A complementary approach of response surface methodology and an artificial neural network for the optimization and prediction of low salinity reverse osmosis performance
- Brooke, Ryan
- Fan, Linhua
- Khayet Souhaimi, Mohamed
- Wang, Xu
DOIAbstract
The treatment of saline water sources by reverse osmosis (RO) is being utilized increasingly to address water shortages around the world. The application of RO is energy-intensive; therefore, plant and process optimization are crucial. The desalination of low salinity water sources with total dissolved solids (TDS) of <5000 mg/L is less energy intensive than the desalination of highly saline seawater and brackish water. A gap exists in optimization studies on lower salinity water (TDS = 500-5000 mg/L). The novelty of the study is the development of a complementary approach using response surface methodology (RSM) and an artificial neural network (ANN) for performance modelling, optimization, and prediction of RO desalination of low salinity...
Add to ORKG