Our team in theory and computations is the backbone of scientific and engineering research, enabling understanding and predicting complex phenomena. This field encompasses a diverse range of methodologies and techniques that aid in the exploration and analysis of various systems and processes.

Our teams pursue the First principal modeling and develop theoretical models based on fundamental physical laws and principles. These models provide a rigorous and systematic approach to understanding the behavior and properties of materials and systems. Molecular and ab-initio simulations utilize computational techniques to investigate the behavior of molecules and materials at the atomic and molecular levels. By simulating the interactions and dynamics of atoms and molecules, researchers gain valuable insights into the structure, properties, and behavior of materials.

Computational Fluid Dynamics (CFD) is a powerful tool for studying fluid flow and heat transfer phenomena. It involves the numerical simulation of fluid dynamics using computational algorithms and models. CFD enables researchers and engineers to analyze and optimize fluid flow patterns, predict the performance of devices, and study complex fluid-structure interactions.

Process modeling, simulation, and optimization are crucial in various industries and fields. By developing mathematical models that represent real-world processes, our researchers can simulate and analyze the behavior and performance of these processes. Numerical methods are employed to solve the mathematical equations involved in process simulations, allowing for accurate predictions and optimization of process parameters. Reaction kinetics and modeling focus on understanding the rate at which chemical reactions occur. Developing mathematical models that describe these reactions is one of the core research areas in the department. Researchers can predict reaction outcomes, optimize reaction conditions, and design efficient chemical processes by studying the reaction kinetics and developing models. Scaling analysis is fundamental to theory and computations, particularly in studying physical phenomena across scales. It involves analyzing how system properties and behaviors change as the size or conditions of the system are varied. Scaling analysis allows researchers to extract fundamental relationships and principles that govern the behavior of systems and can be used to design and optimize processes.

Group Leaders:

Dr. Abir Ghosh, Dr. Debdip Bhandary, Dr. Dinesh B., Dr Ganesh Madabattula, Dr. Pradeep Ahuja, Dr. Rajesh Upadhyay, Dr. Ravendra Gundlapalli, Dr. Sanjay Katheria, Dr Satarupa Dutta, Dr. Udita U. Ghosh, Dr. Vijay Shindes