Data-driven modelling of complex reactive flows

复杂反应流的数据驱动建模

• 批准号: FT190100361
• 负责人: Prof Yansong Shen
• 金额: $ 61.76万
• 依托单位: The University of New South Wales
• 依托单位国家: 澳大利亚
• 项目类别: ARC Future Fellowships
• 财政年份: 2020
• 资助国家: 澳大利亚
• 起止时间: 2020-05-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FT190100361
• 关键词: Data; driven; modelling; complex; reactive

Complex reactive flow is dominant in many chemicals, physical and biological processes and should be optimised online for operational efficiency and stability, yet it is hindered by the lack of reliable model techniques. The project tackles this challenge by developing a next-generation data-driven modelling approach via integrating continuum/discrete-scale fluid-particle dynamics with system/control theories, supported by lab/plant experiments. Driven by online data, the generic approach can open up a powerful way to reliably describe the inner state of reactors and online predict operation anomalies. The outcomes can help transform a range of industries to smart manufacturing and design, which is vital to Australia's technological future.

复杂的反应流在许多化学、物理和生物过程中占主导地位，应在线优化以提高操作效率和稳定性，但由于缺乏可靠的模型技术，这一过程受到阻碍。该项目通过开发下一代数据驱动的建模方法来应对这一挑战，该方法通过将连续/离散尺度流体粒子动力学与系统/控制理论相结合，并得到实验室/工厂实验的支持。在在线数据的驱动下，通用方法可以为可靠地描述反应堆内部状态和在线预测运行异常开辟一条强有力的途径。这些成果有助于将一系列行业转变为智能制造和设计，这对澳大利亚的技术未来至关重要。