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

Supervisors: Radu Cimpeanu; James Sprittles; Albert Bartok-Partay

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.

[1] Rudy et al., Data-driven discovery of partial differential equations, Science Advances 3: e1602614, 2017.

[2] Brunton et al., Machine learning for fluid mechanics, Annual Reviews of Fluid Mechanics 52: 477-508, 2020.

[3] Cimpeanu et al., Active control of liquid film flows: beyond reduced-order models, Nonlinear Dynamics 104: 267-287, 2021.

[4] Sprittles, Kinetic effects in dynamic wetting, Physical Review Letters 118: 114502, 2017.

[5] Bartok et al., Machine learning unifies the modeling of materials and molecules, Science Advances 3: e1701816, 2017.

Are you interesting in applying for this project? Head over to our Study with Us page for information on the application process, funding, and the HetSys training programme

At the University of Warwick, we strongly value equity, diversity and inclusion, and HetSys will provide a healthy working environment, dedicated to outstanding scientific guidance, mentorship and personal development.

HetSys is proud to be a part of the Physics Department which holds an Athena SWAN Silver award, a national initiative to promote gender equality for all staff and students. The Physics Department is also a Juno Champion, which is an award from the Institute of Physics to recognise our efforts to address the under-representation of women in university physics and to encourage better practice for both women and men.