Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However, these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611 measurements collected from the open literature, a correlation for hold u...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
University of Baghdad/College of Engineering
2007-12-01
|
| Series: | Iraqi Journal of Chemical and Petroleum Engineering |
| Subjects: | |
| Online Access: | http://ijcpe.uobaghdad.edu.iq/index.php/ijcpe/article/view/494 |
| _version_ | 1818566768072851456 |
|---|---|
| author | Adel Al-Hemiri Suhayla Akkar |
| author_facet | Adel Al-Hemiri Suhayla Akkar |
| author_sort | Adel Al-Hemiri |
| collection | DOAJ |
| description | In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably improved prediction of dispersed phase hold up. The developed correlation also
shows better prediction over a wide range of operation parameters in RDC columns. |
| first_indexed | 2024-12-14T01:57:51Z |
| format | Article |
| id | doaj.art-8dcc4d75975f46f9bf9ba8eddd12c33b |
| institution | Directory Open Access Journal |
| issn | 1997-4884 2618-0707 |
| language | English |
| last_indexed | 2024-12-14T01:57:51Z |
| publishDate | 2007-12-01 |
| publisher | University of Baghdad/College of Engineering |
| record_format | Article |
| series | Iraqi Journal of Chemical and Petroleum Engineering |
| spelling | doaj.art-8dcc4d75975f46f9bf9ba8eddd12c33b2022-12-21T23:21:07ZengUniversity of Baghdad/College of EngineeringIraqi Journal of Chemical and Petroleum Engineering1997-48842618-07072007-12-0184Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural NetworkAdel Al-HemiriSuhayla AkkarIn the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However, these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611 measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network (ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m , s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52% and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the developed ANN correlation noticeably improved prediction of dispersed phase hold up. The developed correlation also shows better prediction over a wide range of operation parameters in RDC columns.http://ijcpe.uobaghdad.edu.iq/index.php/ijcpe/article/view/494dispersed phase hold up, RDC, artificial neural networks (ANN). |
| spellingShingle | Adel Al-Hemiri Suhayla Akkar Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network Iraqi Journal of Chemical and Petroleum Engineering dispersed phase hold up, RDC, artificial neural networks (ANN). |
| title | Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network |
| title_full | Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network |
| title_fullStr | Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network |
| title_full_unstemmed | Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network |
| title_short | Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network |
| title_sort | prediction of fractional hold up in rdc column using artificial neural network |
| topic | dispersed phase hold up, RDC, artificial neural networks (ANN). |
| url | http://ijcpe.uobaghdad.edu.iq/index.php/ijcpe/article/view/494 |
| work_keys_str_mv | AT adelalhemiri predictionoffractionalholdupinrdccolumnusingartificialneuralnetwork AT suhaylaakkar predictionoffractionalholdupinrdccolumnusingartificialneuralnetwork |