Naveen Kumar Subramanian

Physics Informed Neural Networks in FLuid Dynamics Solving PDEs Using Physics Informed Neural Networks(PINNs) Parametric Study of PINNs using SimNet Tool Implementing a Standard PDEs (Heat Equation and Navier Stokes Equation ) in SimNet. Systematic Study of SimNet Tool in comparison to Conventionals CFD Tools (OpenFOAM)

• Analysed different designs of compact heat exchangers • Implemented tests of all basic heat transfer functions • Ensured Error and Warning alerts were issued at the set levels

• Employed different combinations of AI modules to create pipelines of data measuring fractures in gearing mechanisms and validated model accuracy using that data • Generated automated tests for validation of the data • Analysed and compared model performance

• Employed the Functional Mock-up Interface (FMI) as a standard that defines a container and an interface to exchange dynamic models using a combination of XML files, binaries and C code • Performed multi-body simulations to analyse and evaluate moving paths, speeds, accelerations, forces or moments, as well as perform some fluid dynamics and heat transfer calculations • Developed models incorporating co-simulation techniques using Dymola software platform

Worked with an in-house billing application at Telefónica Germany GmbH & Co, using PL\SQL scripts, to assist the Production Support team to correct billing errors identified by clients

Computational Fluid Dynamics, Visual Data Analytics, Numerical Programming ,Micro Fluid Simulation, Image Processing in Physics, Scientific Computing, Parallel Programming, Advanced Programming

Fluid Mechanics, Heat and Mass Transfer, Finite Element Analysis, Thermodynamics, Design of Machine Elements, Thermal Engineering, Calculus, Linear Algebra, Numerical Methods