Simulation of Coking Wastewater Oxidation in Supercritical Water Using an Aspen Model Combined with ANN-Based Kinetic Correlation

Coking wastewater has long been a major source of environmental pollution. Supercritical water oxidation (SCWO) is an effective technology capable of degrading such wastewater deeply into carbon dioxide, water, and nitrogen. However, due to the complex composition of coking wastewater, kinetic data for the process are limited, as establishing accurate simulation models is challenging. To address this issue, an artificial neural network (ANN) based kinetic rate correlation was developed to characterize the reaction kinetics. This data-driven model was then integrated with Aspen Plus® to simulate the degradation behavior of typical oxygen-and nitrogen-containing compounds in coking wastewater, namely phenol, pyridine, and quinoline. Phenol was simulated first to obtain temperature profiles, species concentrations, and reaction rates along the reactor height under different inlet conditions. The model was subsequently validated with other nitrogen-containing compounds. The proposed SCWO simulation approach has potential for application to other oxygen- and nitrogen-rich wastewaters.