Space mapping with co-simulation coarse model for accurate modeling of microwave structures

2010 ◽  
Author(s):  
S Koziel
Keyword(s):  
Space Mapping ◽  
Microwave Structures ◽  
Coarse Model

Comparison of three space mapping techniques on electromagnetic design optimization

2018 ◽  
Vol 37 (2) ◽  
pp. 565-580
Author(s):  
Jinlin Gong ◽  
Frédéric Gillon ◽  
Nicolas Bracikowski
Keyword(s):  
Induction Motor ◽  
Kriging Model ◽  
Poor Quality ◽  
Space Mapping ◽  
Content Type ◽  
Linear Induction ◽  
Linear Induction Motor ◽  
Coarse Model ◽  
Original Approach

PurposeThis paper aims to investigate three low-evaluation-budget optimization techniques: output space mapping (OSM), manifold mapping (MM) and Kriging-OSM. Kriging-OSM is an original approach having high-order mapping. Design/methodology/approachThe electromagnetic device to be optimally sized is a five-phase linear induction motor, represented through two levels of modeling: coarse (Kriging model) and fine.The optimization comparison of the three techniques on the five-phase linear induction motor is discussed. FindingsThe optimization results show that the OSM takes more time and iteration to converge the optimal solution compared to MM and Kriging-OSM. This is mainly because of the poor quality of the initial Kriging model. In the case of a high-quality coarse model, the OSM technique would show its domination over the other two techniques. In the case of poor quality of coarse model, MM and Kriging-OSM techniques are more efficient to converge to the accurate optimum. Originality/valueKriging-OSM is an original approach having high-order mapping. An advantage of this new technique consists in its capability of providing a sufficiently accurate model for each objective and constraint function and makes the coarse model converge toward the fine model more effectively.

Radial output space mapping for electromechanical systems design

2014 ◽  
Vol 33 (3) ◽  
pp. 965-975 ◽  
Author(s):  
Maya Hage Hassan ◽  
Ghislain Remy ◽  
Guillaume Krebs ◽  
Claude Marchand
Keyword(s):  
Traditional Approach ◽  
Systems Design ◽  
Residue Function ◽  
Space Mapping ◽  
Physical Models ◽  
Electrical Machine ◽  
Content Type ◽  
Coarse Model ◽  
Optimum Solution ◽  
Output Space

Purpose – The purpose of this paper is to set a relation through adaptive multi-level optimization between two physical models with different accuracies; a fast coarse model and a fine time consuming model. The use case is the optimization of a permanent magnet axial flux electrical machine. Design/methodology/approach – The paper opted to set the relation between the two models through radial basis function (RBF). The optimization is held on the coarse model. The deduced solutions are used to evaluate the fine model. Thus, through an iterative process a residue RBF between models responses is built to endorse an adaptive correction. Findings – The paper shows how the use of a residue function permits, to diminish optimization time, to reduce the misalignment between the two models in a structured strategy and to find optimum solution of the fine model based on the optimization of the coarse one. The paper also provides comparison between the proposed methodology and the traditional approach (output space mapping (OSM)) and shows that in case of large misalignment between models the OSM fails. Originality/value – This paper proposes an original methodology in electromechanical design based on building a surrogate model by means of RBF on the bulk of existing physical model.

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