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In this study, HDPE drainage pipes were utilized in static immersion experiments with waste incineration plant leachate as the water distribution object. In order to ascertain the mechanism of scaling, a combination of material characterization and scale analysis was employed. The objective of this study is to utilize a BP neural network assignment to quantify the influence of water quality factors. The primary objective is to address the challenges posed by system failure, reduced lifespan, and elevated costs resulting from pipeline fouling during the transportation of highly concentrated organic wastewater. Results showed pH, COD, and Ca2+ had varying effects: more fouling in alkaline conditions, accelerated fouling in acidic environments. Influence order: Ca2+ > COD > pH > Humus > NaHCO3 > Cl−. Combining static experiments and BP neural networks offers new insights into wastewater pipeline fouling, with findings supporting optimized piping system design.

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Research on Scaling Mechanism of High-Concentration Organic Wastewater Pipe Based on BP Neural Network

  • 会议论文

  • 发表日期：

    2026年

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  • Luziping Zhang,
  • Wenbo Liu,
  • Yanhong Wei,
  • Tingting Xiao,
  • Xiaowen Yu

摘要

In this study, HDPE drainage pipes were utilized in static immersion experiments with waste incineration plant leachate as the water distribution object. In order to ascertain the mechanism of scaling, a combination of material characterization and scale analysis was employed. The objective of this study is to utilize a BP neural network assignment to quantify the influence of water quality factors. The primary objective is to address the challenges posed by system failure, reduced lifespan, and elevated costs resulting from pipeline fouling during the transportation of highly concentrated organic wastewater. Results showed pH, COD, and Ca2+ had varying effects: more fouling in alkaline conditions, accelerated fouling in acidic environments. Influence order: Ca2+ > COD > pH > Humus > NaHCO3 > Cl−. Combining static experiments and BP neural networks offers new insights into wastewater pipeline fouling, with findings supporting optimized piping system design.