Openings
PhD positions are available. Interested candidates with a strong background in maths and physics and a deep interest in fundamental and applied fluid mechanics can email me. Please check the sections below to have a broad idea of the areas of research
For post-doctoral positions, I can collaborate to submit applications to the ANRF-National Post Doctoral Fellowship
I am an Assistant Professor in the Department of Applied Mechanics of the Indian Institute of Technology Delhi.
My research is broadly classified into nonlinear instability of transitional flows, geophysical fluid dynamics, and physical oceanography. My research has a strong component of mathematical rigour, high-performance computation, and large-scale data analysis. I am inspired by problems from the oceans and atmosphere and try to understand them using small-scale mathematical models whenever possible. I also use observational and satellite data, model output, and theory to address some of these.
I have previously focused on geophysical turbulence in the Bay of Bengal and the nonlinear non-modal stability of a viscosity-stratified wall-bounded shear flow. The latter involved developing an in-house channel flow and nonlinear stability solver. I have also studied internal wave dynamics and parameterisation in different ocean models and developing an understanding of the wave--mean flow interactions using high-resolution regional simulations of the ocean.
If you are interested in working for a long-term research project, please check the Research Team page too.
Present: Assistant Professor, Indian Institute of Technology Delhi, India
2023, Postdoctoral Research Fellow, University of Michigan, Ann Arbor, USA
2020, M.Sc. (Physics) and Ph.D., Tata Institute of Fundamental Research Bengaluru, India
2014, B. Tech (Mechanical Engineering), National Institute of Technology Silchar, India
Mathematical modelling of fluid flows
Transition to turbulence using nonlinear nonmodal stability
Computational fluid dynamics using high-performance computing
Oceanographic flows and climate change
Experimental fluid dynamics for turbulence transition
Physics-informed machine learning techniques for turbulence
Biological mixing
Science Outreach
Research overview
Laminar to turbulence transition is more than a century-old problem. Linear modal stability analysis cannot predict transition in shear flows because of the non-normality of the governing operator. A non-normal operator has non-orthogonal eigenvectors and hence a combination of two decaying eigenvectors can still grow transiently. So, shear flows need a non-modal analysis.
We employ a non-linear version of the non-modal stability analysis where the flow is a dynamical system and the flow state evolves in phase space. A turbulent state would be an attractor in that phase space. We are exploring the optimal initial condition which causes a large enough transient growth in energy to push the laminar state out of its stable manifold to turbulence.
With Arjun Sharma (Cornell) and Rama Govindarajan (ICTS)
Internal waves exist in the ocean due to density differences. These internal waves break and are one of the most important sources of deep-ocean mixing. Internal wave breaking is thought to play an important role in the global meridional overturning circulation, essentially making the oceans what they are, and regulating regional weather and global climate on shorter time scales.
Ocean models have been developed for many decades in a pursuit to represent real ocean dynamics. There are many numerical models available. I work with the MITgcm and use the model output of regional simulations of ROMS and global simulations of HYCOM to understand internal wave variability in oceans. Internal wave spectra (three bottom panels on the left figure) are a useful tool to quantify spectral variance in the vertical scales of the model. In a recently published work, we have been able to improve a regional MITgcm simulation by suggesting improvements to a very commonly used vertical mixing parameterization scheme (KPP). With these improved parameterizations and also with an increase in model vertical resolution, we are able to achieve an internal wave field comparable to that in the real ocean. These improved estimates would be crucial to improving global mixing estimates and interpreting internal wave signatures from the upcoming NASA-CNES Surface Water and Ocean Topography (SWOT) satellite mission.
The ocean houses myriad interesting phenomena. A combination of moored buoys, ship surveys, and satellite imagery helps us understand some of these.
A mooring line consists of instruments which measure temperature, salinity, speed of the currents, dissolved oxygen etc. I work with turbulence measuring instruments deployed in the Bay of Bengal to understand the feedback of the Bay to the Indian monsoon.
The Bay has been shown to have an important influence on the Indian monsoon system and is an active site for tropical cyclogenesis.
Our study quantifies the turbulent response of the upper mixed layer and the deeper thermocline of the Bay of Bengal to the varying surface forcing of the Indian monsoon seasons. In the latter half of the summer monsoon, monsoonal precipitation and river discharge create a shallow layer of low-salinity water, shutting off geophysical turbulence below the mixed layer for a few months. This isolation of subsurface heat reservoirs has consequences for upper-ocean heat and salt content and creates a layer with active air-sea interaction properties.
A part of the International Centre for Theoretical Sciences In-House Symposium 2019.