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This study optimized the A2O process into a multi-stage AO process using GPS-X software and refined operational parameters through Response Surface Methodology (RSM). Initially, the multi-stage AO process was modeled and simulated using the ASM models embedded within the GPS-X software. A sensitivity analysis of various parameters was conducted, and critical parameters were adjusted to enhance model accuracy. RSM was employed to optimize operational key parameters such as dissolved oxygen (DO) in the aerobic tank, influent flow rate ratio (R), and sludge return ratio (r), exploring their impact on biochemical reaction efficiency. The results revealed significant improvements in BOD5 and TN removal rates, reaching 97.1% and 81.7%, respectively, after optimization. Compared to the A2O process, the multi-stage AO process exhibited notable advantages in reactor capacity, energy consumption, and effluent quality. This study provides a scientific and effective optimization scheme for the upgrade and retrofitting of wastewater treatment plants, demonstrating the broad application potential of the GPS-X combined with RSM in optimizing wastewater treatment processes.

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Research on Simulation and Optimization of Multi-stage AO Process Based on GPS-X Software

  • 会议论文

  • 发表日期：

    2025年

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  • Yuzhou Zhang,
  • Li He,
  • Zongkai Ma,
  • Yawen Luo,
  • Xueping Liu,
  • Zengzhu Wang,
  • Xiaowen Ma,
  • Yuan An

摘要

This study optimized the A2O process into a multi-stage AO process using GPS-X software and refined operational parameters through Response Surface Methodology (RSM). Initially, the multi-stage AO process was modeled and simulated using the ASM models embedded within the GPS-X software. A sensitivity analysis of various parameters was conducted, and critical parameters were adjusted to enhance model accuracy. RSM was employed to optimize operational key parameters such as dissolved oxygen (DO) in the aerobic tank, influent flow rate ratio (R), and sludge return ratio (r), exploring their impact on biochemical reaction efficiency. The results revealed significant improvements in BOD5 and TN removal rates, reaching 97.1% and 81.7%, respectively, after optimization. Compared to the A2O process, the multi-stage AO process exhibited notable advantages in reactor capacity, energy consumption, and effluent quality. This study provides a scientific and effective optimization scheme for the upgrade and retrofitting of wastewater treatment plants, demonstrating the broad application potential of the GPS-X combined with RSM in optimizing wastewater treatment processes.