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相关概念视频

Testing Water Quality01:14

Testing Water Quality

179
When the quality of water for concrete preparation is uncertain, its impact on the setting time of cement and compressive strength of mortar is assessed by comparison with de-ionized or distilled water benchmarks. American Society for Testing and Materials (ASTM) C1602 requires the setting times to be within 90 minutes of the control, British Standard (BS) 3146:1980 allows a 30-minute variance in the initial setting, while British Standards European Norm (BS EN) 1008 specifies initial setting...
179

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Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds
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用于饮用可重复使用的NDMA软传感器:模型开发研究

K B Newhart1, K A Thompson2, A Branch2

  • 1Oregon State University, 105 SW 26th St., Corvallis, OR 97331, USA.

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|August 29, 2025
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概括

实时监测N-二甲基胺 (NDMA) 是一个挑战. 这项研究使用机器学习开发了一种数据驱动的软传感器,以优化紫外线处理,在水再利用设施中实现显著的能源节约.

关键词:
基于数据的决策间接可饮用的再利用机器学习模型开发反透技术微量有机污染物

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科学领域:

  • 环境工程
  • 水处理技术
  • 分析化学

背景情况:

  • N-二甲基胺 (NDMA) 是饮用水中的致癌污染物.
  • 由于缺乏实时分析方法,目前的NDMA监测和处理往往耗费大量能源.
  • 间接饮用再利用设施在优化NDMA去除处理方面面临挑战.

研究的目的:

  • 开发一个数据驱动的软传感器,用于实时预测N-二甲 (NDMA).
  • 优化紫外线消毒剂量控制,以消除 NDMA 在间接饮用重复使用中.
  • 模拟和量化水处理过程中的潜在节能.

主要方法:

  • 采用了来自全面反透 (RO) 间接饮用再利用设施的过程数据.
  • 应用统计和机器学习 (ML) 方法,包括主要组件分析 (PCA) 和支持矢量机器 (SVM).
  • 开发了一个软传感器模型来预测NDMA水平以控制紫外线剂量.

主要成果:

  • 主要组件分析 (PCA) 通过降低传感器噪声显著提高了统计和机器模型的准确性.
  • 与PCA结合的支持矢量机器与传统方法相比降低了13-31%的能量.
  • 基于NDMA的不同监管限制和安全因素,模拟显示了节能效果.

结论:

  • 数据驱动的建模和软传感器为水处理中的实时NDMA控制提供了可行的解决方案.
  • 实施先进的数据分析技术可以在饮用再利用设施中节省大量能源.
  • 这种方法可以精确控制关键处理单元,解决传感环境中的挑战.