Absorption cleaning methods for oily smoke gases: Performance evaluation and optimization

This study investigates the efficacy of absorption cleaning methods for reducing oily smoke gases emitted from industrial processes. Laboratory experiments are conducted to evaluate various absorbent materials and their performance under controlled conditions. Computational modeling techniques are utilized to predict the behavior of air cleaning systems and optimize their design parameters. The influence of mode-constructive indicators on cleaning efficiency is systematically analyzed, with parameters such as absorbent level, smoke temperature, and nozzle type being investigated. Results indicate that changes in these parameters significantly impact cleaning efficiency, with higher absorbent levels generally leading to improved performance. Additionally, the study finds that the type of absorbent and nozzle design play crucial roles in determining cleaning effectiveness, with the conical nozzle exhibiting slightly superior performance compared to the pall ring nozzle when using T-750 absorbent. Overall, the research highlights the effectiveness of the absorption method in removing oily smoke gases and underscores the importance of considering structural parameters and design features in optimizing air cleaning systems for enhanced efficiency.