Research

Primary focus of research in our group is in Development of Multi-scale, and multi-physics computational models, physics informed self-learning methods, obtaining real-time insights through imaging and other lab-scale experimentation

Liquid-state material processing is inherent to manufacturing of several key products in transport, energy and food sectors, and typically involves phenomena occurring over a range of time/length scales and multiple phases. Research in our laboratory is aimed at studying solidification and heat transfer processes in materials processing, using computational as well as experimental approaches, both at system and microstructural levels.

Further real-time experimental data is analyzed and data-analytics tools are built 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 and image-based modelling. Similarly, real-time experiments are performed using X-ray, optical imaging characterization of thermal, flow and compositional fields. IITB's state of the art facilities of 2D and 3D x-ray microscopy will also be utilized to perform both ex situ and in situ experimental studies.

Several research activities are in collaboration with academicians, research labs and industrial organizations.

Collaborators:


Research Highlights

Trimmed_Remelting_Dec2017.mp4

Observations of transport phenomena during freezing of multi-component mixtures 

V. Kumar,et al., Physics of Fluids, 2018, Vol 30, Issue 11, 113603, https://doi.org/10.1063/1.5049135 ) (Featured Article)

V. Kumar et al., J. Fluid Mech., 2020, http://dx.doi.org/10.1017/jfm.2020.630 

V. Kumar et al., Role of microstructure and composition on natural convection during ternary alloy solidification. Journal of Fluid Mechanics, 2021, 913, A41. doi:10.1017/jfm.2021.1 

Multi-scale modeling of microstructural evolution, coupled with multi-physics, prediction of hot-tears, and segregation

Development of a fully parallelized 3D code

Students: Kartheek Minnikanti, G S Abhishek, J. Desai, P Pal, J. Yadav,

Pal et al., Mod. Sim. in Mater. Sci. Engg, 2020, https://doi.org/10.1016/j.matchar.2020.110733 

4D (3D+time) X-ray imaging and microtomography for revealing mechanisms of microstructures and defects during advanced processing

Students: Shishir Bhagavath, jointly supervised by Prof. Peter. D. Lee, University College London 

S. Bhagavath, et al.,10.1007/s11661-019-05378-8), Metallurgical & Materials Transactions A, EDITOR's CHOICE for Free Access, 2019 


N. Srivastava et al., Mater. Today. Commn., 2021, https://doi.org/10.1016/j.mtcomm.2020.101853