Mathematical Modeling of the Reduction of Safranin onto Chemically Modified Rice Husks in Stirred Tank Reactor Using Response Surface Methodology and Artificial Neural Network

ABSTRACT

The effluents coming from the dye industries are colored and polluted, and the disposal of these wastes into receiving waters causes damage to the water as well as the environment. The use of rice husk for the removal of dye from wastewater has been explored in a stir tank reactor. The effects of operation variables such as adsorbent dosage, contact time, dye concentration, initial pH, and agitation on the removal of safranin were investigated in a stirred tank reactor. The combined effect of various process parameters on dye removal were analyzed using response surface methodology (RSM), and the modeling of the process parameter had been done using the artificial neural network simulation method. It was observed that response surface methodology can determine the optimization of the process parameters and the model derived from the simulation of the artificial neural network (ANN) (deviation from experimental results was ～0.09%) described the process variable efficiently. It was observed that at the initial solution pH of 6.28 and adsorbent dosage of 15.63 g L^?1, dye removal of safranin was 97%.