优化石油工业废水处理系统,并提出使用电凝化学氧气需求去除的经验相关性,并通过人工神经网络预测系统的性能
Atef El Jery1, Hayder Mahmood Salman2, Nadhir Al-Ansari3
1Department of Chemical Engineering, College of Engineering, King Khalid University, Abha, King Saudi Arabia.
PeerJ
|October 2, 2023
概括
电凝能有效地消除了炼油厂废水中的化学氧气需求 (COD). 优化条件和机器学习模型准确预测COD去除,有助于环境可持续性.
科学领域:
- 环境科学 环境科学
- 化学工程是化学工程的重要组成部分.
- 水处理技术水处理技术
背景情况:
- 环境退化需要有效的石油工业废水处理.
- 电凝是消除化学氧气需求 (COD) 的一个有前途的技术.
研究的目的:
- 实验性地研究电凝法用于从炼油厂废水中去除COD.
- 确定最佳运行条件并开发用于COD清除的预测模型.
主要方法:
- 单因子实验设计以优化电流密度,pH和NaCl度等参数.
- 开发相关性方程和人工神经网络 (ANN) 模型,用于COD移除预测.
- 使用双因子模型,分析随时间推移的COD去除效率.
主要成果:
- 对于COD去除的最佳条件是: 24 mA/cm2,pH 8,500 mg/l COD,25.26 cm2的电极面积,0.5 g/l的NaCl.
- 在20分钟的反应时间内达到最大的COD去除.
- 安纳模型表现出高准确度,MAE为1.12%,R2为0.99.
结论:
- 电凝对于处理石油工业废水非常有效.
- 机器学习模型可以准确预测COD去除,并有可能取代传统方法.
- 优化的电凝和预测建模有助于可持续的废水管理.
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