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How can programmatic automation, generative CAD, and high-fidelity computational fluid dynamics simulations synergistically assist aerospace engineers in crafting optimal airplane wings that cater to specific flight conditions and constraints?

Project by Polygence alum Aaditya

How can programmatic automation, generative CAD, and high-fidelity computational fluid dynamics simulations can synergistically assist aerospace engineers in crafting optimal airplane wings that cater to specific flight conditions and constraints?

Project's result

The outcomes from this project include a research paper and, once complete, a product that is free to download and fully open source. This is not the final version of the research paper as I had to keep it short to make the requirements for a separate submission however I intend to add more content and detail as well as continue my research and add more to the paper overall.

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Summary

This research explores the fusion of aerospace engineering with software workflows, specifically integrating programmatic automation and generative computer-aided design (CAD) with advanced computational fluid dynamics (CFD) simulations and optimization tools. The overarching aim is to facilitate the seamless design of aerodynamically optimized airplane wings for specific flight conditions within defined constraints. The central question guiding this research is how generative CAD, in tandem with high-fidelity CFD simulations and optimization tools, can aid aerospace engineers in crafting optimal wing designs. Undertaken by Aaditya Barbudhe, the study involves a Python script to convert user-specified NACA(National Advisory Committee for Aeronautics) four-point profiles and parameters, including angle of attack, taper, and wing length into a set of wing contour coordinates. PTC Creo CAD software uses these coordinates to construct a wing model. This model is subjected to comprehensive simulations using SU2, which yield variations in lift and drag coefficients across varied angles of attack. While further SU2 testing is pending, preliminary data analysis reveals discernible patterns in coefficient behavior, indicating the impact of changing angles of attack on lift and drag. What this demonstrates is the ability of software workflows to aid aerospace engineers in rapidly designing optimal wing designs based on their needs because it was able to quickly and cheaply provide data to engineers about how their wing would perform in a variety of conditions, allowing them to make adjustments to their design quickly to craft their optimal wing. The approach reduces reliance on resource-intensive wind tunnel experimentation by expediting simulation-driven insights, propelling innovation in aerodynamic surface design. This work underscores the synergy of CAD, CFD, and programmatic automation, offering a novel avenue for enhancing aircraft performance through optimized wing design. Further conclusions and research are pending.

Keywords: Coefficient of Drag/Lift, Angle of Attack(AoA), CAD/PTC Creo, CFD/SU2, programmatic automation,

Tanay

Tanay

Polygence mentor

PhD Doctor of Philosophy candidate

Subjects

Engineering

Expertise

aerospace engineering, mechanical design & simulation, sensors, signal processing, machine learning

Aaditya

Aaditya

Student

Hello, my name is Aaditya Barbudhe. My Polygence project is on simulating aerodynamic environments digitally in order to create a program that will allow users to cheaply and safely test their airplane wing designs. After I complete this project, I would use the program for my own use and I would like to publish it as free software for others to use.

Graduation Year

2026