👋🏼 Hello there, I’m Viknesh!
👨🏻🎓 PhD Candidate in the Scientific Computing & Imaging (SCI) Institute and the Department of Mechanical Engineering at the University of Utah, advised by Dr. Amirhossein Arzani.
🔬 Research Interests: Scientific Machine Learning, Computational Fluid Mechanics, Inverse Problems, Wildfire Dynamics, Hemodynamics, and Unsteady Aerodynamics.
🌊 Fluid Mechanics: I am strongly inclined towards Fluid Mechanics, delving into areas such as cardiovascular flow, wildfire dynamics, and unsteady aerodynamics. I also focus on developing computational methods and integrating machine learning methodologies to solve these complex problems.
🎓 Educational Background: I hold a Master’s degree in Aerospace Engineering, specializing in Aerodynamics, from IIT Kanpur, India. I had the privilege of working in the HPCL Lab with Dr. Tapan K. Sengupta and the LSA Lab with Dr. Kamal Poddar, where I focused on both Computational Fluid Mechanics and Wind Tunnel Measurements. My Bachelor's degree in Aeronautical Engineering from Anna University, Tamil Nadu, India, sparked my passion for Aerodynamics and solving PDEs.
🔬 Research Interests: Scientific Machine Learning, Computational Fluid Mechanics, Inverse Problems, Wildfire Dynamics, Hemodynamics, and Unsteady Aerodynamics.
🌊 Fluid Mechanics: I am strongly inclined towards Fluid Mechanics, delving into areas such as cardiovascular flow, wildfire dynamics, and unsteady aerodynamics. I also focus on developing computational methods and integrating machine learning methodologies to solve these complex problems.
🎓 Educational Background: I hold a Master’s degree in Aerospace Engineering, specializing in Aerodynamics, from IIT Kanpur, India. I had the privilege of working in the HPCL Lab with Dr. Tapan K. Sengupta and the LSA Lab with Dr. Kamal Poddar, where I focused on both Computational Fluid Mechanics and Wind Tunnel Measurements. My Bachelor's degree in Aeronautical Engineering from Anna University, Tamil Nadu, India, sparked my passion for Aerodynamics and solving PDEs.
🔬 Academic Research
- 🔥 Wildfire Dynamics:Discovered two new non-dimensional numbers governing convection-diffusion-reaction combustion models for the first time. Scaling analysis predicts future fire propagation without reliance on simulations (paper submitted).
- 🤖 Interpretable Machine Learning:Developed the ADAM-SINDy framework for system identification of non-linear dynamical systems, avoiding prior system knowledge (paper submitted). Check out the CRUNCH Seminar Talk.
- 🛩️ Pitching Airfoil:Identified upstream-convecting vortices (vortices advecting against the flow direction) on a pitching airfoil using Time-resolved PIV & Pressure measurements.
- 🌪️ Flow Instabilities:Sensitivity of multiple Hopf bifurcations and critical Reynolds numbers in lid-driven cavity flow problems, noting the influence of numerical methods and grid resolution.
🏭 Industrial Experience
- 🛠️ Formulation of Solver Templates:
Developed a Finite Volume Method (FVM) solver template tailored for Multiple Reference Frame (MRF) Propeller simulations, achieving a significant validation error reduction of 30%. - ✈️ Aerodynamic Performance Evaluation:
Conducted comprehensive CFD simulations of full-scale 3D electric air vehicle models, incorporating MRF zones to evaluate aerodynamic performance and static stability. - 📈 Dynamic Stability Analysis:
Performed Unsteady Reynolds-Averaged Navier–Stokes (RANS) simulations to compute dynamic stability derivatives for air vehicles. Simulations mimicked pitching, plunging, and flapping motions within a non-inertial reference frame. - 🗺️ Mesh Optimization:
Optimized grid resolution for full-scale 3D models using flow physics; Adaptive Mesh Refinement (AMR) techniques. - 🖥️ Custom UDF Development:
Developed User-Defined Functions(UDFs) to mirror rotor effects through an actuating disk model, simultaneously imposing pressure jumps and tangential/radial velocity profiles across specified areas and time intervals. - 🎛️ Control Effectiveness Evaluation:
CFD simulations to assess control effectiveness for components such as rudders, ailerons, and elevators in full-scale 3D models.
🖥️ Software and Simulations
I have developed and optimized several programs/solvers related to scientific machine learning and fluid flow problems. Please note that if the links are unavailable or denied, the corresponding papers are still under review.