Xiaodong Zhang, Yuepeng Jiang, Ke Li, Yu Sun
2024.1.1Energy Harvesting and Systems
tlooto Summary
A machine-learning sequence-based modeling approach is suggested for coagulation process of saltwater with a long lag that offers a solid foundation for managing flocculant and coagulant assistance reduction.
Abstract
Abstract To control water quality and seawater desalination dosage, modeling the coagulation process of saltwater is crucial. With a focus on the features of seawater coagulation with a long lag, a machine-learning sequence-based modeling approach is suggested. The link between influent and effluent turbidities, flow rates, flocculant and coagulant dosages, and other parameters is modeled using structured units such as a gate recurrent unit encoder and a linear network decoder. The model’s validity is confirmed by numerical experiments based on real operating data, which also offer a solid foundation for managing flocculant and coagulant assistance reduction.
Citation format
ZHANG, Xiaodong, et al. Energy-saving analysis of desalination equipment based on a machine-learning sequence modeling. Energy Harvesting and Systems, 2024, 11.