Reducing the Number of CFD Computer Experiments by Use of Latin Hypercube Design and Kriging Regression on the Example of Side Flushing in Sinking EDM

2021 ◽  
pp. 151-159
Author(s):  
N. C. Dinh ◽  
R. Hörl ◽  
S. Yabroudi ◽  
M. Polte ◽  
E. Uhlmann
Keyword(s):  
Computer Experiments ◽  
Latin Hypercube Design ◽  
Latin Hypercube

scholarly journals Generalized Latin Hypercube Design for Computer Experiments

Technometrics ◽  
2010 ◽  
Vol 52 (4) ◽  
pp. 421-429 ◽  
Author(s):  
Holger Dette ◽  
Andrey Pepelyshev
Keyword(s):  
Computer Experiments ◽  
Latin Hypercube Design ◽  
Latin Hypercube

Optimizing Latin hypercube design for sequential sampling of computer experiments

2009 ◽  
Vol 41 (8) ◽  
pp. 793-810 ◽  
Author(s):  
F. Xiong ◽  
Y. Xiong ◽  
W. Chen ◽  
S. Yang
Keyword(s):  
Sequential Sampling ◽  
Computer Experiments ◽  
Latin Hypercube Design ◽  
Latin Hypercube

scholarly journals Adaptive Response Surface Method Using Inherited Latin Hypercube Design Points

2003 ◽  
Vol 125 (2) ◽  
pp. 210-220 ◽  
Author(s):  
G. Gary Wang
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Adaptive Response ◽  
High Dimensional ◽  
Latin Hypercube Design ◽  
Latin Hypercube ◽  
Design Problems ◽  
Surface Method ◽  
Adaptive Response Surface Method ◽  
Design Experiments

This paper addresses the difficulty of the previously developed Adaptive Response Surface Method (ARSM) for high-dimensional design problems. ARSM was developed to search for the global design optimum for computation-intensive design problems. This method utilizes Central Composite Design (CCD), which results in an exponentially increasing number of required design experiments. In addition, ARSM generates a complete new set of CCD points in a gradually reduced design space. These two factors greatly undermine the efficiency of ARSM. In this work, Latin Hypercube Design (LHD) is utilized to generate saturated design experiments. Because of the use of LHD, historical design experiments can be inherited in later iterations. As a result, ARSM only requires a limited number of design experiments even for high-dimensional design problems. The improved ARSM is tested using a group of standard test problems and then applied to an engineering design problem. In both testing and design application, significant improvement in the efficiency of ARSM is realized. The improved ARSM demonstrates strong potential to be a practical global optimization tool for computation-intensive design problems. Inheriting LHD points, as a general sampling strategy, can be integrated into other approximation-based design optimization methodologies.

scholarly journals Sliced Latin Hypercube Designs for Computer Experiments With Unequal Batch Sizes

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 60396-60402 ◽  
Author(s):  
Jin Xu ◽  
Xu He ◽  
Xiaojun Duan ◽  
Zhengming Wang
Keyword(s):  
Computer Experiments ◽  
Latin Hypercube ◽  
Latin Hypercube Designs ◽  
Batch Sizes
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