FlowMat:用于模拟流动反应器的工具箱,使用基于物理和机器学习的方法进行模块化模拟,参数识别和反应器优化
Sebastian Knoll1, Klara Silber2,3, Jason D Williams2,3
1Institute of Automation and Control, Graz University of Technology Inffeldgasse 21b 8010 Graz Austria martin.horn@tugraz.at.
RSC advances
|September 15, 2025
概括
本研究介绍了一个开源的MATLAB/Simulink工具箱,用于流动反应器建模和优化. 它有助于研究人员进行参数确定和反应堆设计,降低成本和时间.
科学领域:
- 化学工程是化学工程的重要组成部分.
- 计算建模 计算建模
- 过程优化 过程优化
背景情况:
- 流动反应器的精确建模和优化对于高效的化学过程至关重要.
- 现有的工具可能缺乏多功能性或用于各种建模方法的整合性.
- 需要有效的参数识别和运营优化是显著的.
研究的目的:
- 为流动反应器建模和优化引入一个多功能,开源的 MATLAB/Simulink 工具箱.
- 支持各种建模范式,包括基于物理,数据驱动和混合方法.
- 展示模拟,参数识别和优化中的实际应用.
主要方法:
- 开发一个模块化,开源的 MATLAB/Simulink 工具箱.
- 实现了一个拖放界面,以方便用户使用.
- 整合基于物理,数据驱动和混合 (例如,基于物理的神经网络) 建模方法.
主要成果:
- 使用工具箱成功模拟流动反应器.
- 从实验过渡数据准确识别反应参数.
- 有效优化反应堆运行点和配置.
- 实验验证确认了工具箱的实际适用性.
结论:
- 开发的工具箱为流动反应堆技术的研究人员和工程师提供了宝贵的资源.
- 它简化了参数确定和反应堆优化过程.
- 该工具箱有可能显著降低与这些任务相关的成本和时间.
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