Contribution of self-organizing maps in the classification of water resources in the production of drinking water by ultrafiltration
The ultrafiltration process has become essential in most drinking water production facilities. However, the variation in water quality remains difficult to manage, especially during major fouling phenomena. For this reason, the objective of this study is to develop a membrane fouling prediction tool...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2023-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://www.matec-conferences.org/articles/matecconf/pdf/2023/06/matecconf_sfgp23_08004.pdf |
| _version_ | 1797807585616723968 |
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| author | Dagher Ghadi Martin Alexis Gilbert Jean-Emmanuel Moulin Laurent Croue Jean-Philippe Teychene Benoit |
| author_facet | Dagher Ghadi Martin Alexis Gilbert Jean-Emmanuel Moulin Laurent Croue Jean-Philippe Teychene Benoit |
| author_sort | Dagher Ghadi |
| collection | DOAJ |
| description | The ultrafiltration process has become essential in most drinking water production facilities. However, the variation in water quality remains difficult to manage, especially during major fouling phenomena. For this reason, the objective of this study is to develop a membrane fouling prediction tool based on seasonal water quality variation. For this, monthly monitoring of 6 water resources in Poitiers and Paris over 8 months was carried out, in which a filtration test was carried out on all the resources to assess their fouling potential and 13 physico-chemical parameters were measured. The collected data were used to build a self-organizing map (SOM) to classify water resources according to their fouling potential. The resulting SOM is able to classify the water resources according to the measured parameters into four clusters: (1) Waters with high TOC and turbidity with high fouling tendency, (2) Waters with average TOC and turbidity with average fouling tendency, (3) Waters with low TOC and turbidity that induce negligible fouling and (4) Very good quality waters that do not cause fouling. |
| first_indexed | 2024-03-13T06:24:47Z |
| format | Article |
| id | doaj.art-73371a3edfc54512ba45081ef27dc1c8 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-03-13T06:24:47Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-73371a3edfc54512ba45081ef27dc1c82023-06-09T09:28:20ZengEDP SciencesMATEC Web of Conferences2261-236X2023-01-013790800410.1051/matecconf/202337908004matecconf_sfgp23_08004Contribution of self-organizing maps in the classification of water resources in the production of drinking water by ultrafiltrationDagher Ghadi0Martin Alexis1Gilbert Jean-Emmanuel2Moulin Laurent3Croue Jean-Philippe4Teychene Benoit5IC2MP (UMR CNRS 7285), Université de PoitiersEau de Paris, DRDQE, Laboratoire R&DAquassayEau de Paris, DRDQE, Laboratoire R&DIC2MP (UMR CNRS 7285), Université de PoitiersIC2MP (UMR CNRS 7285), Université de PoitiersThe ultrafiltration process has become essential in most drinking water production facilities. However, the variation in water quality remains difficult to manage, especially during major fouling phenomena. For this reason, the objective of this study is to develop a membrane fouling prediction tool based on seasonal water quality variation. For this, monthly monitoring of 6 water resources in Poitiers and Paris over 8 months was carried out, in which a filtration test was carried out on all the resources to assess their fouling potential and 13 physico-chemical parameters were measured. The collected data were used to build a self-organizing map (SOM) to classify water resources according to their fouling potential. The resulting SOM is able to classify the water resources according to the measured parameters into four clusters: (1) Waters with high TOC and turbidity with high fouling tendency, (2) Waters with average TOC and turbidity with average fouling tendency, (3) Waters with low TOC and turbidity that induce negligible fouling and (4) Very good quality waters that do not cause fouling.https://www.matec-conferences.org/articles/matecconf/pdf/2023/06/matecconf_sfgp23_08004.pdf |
| spellingShingle | Dagher Ghadi Martin Alexis Gilbert Jean-Emmanuel Moulin Laurent Croue Jean-Philippe Teychene Benoit Contribution of self-organizing maps in the classification of water resources in the production of drinking water by ultrafiltration MATEC Web of Conferences |
| title | Contribution of self-organizing maps in the classification of water resources in the production of drinking water by ultrafiltration |
| title_full | Contribution of self-organizing maps in the classification of water resources in the production of drinking water by ultrafiltration |
| title_fullStr | Contribution of self-organizing maps in the classification of water resources in the production of drinking water by ultrafiltration |
| title_full_unstemmed | Contribution of self-organizing maps in the classification of water resources in the production of drinking water by ultrafiltration |
| title_short | Contribution of self-organizing maps in the classification of water resources in the production of drinking water by ultrafiltration |
| title_sort | contribution of self organizing maps in the classification of water resources in the production of drinking water by ultrafiltration |
| url | https://www.matec-conferences.org/articles/matecconf/pdf/2023/06/matecconf_sfgp23_08004.pdf |
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