Primary focus of research in our group is in Development of Multi-scale, and multi-physics computational models, physics informed learning methods, Hybrid Numerical and Data-driven approaches, and real-time observations through imaging and other lab-scale experimentation.

Processing of materials at the solid, liquid and semi-solid, and even vapour states is inherent to engineering and design of structural components in transport, energy and food sectors, and typically involves phenomena occurring over a range of time/length scales and multiple phases. In addition, several natural phenomena in oceans, magma and fluids involve such physical aspects. Research in our laboratory is aimed at studying microstructure formation and heat+mass transfer processes in materials, using computational, data-driven as well as experimental approaches, both at system and microstructural levels. 

A key challenge is the linkages between scales, which if unaddressed, predictive simulations are not practical. We develop approaches that utilize reliable macroscopic information (in the form of Temperature, Flow, Stress-strain, & Composition fields) to make predictions at the small scales, without having to resolve the smallest scale. The macroscopic information are obtained using conventional CFD/FEM and Granular flow models, while validation for small-scale phenomena are obtained using in-house microstructure simulations (Cellular Automata, Phase-field, Volume-of-fluid based interface capture, as well as Discrete Element Methods (DEM))

Further real-time experimental data is analyzed and data-analytics tools are developed for process monitoring, control, and validation. 

The applications are diverse and interdisciplinary, for e.g., from cryobiology to superalloys. The tools employed in the numerical studies are multi-scale interface tracking methods, Physics-informed learning methods, CFD/FEM and image-based modelling.