Artificial neural network modeling of a multiphase photodegradation system

• Published in: Journal of photochemistry and photobiology. A, Chemistry. Vol. 149; no. 1; pp. 139 - 146
• Main Authors: Pareek, V.K, Brungs, M.P, Adesina, A.A, Sharma, Raj
• Format: Journal Article
• Language: English
• Published: Lausanne Elsevier B.V 28.06.2002; Elsevier Science
• Subjects: Artificial neural networks (ANN); Backpropagation; Bayer liquor; Chemistry; Exact sciences and technology; General and physical chemistry; Photochemistry; Photodegradation; Physical chemistry of induced reactions (with radiations, particles and ultrasonics); Photodegradation; Backpropagation; Artificial neural networks (ANN); Bayer liquor; Multiphase system; Backpropagation algorithm; Feedforward neural nets; Algorithm performance; Spent liquor; Theoretical study; Photochemical reactor; Chemical degradation; Metallurgy; Viscous solution

Photodegradation of spent Bayer liquor was carried out in an 18 l pilot scale photoreactor. The experimental data indicated that the average reaction rate was a complex nonlinear function of various process variables, such as lamp power, catalyst loading, initial solution pH, liquid batch time, and...