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A fully-convolutional neural-network model is used to predict the streamwise velocity fields at several wall-normal locations by taking as input the streamwise and spanwise wall-shear-stress planes in a turbulent open channel flow. The…

流体动力学 · 物理学 2020-08-26 L. Guastoni , M. P. Encinar , P. Schlatter , H. Azizpour , R. Vinuesa

The main objective of this work is to perform a detailed comparison of the lattice Boltzmann equation (LBE) and the recently developed discrete unified gas-kinetic scheme (DUGKS) methods for direct numerical simulation (DNS) of the decaying…

计算物理 · 物理学 2016-10-26 Peng Wang , Lian-Ping Wang , Zhaoli Guo

The objective of the present study is to provide a numerical database of thermal boundary layers and to contribute to the understanding of the dynamics of passive scalars at different Prandtl numbers. In this regard, a direct numerical…

流体动力学 · 物理学 2023-11-10 Arivazhagan G. Balasubramanian , Luca Guastoni , Philipp Schlatter , Ricardo Vinuesa

A promising and cost-effective method for numerical simulation of high Re wall-bounded flows is wall-modeled large-eddy simulation. Most wall models are formulated from the Reynolds-averaged Navier-Stokes equations (RANS). These RANS-based…

流体动力学 · 物理学 2021-01-08 Ahmed Elnahhas , Adrián Lozano-Durán , Parviz Moin

Simulation of fluid flow in porous media has many applications, from the micro-scale (cell membranes, filters, rocks) to macro-scale (groundwater, hydrocarbon reservoirs, and geothermal) and beyond. Direct simulation of flow in porous media…

流体动力学 · 物理学 2020-04-27 Ying Da Wang , Traiwit Chung , Ryan T. Armstrong , Peyman Mostaghimi

Noncritical soft-faults and model deviations are a challenge for Fault Detection and Diagnosis (FDD) of resident Autonomous Underwater Vehicles (AUVs). Such systems may have a faster performance degradation due to the permanent exposure to…

机器人学 · 计算机科学 2018-07-12 Samy Nascimento , Matias Valdenegro-Toro

Direct numerical simulations of turbulent open channel flow with friction Reynolds numbers of $Re_{\tau}=200,400,600$ are performed. Their results are compared with closed channel data in order to investigate the influence of the free…

流体动力学 · 物理学 2022-12-02 Christian Bauer

Deep learning (DL) has demonstrated promise for accelerating and enhancing the accuracy of flow physics simulations, but progress is constrained by the scarcity of high-fidelity training data, which is costly to generate and inherently…

流体动力学 · 物理学 2025-10-06 Daniel Dehtyriov , Jonathan F. MacArt , Justin Sirignano

Small-scale liquid flows on solid surfaces provide convincing details in liquid animation, but they are difficult to be simulated with efficiency and fidelity, mostly due to the complex nature of the surface tension at the contact front…

图形学 · 计算机科学 2018-11-07 Rajaditya Mukherjee , Qingyang Li , Zhili Chen , Shicheng Chu , Huamin Wang

We present direct numerical simulations (DNS) of laminar to turbulent transition in Herschel-Bulkley (HB) yield-stress fluids flowing through pipes and rectangular channels. The simulations employ a Herschel-Bulkley formulation that…

流体动力学 · 物理学 2026-03-13 Shivam Prajapati , Prasoon Suchandra , Vivek Kumar , Ardalan Javadi , Suhas Jain , Cyrus Aidun

Optimizing fluid-dynamic performance is an important engineering task. Traditionally, experts design shapes based on empirical estimations and verify them through expensive experiments. This costly process, both in terms of time and space,…

计算工程、金融与科学 · 计算机科学 2020-01-24 Yang Chen

Fluid simulation is an important research topic in computer graphics (CG) and animation in video games. Traditional methods based on Navier-Stokes equations are computationally expensive. In this paper, we treat fluid motion as point cloud…

计算机视觉与模式识别 · 计算机科学 2025-01-07 Yu Chen , Shuai Zheng , Nianyi Wang , Menglong Jin , Yan Chang

One route to improved predictive modeling of magnetically confined fusion reactors is to couple transport solvers with direct numerical simulations (DNS) of turbulence, rather than with surrogate models. An additional challenge presented by…

等离子体物理 · 物理学 2018-07-16 Jeffrey B. Parker , Lynda L. LoDestro , Alejandro Campos

Computational complexity has been the bottleneck of applying physically-based simulations on large urban areas with high spatial resolution for efficient and systematic flooding analyses and risk assessments. To address this issue of long…

计算机视觉与模式识别 · 计算机科学 2020-05-14 Zifeng Guo , Joao P. Leitao , Nuno E. Simoes , Vahid Moosavi

The influence of near-wall density and viscosity gradients on near-wall turbulence in a channel are studied by means of Direct Numerical Simulation (DNS) of the low-Mach number approximation of the Navier--Stokes equations. Different…

流体动力学 · 物理学 2023-02-17 Ashish Patel , Bendiks Jan Boersma , Rene Pecnik

Machine learning is playing an increasing role in hydrology, supplementing or replacing physics-based models. One notable example is the use of recurrent neural networks (RNNs) for forecasting streamflow given observed precipitation and…

计算物理 · 物理学 2024-12-09 Mauricio Lima , Katherine Deck , Oliver R. A. Dunbar , Tapio Schneider

Inverse problems in granular flows, such as landslides and debris flows, involve estimating material parameters or boundary conditions based on target runout profile. Traditional high-fidelity simulators for these inverse problems are…

地球物理 · 物理学 2024-04-29 Yongjin Choi , Krishna Kumar

The development of a reliable subgrid-scale (SGS) model for large-eddy simulation (LES) is of great importance for many scientific and engineering applications. Recently, deep learning approaches have been tested for this purpose using…

流体动力学 · 物理学 2022-11-09 Junhyuk Kim , Hyojin Kim , Jiyeon Kim , Changhoon Lee

Water distribution systems (WDS) are an integral part of critical infrastructure which is pivotal to urban development. As 70% of the world's population will likely live in urban environments in 2050, efficient simulation and planning tools…

机器学习 · 计算机科学 2024-03-28 Inaam Ashraf , Janine Strotherm , Luca Hermes , Barbara Hammer

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…

流体动力学 · 物理学 2025-10-15 C. Ricardo Constante-Amores , Alec J. Linot , Michael D. Graham