Comparison of global and local response surface techniques in reliability-based optimization of composite structures

2004 ◽  
Vol 26 (5) ◽  
pp. 333-345 ◽  
Author(s):  
M. Rais-Rohani ◽  
M.N. Singh
2017 ◽  
Vol 45 (11) ◽  
pp. 2663-2672 ◽  
Author(s):  
Benjamin K. Shurtz ◽  
Amanda M. Agnew ◽  
Yun-Seok Kang ◽  
John H. Bolte

Polymers ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1843
Author(s):  
Bo Deng ◽  
Yaoyao Shi ◽  
Tao Yu ◽  
Pan Zhao

Composite prepreg tape winding technology has proven to be an effective method for manufacturing revolving body composite structures in aerospace field. Process parameters including heating temperature, tape tension and roller pressure have an important impact on the winding products’ mechanical property such as tensile strength. The aim of this study is to investigate the influence mechanism and optimization analysis of parameters for the composite prepreg tape winding process. Firstly, the sensitivity analysis for single parameter had be employed to reveal the influence mechanism of each winding parameter change on tensile strength. Secondly, iso-surfaces analysis for parameter range had be applied to describe the distribution law of parameter with continuous distribution characteristics. Then the coupling analysis for process parameters was carried out employing response surface methodology. The analysis results showed that tape tension has the most significant effect on the winding products’ tensile strength. And the outstanding parameter combination with the heating temperature of 72 °C, tape tension of 307 N and roller pressure of 1263 N was provided by response surface design software via desirability function method. The validation experiments showed that the optimal parameter combination has a positive guiding significance for improving the quality of winding products.


1997 ◽  
Vol 119 (4) ◽  
pp. 427-433 ◽  
Author(s):  
J. C. Korngold ◽  
G. A. Gabriele

The objective of this paper is to present a new algorithm to efficiently optimize multidisciplinary, coupled nonhierarchic systems with discrete variables. The algorithm decomposes the system into contributing disciplines, and uses designed experiments within the disciplines to build local response surface approximations to the discipline analysis. First and second order Global Sensitivity Equations are formulated and approximated by experimental data to build approximations to the global design space. The global approximation is optimized using branch and bound or simulated annealing. Convergence is rapid for systems with near quadratic behavior. The algorithm is demonstrated on a unique multidisciplinary learning tool, the Design and Manufacturing Learning Environment. This environment provides multimedia simulation for product life cycle disciplines, including design, manufacturing, marketing, and sales.


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