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Design Analysis and Optimization of a Tail for a Civil UAV
by
Rodrigues, Diogo Pinheiro
in
Aeronautics
/ Aerospace engineering
/ Aircraft
/ Artificial intelligence
/ Aviation
/ CAD
/ CAE
/ Carbon fiber reinforcement
/ Certification
/ Composite materials
/ Computer aided design
/ Computer aided engineering
/ Design
/ Genetic algorithms
/ Load
/ Materials science
/ Mechanical engineering
/ Robotics
/ Surveillance
/ Unmanned aerial vehicles
2024
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Design Analysis and Optimization of a Tail for a Civil UAV
by
Rodrigues, Diogo Pinheiro
in
Aeronautics
/ Aerospace engineering
/ Aircraft
/ Artificial intelligence
/ Aviation
/ CAD
/ CAE
/ Carbon fiber reinforcement
/ Certification
/ Composite materials
/ Computer aided design
/ Computer aided engineering
/ Design
/ Genetic algorithms
/ Load
/ Materials science
/ Mechanical engineering
/ Robotics
/ Surveillance
/ Unmanned aerial vehicles
2024
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Do you wish to request the book?
Design Analysis and Optimization of a Tail for a Civil UAV
by
Rodrigues, Diogo Pinheiro
in
Aeronautics
/ Aerospace engineering
/ Aircraft
/ Artificial intelligence
/ Aviation
/ CAD
/ CAE
/ Carbon fiber reinforcement
/ Certification
/ Composite materials
/ Computer aided design
/ Computer aided engineering
/ Design
/ Genetic algorithms
/ Load
/ Materials science
/ Mechanical engineering
/ Robotics
/ Surveillance
/ Unmanned aerial vehicles
2024
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Design Analysis and Optimization of a Tail for a Civil UAV
Dissertation
Design Analysis and Optimization of a Tail for a Civil UAV
2024
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Overview
This thesis, developed in collaboration with Tekever, a leading Portuguese company in unmanned aerial systems (UAS), focuses on the structural design and optimization of the tail and boom components of the ARX, Tekever’s future UAV, with a focus on versatile missions, including ISAR operations and cargo transportation, with an expected launch in 2025. The main objective of this research is to design a lightweight and structurally robust tail and boom system, in compliance with ASTM F3116-18 standards, while simultaneously optimizing operational efficiency and performance using heuristic optimization tools. Additionally, the project aims to validate and improve in terms of computational efficiency a heuristic algorithm optimization tool initiated in the 2022/2023 academic year to predict the minimum number of layers and the optimal fiber orientations for the composite material used in the critical points of the Tail boom structure developed for the ARX seeking better performance and structural optimization. The tool is based on a unique evolutionary algorithm to explore the search space, with limits based on Hashin matrix and fiber failure indices. To accommodate these limitations, a surrogate model was developed, combining the Abaqus finite element program and Python, building the training data for the surrogate model using the Latin hypercube sampling technique and a Gaussian regression model. As a final phase, it was possible to obtain an approximate 73% computational efficiency over the initial tool, through the fine-tuning of the genetic algorithm and Gaussian regression, greater flexibility in applying the tool to complex cases after direct implementation of .Cae files and an improved condition of the failure criterion and studying the application of LAr05 and Hashin criteria, culminating in an ARX tail boom structure 14% lighter than the initial reference. Overall, this research not only advances the structural design of Tekever’s ARX but also contributes to the broader field of UAV development by demonstrating effective methodologies for lightweight, high-performance aerostructure optimization.
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