
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Nanofiltration performance prediction for brackish water desalination: case study of Tunisian groundwater

Nanofiltration performance prediction for brackish water desalination: case study of Tunisian groundwater
In response to the fresh water scarcity, Tunisia is utilizing more and more membrane desalination of unconventional resources, including brackish waters and seawater. The widespread reserves of groundwaters and their low salinity make this resource of special interest. Two predominant ionic compositions have been identified depending on their relative proportion of sulfate to chloride ions. The question arising for the decision-makers concerns the choice of membrane technology and, therefore, of membrane. Two nanofiltration (NF) membranes (NF270 and NF90) and a reverse osmosis (RO) one (BW30) were tested in a desalination study of synthetic feeds reproducing the ionic composition of three representative groundwaters. Sulfate/chloride ratio appears to be the key factor for the membrane choice to obtain good quality drinking water meeting the Tunisian standards. Moreover, validation of two prediction tools was investigated: ROSA, software provided by the membrane manufacturer and Nanoflux ® , software specifically designed for NF. The experimental NF results are well fitted by the Nanoflux ® simulations. We concluded that ROSA cannot generally provide good NF predictions because it does not take into account the electric interactions between membrane and feed.
- Institut Européen des Membranes France
- University of Sfax Tunisia
- University of Montpellier France
[SPI.FLUID]Engineering Sciences [physics]/Reactive fluid environment, Membrane desalination, Performance prediction, [SPI.NANO] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics, [SPI.FLUID] Engineering Sciences [physics]/Reactive fluid environment, Nanofiltration, [PHYS.COND.CM-SM] Physics [physics]/Condensed Matter [cond-mat]/Statistical Mechanics [cond-mat.stat-mech], Software validation, [PHYS.COND.CM-SM]Physics [physics]/Condensed Matter [cond-mat]/Statistical Mechanics [cond-mat.stat-mech], [SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics, Groundwater
[SPI.FLUID]Engineering Sciences [physics]/Reactive fluid environment, Membrane desalination, Performance prediction, [SPI.NANO] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics, [SPI.FLUID] Engineering Sciences [physics]/Reactive fluid environment, Nanofiltration, [PHYS.COND.CM-SM] Physics [physics]/Condensed Matter [cond-mat]/Statistical Mechanics [cond-mat.stat-mech], Software validation, [PHYS.COND.CM-SM]Physics [physics]/Condensed Matter [cond-mat]/Statistical Mechanics [cond-mat.stat-mech], [SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics, Groundwater
2 Research products, page 1 of 1
- 2012IsAmongTopNSimilarDocuments
- 2020IsAmongTopNSimilarDocuments
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).11 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
