软传感器通过反向应用ADM1模型来进行基质表征,用于无氧消化工厂的运行
Fernando Zorrilla1, Ma Constanza Sadino-Riquelme2, Felipe Hansen3
1Modela SpA., Encomenderos 231, Edf A, Ofc. 701, Las Condes, Santiago De Chile; ProCycla SL, Carretera Pont de Vilomara 140, 2-1, 08241 Manresa, Spain
概括
预测生物气厂的性能需要准确的基质表征,特别是在代消化过程中. 一个新的基质预测模块 (SPM) 使用无氧消化模型n1 (ADM1) 估计了入口特性,但在完全确定所有变量时面临限制.
科学领域:
- 生物化学工程 生物化学工程
- 可再生能源系统可再生能源系统
- 环境科学 环境科学
背景情况:
- 准确的基质表征对于预测生物气厂性能至关重要.
- 模拟无氧消化,特别是共消化,由于基质变异性,存在重大挑战.
- 现有的方法很难准确地定义复杂的消化系统所需的所有入口参数.
研究的目的:
- 开发和测试一种新的方法,即基质预测模块 (SPM),用于估计无氧消化中的基质特性.
- 评估使用无氧消化模型n1 (ADM1) 的反向应用的可行性.
- 评估SPM在估计代消化输入参数中的准确性和局限性.
主要方法:
- 一个基板预测模块 (SPM) 的开发.
- 使用虚拟代码处理数据来测试SPM.
- 使用无氧消化模型n1 (ADM1) 的反向应用作为SPM的核心.
主要成果:
- 根据特定的输出参数,SPM成功估计了某些基质特性.
- 该方法证明了对无氧消化模型的输入进行表征的潜力.
- 在SPM准确确定所有所需基质变量的能力方面发现了局限性.
结论:
- 开发的基质预测模块 (SPM) 显示出对估计一些无氧消化基质特性有前途.
- 需要进一步改进,以克服在准确确定ADM1.1的所有必要输入变量的局限性.
- SPM提供了一个潜在的工具来改进生物气厂的建模,特别是在共消化场景中.
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