Use of Adaptive Kriging Metamodeling in Reliability Analysis of Radiated Susceptibility in Coaxial Shielded Cables

Bdour, Tarek; Guiffaut, Christophe; Reineix, Alain

doi:10.1109/temc.2015.2501899

Cited by 21 publications

(7 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An intuitive metamodeling method, called individual Kriging (IK) [1], [4], can be considered. It simply fits separate s classic GP models, with only quantitative variables, for each response surface indexed by one-level combination of the qualitative variables.…”

Section: Gp Metamodels With Quantitative and Qualitative Variablesmentioning

confidence: 99%

“…The latter, approximates the input/output function of the simulation model with a small number of runs in order to predict the code output at unobserved inputs. When the input factors are uncertain, the metamodel allows the performance of optimization, reliability [1], uncertainty and sensitivity analysis [2] in a faster and more computationally efficient manner than the original model.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Emulation of an Expensive FDTD Code With Mixed Quantitative and Qualitative Factors for Analysis of Lightning-Induced Transient Responses

Bdour

Diaz

Guiffaut

et al. 2016

IEEE Trans. Electromagn. Compat.

Self Cite

View full text Add to dashboard Cite

In this paper, we discuss how to replace a timedemanding computer code having both quantitative and qualitative variables with a surrogate model based on Kriging technique. The recourse to a predictive model is motivated by a challenging electromagnetic compatibility problem of maximum lightning-induced current in electronic equipment connected to a large industrial site. The technical aspects of the incorporation of qualitative variables via specific correlation functions are detailed. The accuracy of the built surrogate model is statistically validated. The application of the resulting metamodel to the uncertainty analysis of induced currents will be also investigated.

show abstract

Section: Gp Metamodels With Quantitative and Qualitative Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Emulation of an Expensive FDTD Code With Mixed Quantitative and Qualitative Factors for Analysis of Lightning-Induced Transient Responses

Bdour

Diaz

Guiffaut

et al. 2016

IEEE Trans. Electromagn. Compat.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Different stochastic techniques have been successfully applied in order to provide a more realistic view of EM simulations including uncertainties. Among them, the unscented transform [4] or the ''Lagrange'' stochastic collocation [5], [6] methods, the kriging technique [7]- [11], the polynomial chaos expansion [12]- [16] were proposed. The previous quoted techniques were mainly applied to numerical simulations including various applications: shielding effectiveness [17], scattering and propagation [18] and/or EMC/EMI problems.…”

Section: Introductionmentioning

confidence: 99%

Controlled Stratification Based on Kriging Surrogate Model: An Algorithm for Determining Extreme Quantiles in Electromagnetic Compatibility Risk Analysis

et al. 2020

View full text Add to dashboard Cite

show abstract

“…In [12] a sparse PCE in a high dimension problem is compared to MC to estimate the output distribution. In [13] an adaptive kriging is compared to classical reliability methods (FORM, Importance Sampling, Subset Simulation) to estimate the output distribution tail.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Surrogate Models for Extreme Quantile Estimation in the Context of EMC Risk Analysis

Houret

Besnier

Vauchamp

et al. 2019

2019 Joint International Symposium on Electromagnetic Compatibility, Sapporo and Asia-Pacific International Symposium on Electr

View full text Add to dashboard Cite

Various EMC problems may be studied from numerical simulations involving 3D Maxwell equation solvers. However, the EMC risk analysis, either from a susceptibility or emissivity point of view requires various configurations of coupling paths described by important sets of unknown or uncertain parameters. The use of surrogate models is very relevant to speed up the risk analysis process. More specifically, values at risk corresponding to extreme values of relevant fields, currents or voltages are often the most important information with regard to a possible EMC risk. Specific methods such as controlled stratification provide a way to sample the input space of random variables in an efficient way to estimate extreme quantiles of a distribution. However, it requires a simple (i.e. fast calculation time) companion model. This companion model has to be correlated to the reference model in a specific sense. Building a surrogate model would be a possible way. This paper discusses various surrogate models and provides some conclusions about their ability to provide either a direct estimation of extreme quantiles of the response of interest, or a companion model for the controlled stratification method.

show abstract

Use of Adaptive Kriging Metamodeling in Reliability Analysis of Radiated Susceptibility in Coaxial Shielded Cables

Cited by 21 publications

References 34 publications

Emulation of an Expensive FDTD Code With Mixed Quantitative and Qualitative Factors for Analysis of Lightning-Induced Transient Responses

Emulation of an Expensive FDTD Code With Mixed Quantitative and Qualitative Factors for Analysis of Lightning-Induced Transient Responses

Controlled Stratification Based on Kriging Surrogate Model: An Algorithm for Determining Extreme Quantiles in Electromagnetic Compatibility Risk Analysis

Comparison of Surrogate Models for Extreme Quantile Estimation in the Context of EMC Risk Analysis

Contact Info

Product

Resources

About