Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Three-dimensional structural topology optimization of aerial vehicles under aerodynamic loads
Date
2014-03-20
Author
Oktay, Erdal
AKAY, HASAN UMUR
Şehitoğlu, Onur Tolga
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
213
views
0
downloads
Cite This
A previously developed density distribution-based structural topology optimization algorithm coupled with a Computational Fluid Dynamics (CFD) solver for aerodynamic force predictions is extended to solve large-scale problems to reveal inner structural details of a wing wholly rather than some specific regions. Resorting to an iterative conjugate gradient algorithm for the solution of the structural equilibrium equations needed at each step of the topology optimizations allowed the solution of larger size problems, which could not be handled previously with a direct equation solver. Both the topology optimization and CFD codes are parallelized to obtain faster solutions. Because of the complexity of the computed aerodynamic loads, a case study involving optimization of the inner structure of the wing of an unmanned aerial vehicle (UAV) led to topologies, which could not be obtained by intuition alone. Post-processing features specifically tailored for visualizing computed topologies proved to be good design tools in the hands of designers for identifying complex structural components.
Subject Keywords
Structural topology optimization
,
Aerial vehicle structural design
,
Parallel CFD
,
Mesh coupling
,
Code coupling
,
Parallelized solvers
URI
https://hdl.handle.net/11511/47266
Journal
COMPUTERS & FLUIDS
DOI
https://doi.org/10.1016/j.compfluid.2013.11.018
Collections
Department of Computer Engineering, Article
Suggestions
OpenMETU
Core
Structural Coupling of Two Nonlinear Structures
Tepe, Çağrı; Ciğeroğlu, Ender (null; 2015-02-02)
In mechanical design, modeling and analysis of a complex structure can be simplified with dividing the structure into substructures; therefore, any change in the structure can be addressed easily which is referred as “structural coupling”. Utilization of proper coupling techniques, it is possible to understand the behavior of the whole structure by considering the behavior of its substructures. For linear structures, coupling is a common technique; however, in most of the engineering structures, nonlinearit...
Evolutionary topology optimization of a folding missile wing for stiffness and frequency
Ürün, Ata; Şahin, Melin; Gürses, Ercan; Department of Aerospace Engineering (2023-1-25)
This thesis presents a study on the topology optimization of a folding wing structure for a cruise missile with the aim of minimizing the weight of the wing while maximizing its stiffness and/or maximizing the selected natural frequency values. The weight of the folding wing has a significant impact on the performance of the opening mechanism and the overall dynamic behavior of the missile. The Bidirectional Evolutionary Structural Optimization (BESO) method, a widely-used topology optimization technique, i...
Layout optimization of trusses using simulated annealing
Hasançebi, Oğuzhan (2000-09-08)
This paper addresses to the development of a simulated annealing (SA) based solution algorithm which is automated to achieve the simultaneous optimum design of truss type structures with respect to size, shape and topology design variables. The proposed algorithm is designed in such a way that together with applicability to practical design problems, it is also aimed at producing efficient and improved design solutions for the problems of interest. From the practicality point of view, the task is chosen as ...
Predicting the shear strength of reinforced concrete beams using artificial neural networks
Mansour, MY; Dicleli, Murat; Lee, JY; Zhang, J (Elsevier BV, 2004-05-01)
The application of artificial neural networks (ANNs) to predict the ultimate shear strengths of reinforced concrete (RC) beams with transverse reinforcements is investigated in this paper. An ANN model is built, trained and tested using the available test data of 176 RC beams collected from the technical literature. The data used in the ANN model are arranged in a format of nine input parameters that cover the cylinder concrete compressive strength, yield strength of the longitudinal and transverse reinforc...
Optimal load and resistance factor design of geometrically nonlinear steel space frames via tabu search and genetic algorithm
DEĞERTEKİN, SADIK ÖZGÜR; Saka, M. P.; HAYALİOĞLU, MEHMET SEDAT (Elsevier BV, 2008-01-01)
In this paper, algorithms are presented for the optimum design of geometrically nonlinear steel space frames using tabu search and genetic algorithm. Tabu search utilizes the features of short-term memory facility (tabu list) and aspiration criteria. Genetic algorithm employs reproduction, crossover and mutation operators. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
E. Oktay, H. U. AKAY, and O. T. Şehitoğlu, “Three-dimensional structural topology optimization of aerial vehicles under aerodynamic loads,”
COMPUTERS & FLUIDS
, pp. 225–232, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47266.