Experimental investigation on the effect of liquid injection by multiple orifices in the formation of droplets in a Venturi scrubber

Guerra, Vádila Giovana; Gonçalves, José Antônio Silveira; Coury, José Renato

doi:10.1016/j.jhazmat.2008.03.101

Cited by 17 publications

(18 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In this study, a set of 652 experimental data points (Boll et al, 1974;Alonso et al, 2001;Costa et al, 2004;Guerra et al, 2009) for droplet diameter was used to design the ANNs. Moreover, 70% of the data (i.e., 456 data) was used for training process, 15% (i.e., 98 data) for validation and the rest 15% (i.e., 98 data) for testing.…”

Section: Resultsmentioning

confidence: 99%

“…Experimental data were extracted from several papers (Boll et al, 1974;Alonso et al, 2001;Costa et al, 2004;Guerra et al, 2009) with different variables and methods of liquid injection. These data were used for training the network; their ranges are summarized in Table 1.…”

Section: Ann Details and Data Preparationmentioning

confidence: 99%

“…They concluded that, when liquid is injected as spray, droplet size is mostly controlled by the nozzle characteristics and the interaction with the gas in the upstream in the Venturi. Guerra et al (2009) measured the effect of multiple jet liquid injection on the formation and distribution of droplets in a Venturi scrubber. They considered different liquid injection configurations with gas velocity and liquid flow rates as parameters.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Introducing a new formula based on an artificial neural network for prediction of droplet size in venturi scrubbers

Sharifi

Mohebbi

2012

Braz. J. Chem. Eng.

View full text Add to dashboard Cite

-Droplet size is a fundamental parameter for Venturi scrubber performance. For many years, the correlations proposed by Nukiyama and Tanasawa (1938) and Boll et al. (1974) were used for calculating mean droplet size in Venturi scrubbers with limited operating parameters. This study proposes an alternative approach on the basis of artificial neural networks (ANNs) to determine the mean droplet size in Venturi scrubbers, in a wide range of operating parameters. Experimental data were used to design the ANNs. A neural network was trained based on the liquid to gas ratio (L/G) and throat gas velocity (V gth ), as input parameters, and the Sauter mean diameter (D 32 ) as the desired parameter. The back-propagation learning algorithms were used in the network and the best approach was found. A new formula for the prediction of D 32 using the weights of the network was then generated. This formula predicts mean droplet size in Venturi scrubbers more accurately than the correlations of Boll et al. (1974) and Nukiyama and Tanasawa (1938). The Average Absolute Percent Deviation (AAPD) of our formula and the Boll et al. and Nukiyama and Tanasawa correlations for the full ranges of experimental data are 26. 04%, 40.19% and 32.99%, respectively.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Ann Details and Data Preparationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Introducing a new formula based on an artificial neural network for prediction of droplet size in venturi scrubbers

Sharifi

Mohebbi

2012

Braz. J. Chem. Eng.

View full text Add to dashboard Cite

show abstract

“…4 and 5, which differ on account of the nominal throat gas velocity, reveals that, for small penetrations (between 0 and 0.2), film fraction is smaller for the higher gas velocity, while for intermediate jet penetrations (between 0.2 and 0.5), film fraction is higher for the higher gas velocity. The higher gas velocity is able to produce smaller droplets (Guerra et al, 2009). These droplets spread better than the larger droplets due to turbulence diffusion.…”

Section: Resultsmentioning

confidence: 99%

Film fraction in a vertical circular Venturi scrubber

Guerra¹,

Guerra²,

Coury³

et al. 2011

J. Braz. Soc. Mech. Sci. & Eng.

View full text Add to dashboard Cite

“…A poor distribution, characterized by the presence of high and low droplet concentration regions, allows the passage of many contaminants without hitting the droplets, decreasing considerably the efficiency of the equipment (Costa, 2002;Gonçalves et al, 2003b;Guerra et al, 2009). Since a major part of the operational expenses of a Venturi scrubber is associated with the usage of the liquid, more detailed studies on the distribution of droplets in the equipment, due to the characteristics of the injection system utilized, the mechanisms of atomization and the turbulence of the jets and the gas should generate knowledge by which it is possible to design a scrubber optimizing the distribution of droplets, maximizing the efficiency and minimizing the usage of liquid.…”

Section: Introductionmentioning

confidence: 99%

Droplet dispersion angle measurements on a Pease-Antony Venturi scrubber

Puentes

Guerra

Coury

et al. 2012

Braz. J. Chem. Eng.

View full text Add to dashboard Cite

-A Pease-Anthony Venturi scrubber is a gas cleaning device that uses liquid, injected in the equipment as jets, to remove contaminants from the gas. The liquid jet is atomized into droplets, which are dispersed throughout the equipment due to the turbulence. The performance of the scrubber is affected by the spatial distribution of the droplets. Although CFD models have been used to predict the droplet dispersion, these models are expensive. Alternatively, the concept of "jet spreading angle" could be used as a simple and quick way to estimate droplet dispersion. The purpose of this paper is to measure the spreading angle of jets transversally injected into the throat of a Venturi scrubber and correlate it with both gas and jet velocities. The throat gas velocities varied between 59 and 74 m/s and the jet velocity between 3.18 and 19.1 m/s. The angles were measured through image analysis, obtained with high velocity photography. The spreading angle was found to be strongly dependent on jet velocity.

show abstract

Experimental investigation on the effect of liquid injection by multiple orifices in the formation of droplets in a Venturi scrubber

Cited by 17 publications

References 19 publications

Introducing a new formula based on an artificial neural network for prediction of droplet size in venturi scrubbers

Introducing a new formula based on an artificial neural network for prediction of droplet size in venturi scrubbers

Film fraction in a vertical circular Venturi scrubber

Droplet dispersion angle measurements on a Pease-Antony Venturi scrubber

Contact Info

Product

Resources

About