Optimization Algorithms for Simultaneous Multidisciplinary Design on Supersonic Flutter and Structural Mass of Plate Wing

2002 ◽  
Vol 2002.15 (0) ◽  
pp. 49-50
Author(s):  
Hiroshi FURUYA ◽  
Isao FUKUCHI
Keyword(s):  
Optimization Algorithms ◽  
Multidisciplinary Design ◽  
Supersonic Flutter ◽  
Structural Mass

scholarly journals RAPID GEOMETRY DEFINITION FOR MULTIDISCIPLINARY DESIGN AND ANALYSIS OF AN AIRCRAFT

Aviation ◽  
2016 ◽  
Vol 20 (2) ◽  
pp. 60-64 ◽  
Author(s):  
Jacek MIELOSZYK ◽  
Tomasz GOETZENDORF-GRABOWSKI ◽  
Dawid MIESZALSKI
Keyword(s):  
Numerical Model ◽  
Computational Geometry ◽  
Optimization Algorithms ◽  
Aircraft Design ◽  
Multidisciplinary Design ◽  
Preliminary Design ◽  
Basic Step

Conceptual and preliminary design level of aircraft design is searching for an easy, flexible and efficient way of computational geometry definition. Accelerating the process of geometry definition is the basic step for acceleration of all computations. It also enables optimization, where changes of numerical model are made automatically according to the optimization algorithms. The geometry definition has to be robust, free from errors and stay feasible.

Optimum Design of Plate Wing with Magnesium Alloys on Supersonic Flutter Characteristics and Structural Mass

2003 ◽  
Vol 419-422 ◽  
pp. 207-212
Author(s):  
Hiroshi Furuya ◽  
Isao Fukuchi ◽  
Nozomu Kogiso ◽  
Saburo Matunaga
Keyword(s):  
Magnesium Alloys ◽  
Optimum Design ◽  
Supersonic Flutter ◽  
Structural Mass

Design and Optimization Method of a Two-Disk Rotor System

2016 ◽  
Vol 33 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Jingjing Huang ◽  
Longxi Zheng ◽  
Qing Mei
Keyword(s):  
Design Optimization ◽  
Dynamic Characteristics ◽  
Multidisciplinary Design Optimization ◽  
Optimization Algorithms ◽  
Rotor System ◽  
Multidisciplinary Optimization ◽  
Multidisciplinary Design ◽  
Design Efficiency ◽  
Optimization Software ◽  
Finite Element Software

AbstractAn integrated analytical method based on multidisciplinary optimization software Isight and general finite element software ANSYS was proposed in this paper. Firstly, a two-disk rotor system was established and the mode, humorous response and transient response at acceleration condition were analyzed with ANSYS. The dynamic characteristics of the two-disk rotor system were achieved. On this basis, the two-disk rotor model was integrated to the multidisciplinary design optimization software Isight. According to the design of experiment (DOE) and the dynamic characteristics, the optimization variables, optimization objectives and constraints were confirmed. After that, the multi-objective design optimization of the transient process was carried out with three different global optimization algorithms including Evolutionary Optimization Algorithm, Multi-Island Genetic Algorithm and Pointer Automatic Optimizer. The optimum position of the two-disk rotor system was obtained at the specified constraints. Meanwhile, the accuracy and calculation numbers of different optimization algorithms were compared. The optimization results indicated that the rotor vibration reached the minimum value and the design efficiency and quality were improved by the multidisciplinary design optimization in the case of meeting the design requirements, which provided the reference to improve the design efficiency and reliability of the aero-engine rotor.

Optimization Algorithms and ODE’s in MDO

2013 ◽  
Author(s):  
C. Bakker ◽  
G. T. Parks ◽  
J. P. Jarrett
Keyword(s):  
Differential Geometry ◽  
Differential Equations ◽  
Ordinary Differential Equations ◽  
Multidisciplinary Design Optimization ◽  
Optimization Algorithms ◽  
Optimization Methods ◽  
Multidisciplinary Design ◽  
Theoretical Understanding ◽  
Solution Methods ◽  
Systems Of Odes

There is a need for a stronger theoretical understanding of Multidisciplinary Design Optimization (MDO) within the field. Having developed a differential geometry framework in response to this need, we consider how standard optimization algorithms can be modeled using systems of ordinary differential equations (ODEs) while also reviewing optimization algorithms which have been derived from ODE solution methods. We then use some of the framework’s tools to show how our resultant systems of ODEs can be analyzed and their behaviour quantitatively evaluated. In doing so, we demonstrate the power and scope of our differential geometry framework, we provide new tools for analyzing MDO systems and their behaviour, and we suggest hitherto neglected optimization methods which may prove particularly useful within the MDO context.

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