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Very recently, a defect model which depicts the growth tendency of the near-wall peak of the streamwise turbulence intensity has been developed (Chen $\&$ Sreenivasan, J. Fluid Mech. (2021), vol.908, R3). Based on the finiteness of the…

Fluid Dynamics · Physics 2023-03-30 Cheng Cheng , Lin Fu

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

This paper presents an adjoint-assisted, topology-optimization-inspired approach for analyzing topological sensitivities in fluid domains based on porous media formulations -- without directly utilizing the porosity field as a design…

Fluid Dynamics · Physics 2025-05-09 Niklas Kühl

One of the limitations of the Lattice Boltzmann Method in simulating inertial flows is the coupling of the discretization of space to the velocity discretization. It requires an increase of the size of computational lattices in order to…

Fluid Dynamics · Physics 2024-09-25 Dawid Strzelczyk , Maciej Matyka

Accurate prediction of the transition from laminar flow to turbulence remains an unresolved challenge despite its importance for understanding a variety of environmental, biological, and industrial phenomena. Well over a century of…

Fluid Dynamics · Physics 2023-01-10 John O. Dabiri , Nina Mohebbi , Matthew K. Fu

This paper is concerned with the problem of shape optimization of two-dimensional flows governed by the time-dependent Navier-Stokes equations. We derive the structures of shape gradients with respect to the shape of the variable domain for…

Optimization and Control · Mathematics 2007-05-23 Zhiming Gao , Yichen Ma , Hongwei Zhuang

The transition to turbulence in flows where the laminar profile is linearly stable requires perturbations of finite amplitude. "Optimal" perturbations are distinguished as extrema of certain functionals, and different functionals give…

Fluid Dynamics · Physics 2015-02-09 Marina Pausch , Bruno Eckhardt

In traditional topology optimization, the computing time required to iteratively update the material distribution within a design domain strongly depends on the complexity or size of the problem, limiting its application in real engineering…

Computational Engineering, Finance, and Science · Computer Science 2024-05-14 Gabriel Garayalde , Matteo Torzoni , Matteo Bruggi , Alberto Corigliano

The addition of particles to turbulent flows changes the underlying mechanism of turbulence and leads to turbulence modulation. Different temporal and spatial scales for both phases make it challenging to understand turbulence modulation…

Fluid Dynamics · Physics 2023-05-24 Naveen Rohilla , Siddhi Arya , Partha Sarathi Goswami

The need for optimized structures with good mechanical performance for the minimum weight is common in industry. Solid Isotropic Material with Penalization (SIMP) is a Topology Optimization (TO) method offering a trade-off between minimum…

Optimization and Control · Mathematics 2025-03-28 Luis Irastorza-Valera , Ricardo Larraínzar-Garijo , Javier Montoya-Adárraga , Luis Saucedo-Mora

Accurate simulation of turbulent flow with separation is an important but challenging problem. In this paper, a data-driven Reynolds-averaged turbulence modeling approach, field inversion and machine learning is implemented to modify the…

Fluid Dynamics · Physics 2022-06-02 Chongyang Yan , Haoran Li , Yufei Zhang , Haixin Chen

In particle-laden turbulent flows the turbulence in carrier fluid phase gets affected by the dispersed particle phase for volume fraction above $10^{-4}$ and hence reverse coupling or two-way coupling becomes relevant in that volume…

Fluid Dynamics · Physics 2022-09-14 Swagnik Ghosh , Partha Sarathi Goswami

We address the problem of sampling from terminally constrained distributions with pre-trained flow-based generative models through an optimal control formulation. Theoretically, we characterize the value function by a…

Machine Learning · Computer Science 2026-01-15 Weiguo Gao , Ming Li , Qianxiao Li

The simulation of turbulent flow requires many degrees of freedom to resolve all the relevant times and length scales. However, due to the dissipative nature of the Navier-Stokes equations, the long-term dynamics are expected to lie on a…

Fluid Dynamics · Physics 2025-10-15 C. Ricardo Constante-Amores , Alec J. Linot , Michael D. Graham

The complex small-scale statistics of turbulence are a result of the combined cascading dynamics through all scales of the flow. Predicting these statistics using fully resolved simulations at the high Reynolds numbers that typically occur…

Fluid Dynamics · Physics 2025-07-01 Lukas Bentkamp , Michael Wilczek

We investigate the mechanisms by which inertial solid particles modulate turbulence and alter the fluid mass transport in dense turbulent liquid-solid flows. To this end, we perform Euler-Lagrange simulations at friction Reynolds number…

Fluid Dynamics · Physics 2024-06-13 Jonathan S. Van Doren , M. Houssem Kasbaoui

Turbulent flows have high requirements for very fine meshes near the boundary to ensure accuracy. In the context of topology optimization (TO), such fine meshes become unrealistic and common approaches are hampered by low accuracy and…

Fluid Dynamics · Physics 2026-01-06 Amirhossein Bayat , Hao Li , Joe Alexandersen

Predicting the flow of non-Newtonian fluids in porous structure is still a challenging issue due to the interplay betwen the microscopic disorder and the non-linear rheology. In this letter, we study the case of an yield stress fluid in a…

Soft Condensed Matter · Physics 2019-06-26 Chen Liu , Andrea De Luca , Alberto Rosso , Laurent Talon

Iterative coarse-graining procedure based on Wyld's perturbation expansion is applied to the problem of Navier-Stokes turbulence. It is shown that the low-order calculation gives the fixed-point Reynolds number $ Re_{fp}$ (coupling…

Fluid Dynamics · Physics 2013-08-21 Victor Yakhot

The Reynolds-Averaged Navier-Stokes (RANS) approach remains a backbone for turbulence modeling due to its high cost-effectiveness. Its accuracy is largely based on a reliable Reynolds stress anisotropy tensor closure model. There has been…

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