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确定不确定性对水泥制造厂排放的影响量化:基于替代模型的替代方法
Muhammad Usman1, Iftikhar Ahmad1,2, Manabu Kano3
1Department of Chemical Engineering, School of Chemical and Materials Engineering, National University of Sciences and Technology, H-12, Islamabad 44000, Pakistan.
ACS omega
|March 17, 2025
概括
这项研究量化了工艺不确定性如何影响水泥厂的排放. 使用人工神经网络和多项混沌扩展,它准确地预测了CO2,O2,CO和NOx的变化.
科学领域:
- 化学工程是化学工程的重要组成部分.
- 环境科学 环境科学
- 过程控制 过程控制
背景情况:
- 水泥制造需要稳定的运作,以尽量减少资源消耗并最大限度地提高生产率.
- 料成分和运行条件的过程不确定性挑战了水泥厂的稳定运行.
- 量化这些不确定性对排放的影响对于环境管理至关重要.
研究的目的:
- 量化分析输入不确定性对水泥制造排放的集体影响.
- 开发和验证用于水泥厂的不确定性量化框架.
- 在不同的工艺条件下预测CO2,O2,CO和NOx等排放.
主要方法:
- 开发了使用最小平方启动和人工神经网络 (ANN) 的预测模型.
- 使用多项式混沌扩展 (PCE) 来量化不确定性.
- 在 PCE 框架内使用 ANN 模型作为代用.
- 在关键输入变量中模拟了±10%的不确定性:料流量,炉气流量,三级空气流量和煤气流量.
主要成果:
- 与最小方形启动相比,ANN模型在预测排放方面表现出更高的准确性.
- 该PCE框架成功量化了输入不确定性对排放的集体影响.
- 预测的CO2,O2,CO和NOx排放变化是根据输入不确定性进行评估的.
结论:
- 拟议的框架准确量化了不确定性对水泥厂排放的影响.
- 这种方法为优化水泥制造工艺的稳定性和效率提供了宝贵的见解.
- 有效的不确定性量化有助于减轻环境影响和改善过程控制.
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