Computational fluid dynamics for predicting performance of ultraviolet disinfection – sensitivity to particle tracking inputs

2007 ◽  
Vol 6 (3) ◽  
pp. 285-301 ◽  
Author(s):  
Alex Munoz ◽  
Stephen Craik ◽  
Suzanne Kresta
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Particle Tracking ◽  
Ultraviolet Disinfection ◽  
Predicting Performance

Efficiency prediction for storage chambers using computational fluid dynamics

1996 ◽  
Vol 33 (9) ◽  
pp. 163-170 ◽  
Author(s):  
Virginia R. Stovin ◽  
Adrian J. Saul
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Shear Stress ◽  
Particle Tracking ◽  
Critical Value ◽  
Complex Geometries ◽  
Bed Shear Stress ◽  
Breadth Ratio ◽  
Computational Fluid Dynamics Cfd ◽  
Simulated Flow

Research was undertaken in order to identify possible methodologies for the prediction of sedimentation in storage chambers based on computational fluid dynamics (CFD). The Fluent CFD software was used to establish a numerical model of the flow field, on which further analysis was undertaken. Sedimentation was estimated from the simulated flow fields by two different methods. The first approach used the simulation to predict the bed shear stress distribution, with deposition being assumed for areas where the bed shear stress fell below a critical value (τcd). The value of τcd had previously been determined in the laboratory. Efficiency was then calculated as a function of the proportion of the chamber bed for which deposition had been predicted. The second method used the particle tracking facility in Fluent and efficiency was calculated from the proportion of particles that remained within the chamber. The results from the two techniques for efficiency are compared to data collected in a laboratory chamber. Three further simulations were then undertaken in order to investigate the influence of length to breadth ratio on chamber performance. The methodology presented here could be applied to complex geometries and full scale installations.

scholarly journals Assessment of the Flow Field in the HeartMate 3 Using Three-Dimensional Particle Tracking Velocimetry and Comparison to Computational Fluid Dynamics

ASAIO Journal ◽  
2020 ◽  
Vol 66 (2) ◽  
pp. 173-182 ◽  
Author(s):  
Bente Thamsen ◽  
Utku Gülan ◽  
Lena Wiegmann ◽  
Christian Loosli ◽  
Marianne Schmid Daners ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Flow Field ◽  
Particle Tracking ◽  
Particle Tracking Velocimetry ◽  
Three Dimensional

Experimental and Numerical Study of Ascending Aorta Hemodynamics Through 3D Particle Tracking Velocimetry and Computational Fluid Dynamics

2013 ◽  
Author(s):  
Utku Gülan ◽  
Diego Gallo ◽  
Raffaele Ponzini ◽  
Beat Lüthi ◽  
Markus Holzner ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Particle Tracking ◽  
Particle Tracking Velocimetry ◽  
Numerical Study ◽  
Imaging Techniques ◽  
Ascending Aorta ◽  
Human Aorta ◽  
Wide Range

The complex hemodynamics observed in the human aorta make this district a site of election for an in depth investigation of the relationship between fluid structures, transport and pathophysiology. In recent years, the coupling of imaging techniques and computational fluid dynamics (CFD) has been applied to study aortic hemodynamics, because of the possibility to obtain highly resolved blood flow patterns in more and more realistic and fully personalized flow simulations [1]. However, the combination of imaging techniques and computational methods requires some assumptions that might influence the predicted hemodynamic scenario. Thus, computational modeling requires experimental cross-validation. Recently, 4D phase contrast MRI (PCMRI) has been applied in vivo and in vitro to access the velocity field in aorta [2] and to validate numerical results [3]. However, PCMRI usually requires long acquisition times and suffers from low spatial and temporal resolution and a low signal-to-noise ratio. Anemometric techniques have been also applied for in vitro characterization of the fluid dynamics in aortic phantoms. Among them, 3D Particle Tracking Velocimetry (PTV), an optical technique based on imaging of flow tracers successfully used to obtain Lagrangian velocity fields in a wide range of complex and turbulent flows [4], has been very recently applied to characterize fluid structures in the ascending aorta [5].

Reduced-order Kalman-filtered hybrid simulation combining particle tracking velocimetry and direct numerical simulation

2012 ◽  
Vol 709 ◽  
pp. 249-288 ◽  
Author(s):  
Takao Suzuki
Keyword(s):  
Fluid Dynamics ◽  
Numerical Simulation ◽  
Computational Fluid Dynamics ◽  
Direct Numerical Simulation ◽  
Particle Tracking ◽  
Particle Tracking Velocimetry ◽  
Hybrid Simulation ◽  
Computational Time ◽  
Time Step ◽  
Reduced Order

AbstractThe capability of state-of-the-art techniques integrating experimental and computational fluid dynamics has been expanding recently. In our previous study, we have developed a hybrid unsteady-flow simulation technique combining particle tracking velocimetry (PTV) and direct numerical simulation (DNS) and demonstrated its capability at low Reynolds numbers. Similar approaches have also been proposed by a few groups; however, applying algorithms of this type generally becomes more challenging with increasing Reynolds number because the time interval of the frame rate for particle image velocimetry (PIV) becomes much greater than the required computational time step, and the PIV/PTV resolution tends to be lower than that necessary for computational fluid dynamics. To extend the applicability to noisy time-resolved PIV/PTV data, the proposed algorithm optimizes the data input temporally and spatially by introducing a reduced-order Kalman filter. This study establishes a framework of the Kalman-filtered hybrid simulation and proves the concept by tackling a planar-jet flow at $\mathit{Re}\approx 2000$ as an example. We evaluate the filtering functions as well as convergence of the proposed algorithm by comparing with the existing PTV–DNS hybrid simulation, and show some techniques available to hybrid velocity fields by analysing vortical motion in the shear layers of the jet.

scholarly journals Computational fluid dynamics for enhanced tracheal bioreactor design and long-segment graft recellularization

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hankyu Lee ◽  
Alba E. Marin-Araujo ◽  
Fabio G. Aoki ◽  
Siba Haykal ◽  
Thomas K. Waddell ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Shear Stress ◽  
Particle Tracking ◽  
Lessons Learned ◽  
Cell Seeding ◽  
Fluid Delivery ◽  
Tracking Model ◽  
Graft Success ◽  
Hydrodynamic Environment

AbstractSuccessful re-epithelialization of de-epithelialized tracheal scaffolds remains a challenge for tracheal graft success. Currently, the lack of understanding of the bioreactor hydrodynamic environment, and its relation to cell seeding outcomes, serve as major obstacles to obtaining viable tracheal grafts. In this work, we used computational fluid dynamics to (a) re-design the fluid delivery system of a trachea bioreactor to promote a spatially uniform hydrodynamic environment, and (b) improve the perfusion cell seeding protocol to promote homogeneous cell deposition. Lagrangian particle-tracking simulations showed that low rates of rotation provide more uniform circumferential and longitudinal patterns of cell deposition, while higher rates of rotation only improve circumferential uniformity but bias cell deposition proximally. Validation experiments with human bronchial epithelial cells confirm that the model accurately predicts cell deposition in low shear stress environments. We used the acquired knowledge from our particle tracking model, as a guide for long-term tracheal repopulation studies. Cell repopulation using conditions resulting in low wall shear stress enabled enhanced re-epithelialization of long segment tracheal grafts. While our work focuses on tracheal regeneration, lessons learned in this study, can be applied to culturing of any tissue engineered tubular scaffold.

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