , Karthik Kashinath , Emmanuel Motheau , Thorsten Kurth , Marcus Day

Understanding particle transport and localisation in porous channels, especially at moderate Reynolds numbers, is relevant for many applications ranging from water reclamation to biological studies. Recently, researchers experimentally…

Fluid Dynamics · Physics 2019-01-30 Mike Garcia , Baskar Ganapathysubramanian , Sumita Pennathur

Deep learning has revolutionized many industries by enabling models to automatically learn complex patterns from raw data, reducing dependence on manual feature engineering. However, deep learning algorithms are sensitive to input data, and…

Machine Learning · Computer Science 2025-07-21 Mert Sehri , Zehui Hua , Francisco de Assis Boldt , Patrick Dumond

Finite-size neutrally buoyant particles in a channel flow are known to accumulate at specific equilibrium positions or spots in the channel cross-section if the flow inertia is finite at the particle scale. Experiments in different conduit…

Fluid Dynamics · Physics 2018-10-23 Anupam Gupta , Pascale Magaud , Christine Lafforgue , Micheline Abbas

Quantum computational fluid dynamics (QCFD) offers a promising alternative to classical computational fluid dynamics (CFD) by leveraging quantum algorithms for higher efficiency. This paper introduces a comprehensive QCFD method, including…

Semi-Lagrangian (SL) schemes are highly efficient for simulating transport equations and are widely used across various applications. Despite their success, designing genuinely multi-dimensional and conservative SL schemes remains a…

Numerical Analysis · Mathematics 2024-05-06 Yongsheng Chen , Wei Guo , Xinghui Zhong

Accuracy is a key focus of current work in time series classification. However, speed and data reduction in many applications is equally important, especially when the data scale and storage requirements increase rapidly. Current MTSC…

Machine Learning · Computer Science 2022-12-06 Bhaskar Dhariyal , Thach Le Nguyen , Georgiana Ifrim

Inspired by numerous lab on a chip, biomedical and bioengineering applications such as cell sorting, focusing, trapping, and filtering of particles, manipulation of micron sized particle trajectories has been of significant interest in the…

Fluid Dynamics · Physics 2026-03-18 Partha Kumar Das

The emergence of computational fluid dynamics (CFD) enabled the simulation of intricate transport processes, including flow in physiological structures, such as blood vessels. While these so-called hemodynamic simulations offer…

CFD users of supercomputers usually resort to rule-of-thumb methods to select the number of subdomains (partitions) when relying on MPI-based parallelization. One common approach is to set a minimum number of elements or cells per…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-30 G. Houzeaux , R. M. Badia , R. Borrell , D. Dosimont , J. Ejarque , M. Garcia-Gasulla , V. López
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