Fundamental physics or data science? Why not both: a data-driven modelling framework for interfacial microflows

这个令人兴奋的项目位于多物理建模，高性能计算和数据驱动方法之间的接口。21世纪世纪带来了微制造技术（LCD、3D打印等）的革命。这就需要在低于目前可获得的规模上理解和有效部署知识。进入数据驱动的方程发现技术：新的替代建模方法，可以在模拟或实验数据可用的情况下提供洞察力，但传统的推导方法会崩溃。我们的挑战是创建一个新的计算框架，利用这些方法的力量，在小尺度上产生新的有意义的理解流体流动。该项目将涉及数学建模，渐近分析，计算流体动力学和数据驱动的方法之间的有效相互作用，以及多物理元素和更普遍的异构方法。下面提供了一些有用的资源，展示了这些技术在相关环境中的一些功能，并为这个快速发展的研究领域提供了更广阔的视角。

This exciting project lives at the interface between multi-physics modelling, high performance computing and data-driven approaches. The 21st century has brought a revolution in micromanufacturing techniques (LCD, 3D printing etc.) that require understanding and efficient deployment of knowledge at scales below those currently accessible. Enter data-driven equation discovery techniques: novel surrogate modelling methods which can provide insight in scenarios in which simulation or experimental data are available, but traditional derivation approaches break down. Our challenge is to create a new computational framework that harnesses the power of these approaches towards generating new meaningful understanding of fluid flows at small scales.The project will involve a productive interplay between mathematical modelling, asymptotic analysis, computational fluid dynamics and data-driven methods, as well as multi-physics elements and heterogeneous approaches more generally. Several useful resources are provided below, showcasing some of the capabilities of these techniques in related contexts, as well as providing a broader perspective into this rapidly evolving research area.