I'm a final-year Aerospace Engineering student at RV College of Engineering, Bengaluru, working across orbital mechanics, computational fluid dynamics, structural meshing automation, and propulsion system design and test.
I try not to stop at the simulation β every project here goes from theory to a build, a test rig, or a working script.
- LEO constellation orbital propagation (SGP4/HPOP) and conjunction/collision-risk analysis
- Satellite subsystem-level modeling within larger interdisciplinary systems
- Interest in space situational awareness and collision-avoidance strategy
Tools: ANSYS Fluent Β· ANSA Β· SolidWorks Flow
- Compressible / supersonic flow β oblique shocks, shockβboundary-layer interaction
- Propeller and rotor aerodynamics (blade element momentum theory, thrust/drag prediction)
- Solver validation against benchmark cases before trusting a new geometry
- Slosh and internal-flow analysis for fuel systems
Tools: BETA CAE ANSA Β· Python (OOP scripting)
- Scripting commercial FEA/meshing tools instead of clicking through them by hand
- Mesh-quality-controlled, batchable pipelines for mesh-convergence studies
- Turning one-off analyses into repeatable, logged workflows
- Variable-pitch propeller design: blade theory β CAD β CFD β 3D-printed prototype β test rig
- Formula Student fuel and dry-sump oil tank design, cross-validated against two independent sizing methods
- Interest in the full loop: design β predict β build β measure β compare
Tools: MATLAB Simulink Β· Arduino
- Block-diagram modeling of full sensor-to-actuator signal chains (pressure regulation, 4β20 mA sensing)
- Custom test-rig instrumentation: non-contact RPM sensing, thrust measurement, serial data acquisition
- Optical wireless communication (Li-Fi/VLC) prototyping across two hardware generations
| Project | Focus |
|---|---|
| LEO Satellite Conjunction Analysis | Orbital propagation (STK/HPOP) and collision-risk analysis for a LEO constellation digital twin |
| ANSA Python Meshing Automation | OOP Python scripting of BETA CAE ANSA for automated, quality-controlled camshaft meshing |
| Variable Pitch Propeller Test Bench | BEMT design β CFD across 16 pitch configs β 3D-printed prototype β Arduino RPM/thrust rig |
| Formula Student Fuel & Oil Tank Design | Endurance-run fuel and dry-sump oil tank sizing, CFD slosh validation |
| Surface Roughness Effect on Shock Angle | RANS/SST kβΟ CFD study of oblique shock behavior on a Mach 3 double-wedge model |
| Simulink Pneumatic Test Bench | Full pneumatic signal-chain model β compressor, tank, relief logic, 4β20 mA sensing |
| Li-Fi Optical Wireless Data Transmission | Laser-based visible-light-communication prototype, two hardware generations |
| Disaster Relief Modular Workstation π | Air-deployable 75 kg field station β Vyoma Design-a-thon runner-up |
Aerospace / Simulation
STK Β· ANSYS Fluent Β· ANSA Β· SolidWorks Β· MATLAB Simulink Β· OpenProp Β· CFturbo Β· OpenFOAM Β· Pointwise / Fidelity (2D Meshing)
Programming
Python Β· MATLAB Β· Arduino C/C++
Engineering Domains
CFD Β· FEA Β· Orbital Mechanics Β· Controls & Instrumentation Β· Propulsion Β· Structural Design
Hardware & Test
Arduino Β· Serial Data Acquisition Β· Custom RPM/Thrust Rigs Β· Laser Diode / Photodiode Sensing
Problem / Requirement
β
Analytical Model (first principles)
β
CAD / Simulation (CFD, FEA, Simulink)
β
Automation & Scripting (where the workflow repeats)
β
Physical Prototype
β
Experimental Test & Measurement
β
Compare Predicted vs. Measured β Engineering Conclusion
I care less about "did the simulation run" and more about does it hold up against a benchmark case, a test rig, or a second independent method β that comparison shows up somewhere in most of the projects above.
Turbomachinery Design Β· Gas Turbine Engines Β· Systems Engineering
CFD Β· FEA & Simulation Automation Β· Instrumentation
Hands-On Hardware & Mechanical Design Β· Design for Manufacturing (DFM) Β· Engineering Innovation
I'm drawn to problems that sit at the intersection of these β turbomachinery and gas turbine systems in particular, where aero-thermal simulation, structural analysis, manufacturability, and physical test all have to agree with each other before a design is actually good. That's the same loop I keep coming back to across the projects above: model it, automate the repetitive parts, build it, and check the hardware against the prediction.
Beyond the projects above, I'm actively building toward:
- Design Automation β scripting CAD/CFD/FEA workflows (in the spirit of the ANSA meshing project) so engineering iteration cycles get faster, not just individual analyses
- Machine Learning for Aerospace Design β using data-driven models to speed up or supplement traditional simulation, especially in design-space exploration and optimization
- Data Analytics in Aerospace Engineering β extracting engineering insight from test and simulation data at scale, rather than one-off manual post-processing
The common thread: less time spent re-running the same analysis by hand, more time spent on the engineering decision it's meant to inform.
LinkedIn: linkedin.com/in/tejas-l Email: 050tejasl@gmail.com Resume: Download CV (PDF)