在开放道中使用软计算技术进行循环喷气通风的性能分析和建模
Diksha Puri1, Raj Kumar2, Sushil Kumar3
1School of Environmental Science, Shoolini University, Solan, Himachal Pradesh, 173229, India.
Scientific reports
|February 7, 2024
概括
透气增强水中的溶氧 (DO),这对水质至关重要. 这项研究发现,人工神经网络 (ANN) 准确地预测了通风效率,而通道角度是最有影响力的因素.
科学领域:
- 环境工程 环境工程
- 水质管理水质管理
- 流体力学 流体力学 流体力学
背景情况:
- 溶解氧 (DO) 是水质的关键指标,常常因环氧化而耗尽.
- 透气是增加水生系统中DO度的主要方法.
- 了解开放道的通风效率对于有效的水处理至关重要.
研究的目的:
- 在开放道中实验研究圆形喷气的通风效率 (E20).
- 模拟通风效率与关键输入参数之间的关系.
- 开发和比较软计算模型来预测通风效率.
主要方法:
- 试验调查的通风效率与不同的通道倾斜,排放,和喷气的数量.
- 统计分析以确定显著的通风参数 (8-64喷气机).
- 使用WEKA软件开发人工神经网络 (ANN),M5P和随机森林 (RF) 模型.
主要成果:
- 在预测通风效率 (CC=0.9823,MAE=0.0098,RMSE=0.0123) 方面,ANN表现出卓越的性能.
- 灵敏度分析确定了道倾斜角度作为最有影响力的因素.
- 排放量和喷气数量也是通风效率的重要预测指标.
结论:
- 人工神经网络提供了一个非常准确的方法来预测在开放道中的通风效率.
- 通道倾斜角是影响通风的最关键参数.
- 该研究为优化通风系统以改善水质提供了有价值的见解.
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