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介于多物理建模、高性能计算和数据驱动方法之间。21世纪带来了微制造技术(LCD、3D打印等)的革命。这需要在低于目前可获得的范围内理解和有效地部署知识。进入数据驱动的方程发现技术：新的代理建模方法，可以在有模拟或实验数据但传统推导方法崩溃的情况下提供洞察。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来产生对小规模流体流动的新的有意义的理解。该项目将涉及数学建模、渐近分析、计算流体力学和数据驱动方法之间的有效相互作用，以及更广泛的多物理元素和不同类型的方法。下面提供了几个有用的资源，展示了这些技术在相关背景下的一些能力，并为这一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.