Robust Multiscale Design Using PATC and WSRSM

Fen Fen Xiong; Gao Rong Sun; Liang Yu Zhao

doi:10.4028/www.scientific.net/AMR.148-149.1075

Paper Titles

Study on Probabilistic Optimal Design of Diaphragm Spring
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Preparation and Characterization of (Ba_0.88Ca_0.12)(Zr_0.12Ti_0.88)O₃ Powders and Ceramics Produced by Sol-Gel Process
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Sol-Gel Synthesis and Characterization of BaAl₂O₄ and Co: BaAl₂O₄ Nanoparticles
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Study on Wall Thickness Eccentricity of Seamless Steel Tube
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Robust Multiscale Design Using PATC and WSRSM
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Nanometer Anatase Titania Synthesis by Reverse Titration Method and Evaluation of their Photocatalytic Activity
p.1079

Improved Photoelectrochemical Properties of Cu-Loaded TiO₂ Nanotubes
p.1083

Fluorescent Properties of Zn-Al Hydrotalcite and its Modified Products
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Structure and Dielectric Tunability of Ba (Ti_1-yZr_y)O₃ Ferroelectric Ceramics
p.1091

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 148-149Robust Multiscale Design Using PATC and WSRSM

Robust Multiscale Design Using PATC and WSRSM

Abstract:

Multiscale design dealing with 2-scale material and product system is implemented by employing probabilistic analytical target cascading (PATC) and weighted stochastic response surface method (WSRSM) in this paper. PATC allows design autonomy at each scale subsystem by formulating the multiscale design system as a multilevel structure. WSRSM ensures uncertainties to be propagated within and across each scale accurately and efficiently. Comparative study on a multiscale bracket design problem shows that the results obtained by our strategy are very close to the reference values. It is demonstrated that PATC and WSRSM are highly effective and applicable on multiscale design.

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Periodical:

Advanced Materials Research (Volumes 148-149)

Pages:

1075-1078

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.148-149.1075

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Online since:

October 2010

Authors:

Fen Fen Xiong, Gao Rong Sun, Liang Yu Zhao

Keywords:

Material Design, Multiscale Design, Probabilistic Analytical Target Cascading, Product Design, Weighted Stochastic Response Surface Method

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