PREDICTION OF MASS TRANSFER COEFFICIENT IN BUBBLE COLUMN USING ARTIFICIAL NEURAL NETWORK

Adil A. Al-Hemiri; Salih A. Salih

doi:10.31026/j.eng.2007.02.01

Article Details

PREDICTION OF MASS TRANSFER COEFFICIENT IN BUBBLE COLUMN USING ARTIFICIAL NEURAL NETWORK

Authors:

Adil A. Al-Hemiri | Salih A. Salih

Publisher:

University of Baghdad

Journal:

Journal of Engineering Vol.13 Issue 2, pp.1327-1343

Document Type:

Article

Publication Date:

1/2007

Document Language:

English

Document ID (Org No.):

2001379996

pISSN:

2520-3339

DOI:

10.31026/j.eng.2007.02.01

Keywords:

Abstract:

 The volumetric mass transfer coefficient kL.a was calculated using two gases (air and CO2) in water and NaOH solution. The experiments were carried out using 0.1 m column diameter. Empirical and Artificial Neural Network (ANN) correlation were developed to predicted mass transfer coefficient in form of dimensionless groups (Sh, Re,Bo and We). The use of Back Propagation Neural Network (BPNN) gave better results than other correlations found in literature and than the empirical one found in this study.

Article Details

PREDICTION OF MASS TRANSFER COEFFICIENT IN BUBBLE COLUMN USING ARTIFICIAL NEURAL NETWORK

Authors:

Adil A. Al-Hemiri | Salih A. Salih

Publisher:

University of Baghdad

Journal:

Journal of Engineering Vol.13 Issue 2, pp.1327-1343

Document Type:

Article

Publication Date:

1/2007

Document Language:

English

Document ID (Org No.):

2001379996

pISSN:

2520-3339

DOI:

10.31026/j.eng.2007.02.01

Bubble column

Mass transfer coefficient

Artificial neural network

Issues

Article Details

PREDICTION OF MASS TRANSFER COEFFICIENT IN BUBBLE COLUMN USING ARTIFICIAL NEURAL NETWORK

Authors: Adil A. Al-Hemiri | Salih A. Salih

Publisher: University of Baghdad

Journal: Journal of Engineering Vol.13 Issue 2, pp.1327-1343

Document Type: Article

Publication Date: 1/2007

Document Language: English

Document ID (Org No.): 2001379996

pISSN: 2520-3339

DOI: 10.31026/j.eng.2007.02.01

Bubble column

Mass transfer coefficient

Artificial neural network

Issues

Authors:

Adil A. Al-Hemiri | Salih A. Salih

Publisher:

University of Baghdad

Journal:

Journal of Engineering Vol.13 Issue 2, pp.1327-1343

Document Type:

Article

Publication Date:

1/2007

Document Language:

English

Document ID (Org No.):

2001379996

pISSN:

2520-3339

DOI:

10.31026/j.eng.2007.02.01