Conceptual Morphing Aircraft Sizing Using a Multi-Level Optimization Strategy

2008 ◽  
Author(s):  
Michael Skillen ◽  
William Crossley
Keyword(s):  
Optimization Strategy ◽  
Morphing Aircraft ◽  
Multi Level ◽  
Aircraft Sizing

Surrogate Modeling and Parametric Optimization Strategy for Minimizing Sonic Boom in a Morphing Aircraft

2022 ◽  
Author(s):  
Jonathan Weaver-Rosen ◽  
Ying-Kuan Tsai ◽  
Justin Schoppe ◽  
Yutaka Terada ◽  
Richard Malak ◽  
...  
Keyword(s):  
Parametric Optimization ◽  
Surrogate Modeling ◽  
Sonic Boom ◽  
Optimization Strategy ◽  
Morphing Aircraft

Morphing Aircraft Sizing Using Design Optimization

2011 ◽  
Vol 48 (2) ◽  
pp. 612-622 ◽  
Author(s):  
William A. Crossley ◽  
Michael D. Skillen ◽  
Joshua B. Frommer ◽  
Brian D. Roth
Keyword(s):  
Design Optimization ◽  
Morphing Aircraft ◽  
Aircraft Sizing

scholarly journals A Multi-level Optimization Strategy to Improve the Performance of Stencil Computation

2017 ◽  
Vol 108 ◽  
pp. 1083-1092 ◽  
Author(s):  
Gauthier Sornet ◽  
Fabrice Dupros ◽  
Sylvain Jubertie
Keyword(s):  
Optimization Strategy ◽  
Stencil Computation ◽  
Multi Level

Metamodel Based Design Automation: Applied on Multidisciplinary Design Optimization of Industrial Robots

2012 ◽  
Author(s):  
Mehdi Tarkian ◽  
Bhanoday Vemula ◽  
Xiaolong Feng ◽  
Johan Ölvander
Keyword(s):  
Design Optimization ◽  
Design Automation ◽  
Multidisciplinary Design Optimization ◽  
Industrial Robots ◽  
Multidisciplinary Design ◽  
Proof Of Concept ◽  
Optimization Strategy ◽  
Concept Generation ◽  
Multi Level ◽  
High Level

Intricate and complex dependencies between multiple disciplines require iterative intensive optimization processes. To this end, multidisciplinary design optimization (MDO) has been established as a convincing concurrent technique to manage inherited complexities. This paper presents a high level CAD and CAE design automation methodology which enables fast, efficient concept generation for MDO. To increase the evaluation speed, global metamodels are introduced to replace computationally expensive CAD and CAE models. In addition, various techniques are applied to drastically decrease the number of samplings required to create the metamodels. In the final part of the paper, a multi-level optimization strategy is proposed to find the optimal concept. As proof of concept, a real world design problem, from ABB industrial robotics, is presented.

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