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A novel uncertainty-based pressure reconstruction method is proposed to evaluate the instantaneous pressure fields from velocity fields measured using particle image velocimetry (PIV) or particle tracking velocimetry (PTV). First, the…

Fluid Dynamics · Physics 2019-12-03 Jiacheng Zhang , Sayantan Bhattacharya , Pavlos P. Vlachos

Particle tracking velocimetry (PTV) is widely used to measure time-resolved, three-dimensional velocity and pressure fields in fluid dynamics research. Inaccurate localization and tracking of particles is a key source of error in PTV,…

Fluid Dynamics · Physics 2026-03-31 Ke Zhou , Jiaqi Li , Jiarong Hong , Samuel J. Grauer

Uncertainty quantification for Particle Image Velocimetry (PIV) is critical for comparing flow fields with Computational Fluid Dynamics (CFD) results, and model design and validation. However, PIV features a complex measurement chain with…

Fluid Dynamics · Physics 2021-07-07 Lalit K. Rajendran , Sayantan Bhattacharya , Sally P. M. Bane , Pavlos P. Vlachos

In the past decades, great progress has been made in the field of optical and particle-based measurement techniques for experimental analysis of fluid flows. Particle Image Velocimetry (PIV) technique is widely used to identify flow…

Image and Video Processing · Electrical Eng. & Systems 2021-01-29 Nikolay Stulov , Michael Chertkov

The performance of a wavelet-based optical flow velocimetry (wOFV) algorithm to extract high accuracy and high resolution velocity fields from particle images in wall-bounded turbulent flows is assessed. wOFV is first evaluated using…

Fluid Dynamics · Physics 2023-10-09 Alexander Nicolas , Florian Zentgraf , Mark Linne , Andreas Dreizler , Brian Peterson

Estimating time-resolved velocity and pressure fields from Particle Image Velocimetry (PIV) remains challenging due to its limited temporal resolution in many applications. Data-driven approaches that combine snapshot PIV with…

Fluid Dynamics · Physics 2026-05-28 Junwei Chen , Marco Raiola , Stefano Discetti

We examine the problem of performing simultaneous and coplanar Particle Image Velocimetry (PIV) and Laser-Induced Fluorescence (LIF) measurements in a stratified fluid initially at rest. Our focus is on enabling detailed velocity and…

Fluid Dynamics · Physics 2022-07-13 Paolo Luzzatto-Fegiz

The existing particle image velocimetry (PIV) do not consider the curvature effect of the non-straight particle trajectory, because it seems to be impossible to obtain the curvature information from a pair of particle images. As a result,…

Computer Vision and Pattern Recognition · Computer Science 2021-12-08 Yong Lee , Shuang Mei

Understanding turbulence in a stratified environment requires a detailed picture of both the velocity field and the density field. Experimentally, this represents a significant measurement challenge, especially when full three-dimensional…

Fluid Dynamics · Physics 2019-05-22 J. L. Partridge , A. Lefauve , Stuart B. Dalziel

This article describes two independent developments aimed at improving the Particle Tracking Method for measurements of flow or particle velocities. First, a stereoscopic multicamera calibration method that does not require any optical…

Investigation of external flows past arbitrary objects requires access to the information in the boundary layer and the inviscid flow to paint a full picture of their characteristics. However, in laser diagnostic techniques such as particle…

Fluid Dynamics · Physics 2023-10-09 Shuangjiu Fu , Shabnam Raayai-Ardakani

This study explores the potential of neuromorphic Event-Based Vision (EBV) cameras for data-efficient representation of low-order model coordinates in turbulent flows. Unlike conventional imaging systems, EBV cameras asynchronously capture…

Fluid Dynamics · Physics 2025-02-26 Luca Franceschelli , Christian E. Willert , Marco Raiola , Stefano Discetti

A new variational inference method, SPH-ParVI, based on smoothed particle hydrodynamics (SPH), is proposed for sampling partially known densities (e.g. up to a constant) or sampling using gradients. SPH-ParVI simulates the flow of a fluid…

Artificial Intelligence · Computer Science 2024-07-29 Yongchao Huang

Altered hemodynamics play a key role in cerebrovascular diseases such as aneurysms and stenosis. However, in vivo imaging lacks the spatial resolution required to resolve flow dynamics in small vessels. This study presents an experimental…

Fluid Dynamics · Physics 2026-05-25 Job van Essen , Ahmed Sharaf , Denzel Hopman , Selene Pirola , Paola Fanzio

Particle Image Velocimetry (PIV) estimates velocities through correlations of particle images within interrogation windows, leading to a spatial modulation of the velocity field. Although in principle Particle Tracking Velocimetry (PTV)…

Fluid Dynamics · Physics 2023-02-14 Iacopo Tirelli , Andrea Ianiro , Stefano Discetti

We present a novel experimental technique to characterize the free surface of capillary flows adapted from the Spatio-Temporal Phase Shifting Profilometry (ST-PSP) method introduced by Ri et al. (Journal of Optics, 2019) for solid bodies.…

Around 1930 Ludwig Prandtl and his colleagues O. Tietjens and W. M\"uller published two films with visualizations of flows around surface piercing obstacles to illustrate the unsteady process of flow separation. These visualizations were…

Fluid Dynamics · Physics 2010-10-18 Christian Willert , Jürgen Kompenhans

Particle Image Velocimetry (PIV) is a method of im-aging and analysing fields of flows. The PIV tech-niques compute and display all the motion vectors of the field in a resulting image. Speeds more than thou-sand vectors per second can be…

Hardware Architecture · Computer Science 2008-07-24 Alain Aubert , Nathalie Bochard , Virginie Fresse

To date, the iterative image deformation method of PIV for two-pulse measurements is widely used in experimental fluid dynamics due to its robustness in many scientific and industrial applications. However, it has a known limitation…

Fluid Dynamics · Physics 2022-05-03 Dinar Zaripov , Renfu Li , Mikhail Tokarev , Dmitriy Markovich

Particle image velocimetry (PIV) is an effective tool in experimental fluid mechanics to extract flow fields from images. Recently, convolutional neural networks (CNNs) have been used to perform PIV analysis with accuracy on par with…

Fluid Dynamics · Physics 2021-07-07 Mia Morrell , Kyle Hickmann , Brandon Wilson