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Improved Lightweight Design of Variable Stiffness Composite Aircraft Panels Enabled by Tow-Steering and Machine Learning

Implementing Organization

Indian Institute of Technology (Indian School of Mines) Dhanbad
Principal Investigator
Dr. Tanish Dey
Indian Institute of Technology (Indian School of Mines) Dhanbad
CO-Principal Investigator
Dr. Ayan Haldar
Indian Institute Of Technology (Bhu)

Project Overview

Zero-emission aircraft is a pressing need, driving the development of lightweight high-performance structures and materials. Current constraints on large structural components, such as the upper skin of wing structures, limit their potential for exploitation. Novel manufacturing processes enable variable-stiffness (VS) composites with higher tailoring potential, but the vast design space presents a real optimization challenge. This research aims to develop methods for post-buckling, calculate failure modes, and estimate their impact on stiffened composite panels. Bayesian-based Machine Learning (ML) schemes will be used to map the complex design space and find suitable optimum designs. The proposed framework will solve inverse problems and use a novel finite element Bogner-Fox-Schmit-Castro for efficient modeling of VS panels. The instability problem will be solved using a displacement-based multi-modal formulation of the asymptotic theory. The new failure modes activated by post-buckling will produce additional fatigue damage, modelled according to Socci and Kassapoglou's computationally efficient approach based on crack density. A detailed experimental investigation will validate the developed design framework. 3D printing technology will be used for manufacturing VS composite stiffened panels.
Funding Organization
Funding Organization
Science and Engineering Research Board (SERB), New Delhi
Anusandhan National Research Foundation (ANRF)
Quick Information
Area of Research
Engineering Sciences
Focus Area
Aerospace Engineering, Composite Materials
Start Year
2024
End Year
2027
Sanction Amount
₹ 47.63 L
Status
Ongoing
Output
No. of Research Paper
00
Technologies (If Any)
00
No. of PhD Produced
N/A
Startup (If Any)
00
No. of Patents
Filed :00
Grant :00
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