Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
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
AXIAL TURBINE BLADE AERODYNAMIC OPTIMIZATION USING A NOVEL MULTI-LEVEL GENETIC ALGORITHM
Date
2008-06-13
Author
Oeksuez, Oezhan
Akmandor, Ibrahim Sinan
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
48
views
0
downloads
Cite This
In this paper, a new multiploid genetic optimization method handling surrogate models of the CFD solutions is presented and applied for single objective turbine blade aerodynamic optimization problem. A fast, efficient, robust, and automated design method is developed to aerodynamically optimize 3D gas turbine blades. The design objectives are selected as maximizing the adiabatic efficiency and torque so as to reduce the weight, size and cost of the gas turbine engine. A 3-Dimensional steady Reynolds Averaged Navier Stokes solver is coupled with an automated unstructured grid generation tool. The solver is verified using two well known test cases. Blade geometry is modeled by 36 design variables plus the number of blades variable in a row. Fine and coarse grid solutions are respected as high and low fidelity models, respectively. One of the test cases is selected as the baseline and is modified by the design process. It was found that the multiploid genetic algorithm successfully accelerates the optimization at the initial generations for both optimization problems, while preventing converging to local optimums.
URI
https://hdl.handle.net/11511/65297
Conference Name
53rd ASME Turbo Expo 2008
Collections
Department of Aerospace Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
MULTI-OBJECTIVE AERODYNAMIC OPTIMIZATION OF AXIAL TURBINE BLADES USING A NOVEL MULTI-LEVEL GENETIC ALGORITHM
Oeksuz, Oezhan; Akmandor, Ibrahim Sinan (2008-06-13)
In this paper, a new multiploid genetic optimization method handling surrogate models of the CID solutions is presented and applied for multi objective turbine blade aerodynamic optimization problem. A fast, efficient, robust, and automated design method is developed to aerodynamically optimize 3D gas turbine blades. The design objectives are selected as maximizing the adiabatic efficiency and torque so as to reduce the weight, size and cost of the gas turbine engine. A 3-Dimensional steady Reynolds Average...
Aerothermodynamic shape optimization using DSMC and POD-RBF methods
Kutkan, Halit; Eyi, Sinan; Department of Aerospace Engineering (2018)
This thesis study presents a hybrid method based on Proper Orthogonal Decomposition (POD) with Radial Basis Function (RBF), on Direct Simulation Monte Carlo (DSMC) solutions for aerothermodynamic front surface optimization of Stardust re-entry. Gaussian and multiquadric RBFs are implemented for comparison, and multiquadric functions are chosen due to their insensitivity to diverse shape parameters. Cubic uniform B-spline curves are used innovatively for parameterization of the geometry change, instead of cu...
Turbine blade shape aerodynamic design using artificial intelligence
Oksuz, Ozhan; Akmandor, Ibrahim Sinan (2005-06-09)
This paper describes a fast, efficient, robust, and automated design method used to aerodynamically optimize 3D gas turbine blade shapes implementing artificial intelligence. The design objectives are maximizing the aerodynamic efficiency and torque so as to reduce the weight and size and cost of the gas turbine engine. The procedure described here will allow a rapid, practical and low cost design that will answer the need of gas turbine industry. A 3-Dimensional steady Reynolds Averaged Navier Stokes solve...
Thrust vector control by secondary injection
Erdem, Erinç; Albayrak, Kahraman; Department of Mechanical Engineering (2006)
A parametric study on Secondary Injection Thrust Vector Control (SITVC) has been accomplished numerically with the help of a commercial Computational Fluid Dynamics (CFD) code called FLUENT®. This study consists of two parts; the first part includes the simulation of three dimensional flowfield inside a test case nozzle for the selection of parameters associated with both computational grid and the CFD solver such as mesh size, turbulence model accompanied with two different wall treatment approaches, and s...
TRANSONIC AIRFOIL DESIGN BY CONSTRAINED OPTIMIZATION
LEE, KD; Eyi, Sinan (1993-11-01)
AN aerodynamic design method is developed which couples flow analysis and numerical optimization to find an airfoil shape with improved aerodynamic performance. The flow analysis code is based on the coupled Euler and boundary-layer equations in order to include the rotational, viscous physics of transonic flows. The numerical optimization process searches for the best feasible design for the specified design objective and design constraints. The method is demonstrated with several examples at transonic flo...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
O. Oeksuez and I. S. Akmandor, “AXIAL TURBINE BLADE AERODYNAMIC OPTIMIZATION USING A NOVEL MULTI-LEVEL GENETIC ALGORITHM,” Berlin, Germany, 2008, p. 2361, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/65297.
