In vitro validation of flow measurement with phase contrast MRI at 3 tesla using stereoscopic particle image velocimetry and stereoscopic particle image velocimetry-based computational fluid dynamics

2013 ◽  
Vol 39 (6) ◽  
pp. 1477-1485 ◽  
Author(s):  
Iman Khodarahmi ◽  
Mostafa Shakeri ◽  
Melanie Kotys-Traughber ◽  
Stefan Fischer ◽  
M. Keith Sharp ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Particle Image Velocimetry ◽  
Flow Measurement ◽  
Phase Contrast ◽  
Particle Image ◽  
Stereoscopic Particle Image Velocimetry ◽  
Phase Contrast Mri ◽  
Image Velocimetry

Particle Image Velocimetry Experiment and Computational Fluid Dynamics Simulation of Flow Around Rigid Cylinder

2018 ◽  
Vol 140 (5) ◽  
Author(s):  
Guangyao Wang ◽  
Ye Tian ◽  
Spyros A. Kinnas
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Particle Image Velocimetry ◽  
Vector Fields ◽  
Particle Image ◽  
Cfd Simulation ◽  
Dynamics Simulation ◽  
Reynolds Stresses ◽  
Rigid Cylinder ◽  
Image Velocimetry

This work focuses on the study of the flow around a rigid cylinder with both particle image velocimetry (PIV) experiment and computational fluid dynamics (CFD) simulation. PIV measurements of the flow field downstream of the cylinder are first presented. The boundary conditions for CFD simulations are measured in the PIV experiment. Then the PIV flow is compared with both Reynolds-averaged Navier–Stokes (RANS) two-dimensional (2D) and large eddy simulation (LES) three-dimensional (3D) simulations performed with ANSYS fluent. The velocity vector fields and time histories of velocity are analyzed. In addition, the time-averaged velocity profiles and Reynolds stresses are analyzed. It is found that, in general, LES (3D) gives a better prediction of flow characteristics than RANS (2D).

The importance of hydrodynamics in UV advanced oxidation reactors

2007 ◽  
Vol 55 (12) ◽  
pp. 53-58 ◽  
Author(s):  
A. Sozzi ◽  
F. Taghipour
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Particle Image Velocimetry ◽  
Particle Image ◽  
Flow Distribution ◽  
Fluence Rate ◽  
Reactor Performance ◽  
Image Velocimetry ◽  
Reactor Axis ◽  
Computational Fluid Dynamics Cfd

The flow field of UV reactors was characterised experimentally using particle image velocimetry (PIV) and modelled with computational fluid dynamics (CFD). The reactor flow was integrated with the radiation fluence rate and photolysis kinetics to calculate the overall conversion of photo-reactant components in annular UV reactors with an inlet parallel and perpendicular to the reactor axis. The results indicated that the fluid flow distribution within the reactor volume affects photo-reactor performance.

Particle Image Velocimetry and Computational Fluid Dynamics Analysis of Fuel Cell Manifold

2010 ◽  
Vol 7 (3) ◽  
Author(s):  
Jesper Lebæk ◽  
Marcin Blazniak Andreasen ◽  
Henrik Assenholm Andresen ◽  
Mads Bang ◽  
Søren Knudsen Kær
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Particle Image Velocimetry ◽  
Fuel Cell ◽  
Particle Image ◽  
High Current Density ◽  
Plug Flow ◽  
Flow Distribution ◽  
Image Velocimetry ◽  
Computational Fluid Dynamics Analysis

The inlet effect on the manifold flow in a fuel cell stack was investigated by means of numerical methods (computational fluid dynamics) and experimental methods (particle image velocimetry). At a simulated high current density situation the flow field was mapped on a 70 cell simulated cathode manifold. Three different inlet configurations were tested: plug flow, circular inlet, and a diffuser inlet. A very distinct jet was formed in the manifold, when using the circular inlet configuration, which was confirmed both experimentally and numerically. This jet was found to be an asymmetric confined jet, known as the symmetry-breaking bifurcation phenomenon, and it is believed to cause a significant maldistribution of the stack flow distribution. The investigated diffuser design proved to generate a much smoother transition from the pipe flow to the manifold flow with a subsequent better flow distribution. A method was found in the literature to probe if there is a risk of jet asymmetry; it is however recommended by the author to implement a diffuser design, as this will generate better stack flow distribution and less head loss. Generally, the numerical and experimental results were found in to be good agreement, however, a detailed investigation revealed some difference in the results.

Multilaboratory Particle Image Velocimetry Analysis of the FDA Benchmark Nozzle Model to Support Validation of Computational Fluid Dynamics Simulations

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Prasanna Hariharan ◽  
Matthew Giarra ◽  
Varun Reddy ◽  
Steven W. Day ◽  
Keefe B. Manning ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Particle Image Velocimetry ◽  
Turbulent Flow ◽  
Medical Device ◽  
Particle Image ◽  
Transitional Flow ◽  
Flow Conditions ◽  
Image Velocimetry ◽  
Flow Case

This study is part of a FDA-sponsored project to evaluate the use and limitations of computational fluid dynamics (CFD) in assessing blood flow parameters related to medical device safety. In an interlaboratory study, fluid velocities and pressures were measured in a nozzle model to provide experimental validation for a companion round-robin CFD study. The simple benchmark nozzle model, which mimicked the flow fields in several medical devices, consisted of a gradual flow constriction, a narrow throat region, and a sudden expansion region where a fluid jet exited the center of the nozzle with recirculation zones near the model walls. Measurements of mean velocity and turbulent flow quantities were made in the benchmark device at three independent laboratories using particle image velocimetry (PIV). Flow measurements were performed over a range of nozzle throat Reynolds numbers (Rethroat) from 500 to 6500, covering the laminar, transitional, and turbulent flow regimes. A standard operating procedure was developed for performing experiments under controlled temperature and flow conditions and for minimizing systematic errors during PIV image acquisition and processing. For laminar (Rethroat=500) and turbulent flow conditions (Rethroat≥3500), the velocities measured by the three laboratories were similar with an interlaboratory uncertainty of ∼10% at most of the locations. However, for the transitional flow case (Rethroat=2000), the uncertainty in the size and the velocity of the jet at the nozzle exit increased to ∼60% and was very sensitive to the flow conditions. An error analysis showed that by minimizing the variability in the experimental parameters such as flow rate and fluid viscosity to less than 5% and by matching the inlet turbulence level between the laboratories, the uncertainties in the velocities of the transitional flow case could be reduced to ∼15%. The experimental procedure and flow results from this interlaboratory study (available at http://fdacfd.nci.nih.gov) will be useful in validating CFD simulations of the benchmark nozzle model and in performing PIV studies on other medical device models.

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