Post by Sai Gawali

Sometimes, the greatest catalyst for engineering excellence is a judge telling you your hard work is "meaningless." Last winter, at the Inter IIT Tech Meet 2025 at IIT Patna, my teammate Kushagra Shahi and I took on the LAT Aerospace problem statement. The challenge was ambitious: design a wing for a STOL (Short Take-Off and Landing) aircraft capable of achieving a Lift Coefficient (C_L) of 6.5. We poured weeks of effort into our design. However, during the final evaluation, the judge delivered a blunt verdict—our CFD methodology was fundamentally flawed, rendering our simulation results invalid. It was tough to accept, but instead of walking away, we decided to double down. We wanted to prove that we could master the fluid dynamics and the methodology behind it. Returning to IIT Gandhinagar, we enrolled in a dedicated project course under the guidance of Prof. Vinod Narayanan and set out to build a robust methodology from the ground up. This became our new project: Computational Investigation and Semi-Empirical Modeling of Propeller-Wing Lift Augmentation for STOL Applications. This time, we didn't just run simulations; we proved our physics. Here is how we turned a rejected methodology into a validated engineering tool: 🔹 Rigorous Validation: Before testing anything new, we validated our isolated propeller thrust against APC manufacturer data and our unblown wing lift against canonical 1997 Selig wind-tunnel experiments. 🔹 Advanced Parametric Sweeps: We executed 32 highly complex 3D steady-state CFD simulations (ANSYS Fluent, MRF) to analyze the chaotic viscous interactions between propeller slipstreams and high-lift aerofoils. 🔹 The Physics: We achieved a 57.23% lift augmentation at 12,000 RPM, mapping out complex real-world aerodynamic phenomena like "hub starvation" and Coanda flap degradation. 🔹 The Ultimate Solution: We decoupled this computationally heavy 3D CFD into a lightweight, semi-empirical mathematical framework. By superimposing Taylor-expanded thin-airfoil theory with our empirical wake parameters, we can now predict STOL aerodynamics instantly with less than 6% error. We built a tool that bypasses the need for slow, expensive computations, rapidly accelerating the design process for future distributed electric propulsion (DEP) aircraft.That blunt feedback from the judge wasn't the end of our road—it was simply the baseline for our next iteration. I’ve attached the link to our full project report and poster detailing our methodology, the findings, and the master equation. I’d love to hear feedback from the aerospace and CFD communities! Project Report and Poster link: https://lnkd.in/dTpfssHP #CFD #ANSYS #STOL #IITGandhinagar #InterIIT #FluidDynamics #EngineeringDesign #Aerodynamics #Resilience