Application of Computational Fluid Dynamics in Sedimentation Tank Design and Its Recent Developments: a Review

2022 ◽  
Vol 233 (1) ◽  
Author(s):  
Kirpa Hirom ◽  
Thiyam Tamphasana Devi
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Sedimentation Tank ◽  
Recent Developments ◽  
Tank Design

Computational fluid dynamics modelling of hydraulics and sedimentation in process reactors during aeration tank settling

2006 ◽  
Vol 53 (12) ◽  
pp. 257-264 ◽  
Author(s):  
M.D. Jensen ◽  
P. Ingildsen ◽  
M.R. Rasmussen ◽  
J. Laursen
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Control Method ◽  
Waste Water Treatment ◽  
Aeration Tank ◽  
Cfd Modelling ◽  
Design Changes ◽  
Dynamics Modelling ◽  
Tank Design ◽  
Tank Settling

Aeration tank settling is a control method allowing settling in the process tank during high hydraulic load. The control method is patented. Aeration tank settling has been applied in several waste water treatment plants using the present design of the process tanks. Some process tank designs have shown to be more effective than others. To improve the design of less effective plants, computational fluid dynamics (CFD) modelling of hydraulics and sedimentation has been applied. This paper discusses the results at one particular plant experiencing problems with partly short-circuiting of the inlet and outlet causing a disruption of the sludge blanket at the outlet and thereby reducing the retention of sludge in the process tank. The model has allowed us to establish a clear picture of the problems arising at the plant during aeration tank settling. Secondly, several process tank design changes have been suggested and tested by means of computational fluid dynamics modelling. The most promising design changes have been found and reported.

A Computational Fluid Dynamics Modeling and Experimental Study of the Mixing Process for Dispersion of Synthetic Fibers in Wet-Lay Forming

TAPPI Journal ◽  
2010 ◽  
Vol 9 (3) ◽  
pp. 6-13 ◽  
Author(s):  
Melur K. Ramasubramanian ◽  
Donald A. Shiffler ◽  
Amit Jayachandran
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Wire Mesh ◽  
Spherical Particles ◽  
Design Parameters ◽  
Mixing Process ◽  
Discrete Phase Model ◽  
Dynamics Modeling ◽  
Synthetic Fibers ◽  
Tank Design

In this paper, we present results from a computational fluid dynamics (CFCFD) model for the mixing process used to disperse synthetic fibers in wet-lay process. We used CFCFD software, FLUENTFLUENTFLUENTFLUENTFLUENTFLUENT, together with the MIXSISIM user interface to accurately model the impeller geometry. A multiple reference frame (MRFRF) model and standard k-e turbulence model were used to model the problem. After obtaining a converged solution for the mixing tank with water, a discrete phase model was constructed by injecting spherical particles into the flow. A mixing tank with baffles and a centrally located impeller was used in experiments. PETET fibers (1.5 denier, 6.35 mm, 12.7 mm, and 38.7 mm) at a concentration of 0.01% were mixed in water for the study. In regions behind the baffles, where the model predicted higher concentration of particles, experimental results showed a 34% higher concentration relative to the region in the high turbulence zone near the center. Instantaneous sheets were formed by rapidly dipping and removing a flat wire mesh strainer into the tank at two different locations to assess the state of dispersion in the tank. The sheets were transferred onto a blotting paper and examined under a microscope to count defects. Results show that the number of rope defects was 43% higher in sheets drawn from the region behind the baffles than in the sheets drawn from regions near the center of the tank. Changing baffles from a rectangular to a triangular cross section decreased the number of rope defects, but increased the number of log defects in the sample sheets at the same location. The CFCFD model can be used to optimize mixing tank design for wet lay fiber dispersion. The model provides further insight into the mixing process by predicting the effect of changes in design parameters on dispersion quality.

ten years of modelling to achieve haemodynamic optimisation of the total cavopulmonary connection

2004 ◽  
Vol 14 (S3) ◽  
pp. 48-52 ◽  
Author(s):  
gabriele dubini ◽  
francesco migliavacca ◽  
giancarlo pennati ◽  
marc r. de leval ◽  
edward l. bove
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Cardiovascular System ◽  
Three Dimensional ◽  
In Vitro Models ◽  
Surgical Reconstruction ◽  
Complex Anatomy ◽  
Recent Developments ◽  
Three Dimensional Models

the techniques of computational fluid dynamics are among the most powerful tools available to engineers dealing with the motion of fluids and the exchange of mass, momentum, and energy. they have recently been shown to have an increasing number of applications to the human cardiovascular system, including the fluid dynamics of surgical reconstruction of congenitally malformed parts of the cardiovascular system. in vitro models are the alternative laboratory tools with which to study fluid dynamics. the advantages of computational fluid dynamics over the in vitro models are the easy quantification of haemodynamic variables, such as rates of flow, pressure, and distribution of shear stress, and changes in geometric and fluid dynamics parameters. furthermore, using computational fluid dynamics allows the development of three-dimensional models to reproduce both the complex anatomy of the investigated region and the details of the surgical reconstruction, especially with the recent developments in magnetic resonance imaging. on the basis of the results, it is possible quantitatively to evaluate the surgical correction. this technology, which benefits greatly from the continuous improvement in hardware and software, enables cardiovascular experts and bioengineers to look at the fluid dynamics of various cardiovascular regions with increasing sophistication.

scholarly journals Recent Developments and Possibilities of Computational Fluid Dynamics in Materials Processing

1991 ◽  
Vol 77 (8) ◽  
pp. 1234-1242 ◽  
Author(s):  
Ikuo SAWADA ◽  
Masahiro TANI ◽  
Julian SZEKELY ◽  
Olusegun Johnson ILEGBUSI
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Materials Processing ◽  
Recent Developments

Sliding mesh computational fluid dynamics—a predictive tool in stirred tank design

1997 ◽  
Vol 211 (3) ◽  
pp. 149-156 ◽  
Author(s):  
Z Jaworski ◽  
M L Wyszynski ◽  
I P T Moore ◽  
A W Nienow
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Initial Conditions ◽  
Integrated Design ◽  
Flow Characteristics ◽  
Cfd Modelling ◽  
Predictive Tool ◽  
Sliding Mesh ◽  
Tank Design ◽  
Experimental Values

The use of a fully predictive numerical model of flow in a stirred, baffled tank is presented and validated for the laminar flow regime. This approach employs a commercial computational fluid dynamics (CFD) package with sliding mesh facility. The comparison of computed and experimental values for various flow characteristics shows a very good agreement without the need to input any experimental values for the boundary or initial conditions. It is proposed that the model/experiment error ratio (involving relative errors) may be generally adopted as a criterion for the quality of CFD modelling. This ratio should not be much larger, and does not need to be smaller, than unity. The ratio obtained in this work was just over unity. The state of the art CFD packages are now believed to be able to form a suitable basis for the process engineering aspects of an integrated design of stirred tanks, including mechanical engineering and other related issues.

scholarly journals Comparing the flow dynamics and particle settling in full-scale sedimentation tanks of different lengths

2016 ◽  
Vol 17 (4) ◽  
pp. 998-1006 ◽  
Author(s):  
S. Arendze ◽  
M. S. Sibiya
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Settling Tank ◽  
Treatment Plant ◽  
Drinking Water Treatment ◽  
Full Scale ◽  
Flow Dynamics ◽  
Particle Removal ◽  
Particle Settling ◽  
Tank Design

The efficiency of sedimentation is dependent on settling tank design and operation, where the streamlined solid–liquid separation results in water of safe potable quality. It is therefore important that the tank design and operation are sufficiently optimised. Sedimentation tanks are commonly overdesigned, leading to unwarranted capital expenditure, and overloading. This study used computational fluid dynamics to model the current conditions of two full-scale sedimentation tanks of different lengths at a large drinking water treatment plant in South Africa, using the shear stress transport turbulence model. The flow dynamics and the polyelectrolyte flocculated particle settling efficiency between the short tank and the long tank were compared. Recirculation zones near the inlet were pronounced in the short tank, which resulted in particles being drawn towards the outlets. The flow in the long tank isolated the inlet and outlet, with low particle volume fractions and particle velocities at the weirs. The particle removal in both tanks was greater than 99%; however, removal was higher in the long tank (99.86%), hence it was more efficient despite greater infrastructure cost. Computational fluid dynamics modelling is a tremendous operational tool which can review the performance of alternative tank designs and provide valuable input into future design.

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