在污泥处理过程中对亚临界湿氧化进行多标准优化
Dengting Guo1, Wei Yu1, Brent R Young2
1Department of Chemical & Materials Engineering, University of Auckland, Auckland, New Zealand.
Chemosphere
|September 1, 2024
概括
亚临界湿氧化 (SWO) 提供了环保的污水污泥减少. 遗传算法优化了SWO条件,实现了显著的污泥解构和污染物去除,以实现可持续的废水管理.
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.
- 废水处理 废水处理
背景情况:
- 亚临界湿氧化 (SWO) 是减少污水污泥体积的一种有前途的技术.
- 缺少SWO条件的全面优化,阻碍了其广泛应用.
研究的目的:
- 开发和应用使用遗传算法 (GA) 的多目标模型来优化SWO条件.
- 在优化过程中考虑污泥解构,排放,能源平衡和资源回收.
主要方法:
- 开发一个包含遗传算法 (GA) 的多目标模型.
- 分析关键参数:温度,反应时间和严重性因子.
- 预测最佳条件的实验验证.
主要成果:
- 多标准优化突出了SWO的显著环境效益,包括减少污泥量和去除污染物.
- 在271±2°C和51±1分钟的最佳SWO条件下进行预测.
- 实验证实,预测结果与实际结果之间的差异很小 (12%).
结论:
- 这项研究提供了有效的污水污泥处理使用优化SWO的实用见解.
- 遗传算法对于优化复杂的环境过程,如SWO,是有效的.
- 优化SWO通过减少污泥和资源回收,为可持续的废水管理做出了贡献.
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