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Machine Learning in Aircraft Design: A Comprehensive Review of Optimization, Aerodynamics and Structural Applications

This B.Tech Aerospace / Aeronautical Engineering project is based on the recent research direction ‘Machine Learning in Aircraft Design: A Comprehensive Review of Optimization, Aerodynamics and Structural Applications’. The project focuses on…

Project Overview This B.Tech Aerospace / Aeronautical Engineering project is based on the recent research direction 'Machine Learning in Aircraft Design: A Comprehensive Review of Optimization, Aerodynamics and Structural Applications'. The project focuses on applying artificial intelligence, machine learning, deep learning, computer vision, reinforcement learning, surrogate modelling, or RAG-style intelligent assistance to the Aircraft Design Projects area. Students can use the linked 2023-onward research paper/source as the academic base, then convert it into an implementation-focused final-year project with a simplified dataset, simulation model, Python workflow, dashboard, or prototype demonstration.
Research Paper Title Machine Learning in Aircraft Design: A Comprehensive Review of Optimization, Aerodynamics and Structural Applications
Research Paper / PDF Link Open Paper / PDF
Year 2026
Project Area Aircraft Design Projects
Project Type Review-Based AI Design
Required Tools / Software Python, Scikit-learn, PyTorch/TensorFlow, OpenVSP optional, CAD data, Streamlit
Main Features / Working Principle Use the review to create a project-selection and AI-method mapping dashboard for aircraft design
Expected Output A dashboard that maps design objectives to ML methods and outputs
Possible Add-ons Add RAG assistant for aircraft design paper search
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This B.Tech aerospace project resource helps students connect a recent AI-based research direction with a practical implementation plan, tools, expected output, and possible extensions.

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