ScholarWorks@경상국립대학교

초록

This study developed a predictive model for a membrane-based wastewater reuse system for semiconductor wastewater treatment. The research, which was undertaken as part of the “Development of Semiconductor Wastewater Treatment and Reuse Technology for Securing Industrial Water” project, aimed to create an effective and safe process by predicting pollutant removal efficiency. The predictive model for organic matter, conductivity, tetramethylammonium hydroxide (TMAH), urea, and silica was initially constructed using operational data from a pilot plant and the International Water Association (IWA) Activated Sludge Model No. 2d (ASM2d). A commercial wastewater treatment simulation software, MassFlow3, was selected for its suitability, including its support for a wide range of models, reasonable pricing, and robust technical support from a domestic developer. Due to low pollutant concentrations in the pilot plant’s influent water and analytical errors, the performance of the developed model was further enhanced by correlating the ASM model’s results with the concentrations of the target substances. The results showed that the predictive model had a low average absolute error of 0.2 mg/L for all substances, with a relative error of up to 23% compared to influent water quality. While the model requires further refinement due to limited operational data, it demonstrates the feasibility and practical applicability for predicting the removal of the performance of the developed model was further enhanced in wastewater treatment systems.

키워드