scholarly journals Incremental Space-Filling Design Based on Coverings and Spacings: Improving Upon Low Discrepancy Sequences

2021 ◽  
Vol 15 (4) ◽  
Author(s):  
A. Nogales Gómez ◽  
L. Pronzato ◽  
M.-J. Rendas
Keyword(s):  
Space Filling ◽  
Low Discrepancy Sequences ◽  
Space Filling Design

Improving Cylindrical Pin Cage Bearing Performance in Mill Applications Using Dynamic Modeling and Space Filling Design

2007 ◽  
Author(s):  
Bradley M. Pederson ◽  
Jerry Rhodes
Keyword(s):  
Transfer Function ◽  
Dynamic Modeling ◽  
Space Filling ◽  
Input And Output ◽  
Performance Response ◽  
Response Optimization ◽  
Space Filling Design

A dynamic cylindrical bearing model was modified to analyze large bore cylindrical mill bearings with pin cages. A factor-response methodology was coupled to the dynamic modeling input and output variables in order to generate a suitable transfer function for predicting bearing performance. Response optimization of the transfer function indicated that a traction-based parameter was determined to have the greatest effect on reducing roller slip and improving bearing performance.

Optimization of Composite Housing in a Multi-Special Camera Using Kriging Algorithm

2007 ◽  
Vol 334-335 ◽  
pp. 341-344
Author(s):  
Jung Sun Park ◽  
Jong Bin Im ◽  
Youg Hee Ro
Keyword(s):  
Optimization Problems ◽  
Earth Observation ◽  
Optimized Design ◽  
Space Filling ◽  
Design Constraints ◽  
Localization Method ◽  
Physical Problems ◽  
Classical Design ◽  
Effective Use ◽  
Space Filling Design

This paper is concerned with the optimization of composite housing in a multi-spectral camera using Kriging algorithm. The effective use of Kriging on physical problems has been expanded to provide global approximations for optimization problems. There are two major strategies to improve efficiency and accuracy of approximate optimization using Kriging. These methods are performed by the stochastic process, stochastic-localization method (SLM), as the criterion to move the local domains and the design of experiment (DOE), the classical design and space-filling design. The proposed methodology is applied to the design of a Multi-Spectral Camera (MSC), as a practical example, which will provide high resolution panchromatic and multi-spectral images and is carried by a satellite designed to fulfill the need for further Earth observation and allowing scientists and communication experts to conduct potentially valuable experiments. When this composite structure is optimized, design constraints are taken for natural frequency and shear stress which should be considered in a launching environment.

Optional Correlation Function Method in Kriging for Stochastic Optimal Design

2008 ◽  
Vol 580-582 ◽  
pp. 609-612
Author(s):  
Jong Bin Im ◽  
Young Hee Ro ◽  
Soo Yong Lee ◽  
Jung Sun Park
Keyword(s):  
Stochastic Process ◽  
Correlation Function ◽  
Function Method ◽  
Optimization Models ◽  
Space Filling ◽  
Adaptation Algorithm ◽  
Localization Method ◽  
Classical Design ◽  
Space Filling Design ◽  
Sequential Adaptation

This paper is focused on the three strategies to improve efficiency and accuracy of approximate optimization models using Kriging. The strategies are performed by the stochastic process which is called stochastic-localization method as the criterion to move the local domains and the design of experiments, the classical design and space-filling design. We also propose the methodology conducted by the max-min reused sampling and a sequential adaptation algorithm of correlation functions. The proposed strategies are applied to the known analytical function such as Sandgren’s pressure vessel and three-bar truss for practical examples.

Optimal Water Jacket Flow Distribution Using a New Group-Based Space-Filling Design of Experiments Algorithm

2018 ◽  
Author(s):  
Dionysios Panagiotopoulos ◽  
Owais Iqbal ◽  
Zissimos Mourelatos ◽  
Dimitrios Papadimitriou
Keyword(s):  
Design Of Experiments ◽  
Flow Distribution ◽  
Space Filling ◽  
Water Jacket ◽  
Space Filling Design

Selection of a Greener Set of Solvents Evenly Spread in the Hansen Space by Space-Filling Design

2013 ◽  
Vol 52 (47) ◽  
pp. 16585-16597 ◽  
Author(s):  
Adrien Benazzouz ◽  
Laurianne Moity ◽  
Christel Pierlot ◽  
Michelle Sergent ◽  
Valérie Molinier ◽  
...  
Keyword(s):  
Space Filling ◽  
Space Filling Design ◽  
Selection Of

scholarly journals Robustness of Maximin Space-filling Designs

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Cassandra Lisitza
Keyword(s):  
Spatial Data ◽  
Model Misspecification ◽  
Data Sets ◽  
Prediction Errors ◽  
Space Filling ◽  
Squared Prediction Error ◽  
The Mean ◽  
Spatial Data Sets ◽  
Space Filling Design ◽  
Future Work

In this report, we first have a review of the maximin space-filling design methods that is often applied and discussed in the literature (for example, Müller (2007)). Then we will discuss the robustness of the maximin space-filling design against model misspecification via numerical simulation. For this purpose, we will generate spatial data sets on a n x n grid and design points are selected from the n2 locations. The predictions at the unsampled locations are made based on the observations at these design points. Then the mean of the squared prediction errors are estimated as a measure of the robustness of the designs against possible model misspecification. Surprisingly, according to the simulation results, we find that the maximin space-filling designs may be robust against possible model misspecification in the sense that the mean of the squared prediction error does not increase significantly when the model is misspecified. Although the results were obtained based on simple models, this result is very inspiring. It will guide further numerical and theoretical studies which will be done as future work.

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