Study on optimal conditions of flocculation in deinking wastewater treatment

Abstract Flocculation is an important method to treat paper manufacturing wastewater. Coagulants and flocculants added wastewater facilitate the aggregation sedimentation of various particles in lead formation floc networks which can be easily removed using physical methods. The goal this determine optimal hydraulic conditions machine learning order enable efficient flocculation improve performance during treatment deinking Experiments polymerized aluminum chloride as flocculant were carried out. Based on orthogonal array test, 16 different combinations chosen investigate flocculation, was indicated by turbidity solution after treatment. To develop a model representing relationship between treatment, methods, support vector regression Gaussian process regression, compared, whereby chosen. According fitness function derived from model, genetic algorithm applied evaluate conditions. determined real-life experience, set implemented experimentally. After under higher stirring speed at 120 rpm for 1 min lower 20 5 temperature °C, measured NTU. reduction high 99.6%, good