• Aucun résultat trouvé

Uncertainty estimation of mechanical testingproperties using sensitivity analysis andstochastic modelling

N/A
N/A
Protected

Academic year: 2021

Partager "Uncertainty estimation of mechanical testingproperties using sensitivity analysis andstochastic modelling"

Copied!
1
0
0

Texte intégral

(1)

Measurement

Volume 62, 2015, Pages 149-154

Uncertainty estimation of mechanical testing properties using sensitivity analysis and

stochastic modelling

Bouhouche Salah, Ziani Slimane, Mentouri Zoheir, Bast Jurgen

Abstract: This paper is concerned with a method for uncertainty evaluation of mechanical propertiesin metal testing. This method uses a combined approach based on Monte Carlo simulationand Markov Chain (MCMC) as a computing procedure of different uncertainties of mechanicaland metallurgical parameters such as stress, and elongation. The MCMC is a stochasticmethod that computes the statistical properties of the considered states such as the probabilitydistribution function (PDF) according to the initial state and the target distributionusing Metropolis-Hasting (MH) algorithm. Conventional approach is based on the Guide ofUncertainty Measurement (GUM), the uncertainty budget is established for the stress andelongation parameters respectively. A comparative study between the conventional procedureand the proposed method is given. This kind of approaches is applied for constructingan accurate computing procedure of uncertainty measurement of mechanical and metallurgicalparameters.

Keywords : Markov Chain Monte Carlo (MCMC) Metropolis-Hasting (MH) algorithm Mechanical and metallurgical testing Stress, elongation and hardness measurement Guide of Uncertainty Measurement (GUM)

Centre de Recherche en Technologies Industrielles - CRTI - www.crti.dz

Powered by TCPDF (www.tcpdf.org)

Références

Documents relatifs

– MCMC yields Up component velocity uncertainties which are around [1.7,4.6] times larger than from CATS, and within the millimetre per year range

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des

Two approaches of literature are here considered for performing the sensitivity analysis of the passive system performance by SS: the first one is local and

Key words: Curve Resolution, Factor analysis, Bayesian estimation, non-negativity, statistical independence, sparsity, Gamma distribution, Markov Chain Monte Carlo (MCMC)..

The proposed model is applied to the region of Luxembourg city and the results show the potential of the methodologies for dividing an observed demand, based on the activity

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des

It is proposed in this work a new combined approach using the Kalman Filter and Markov Chain Monte Carlo (MCMC) for uncertainty estimation of steel content

This method uses a combined approach based on Monte Carlo Simulation and Markov Chain (MCMC) as a computing procedure of different uncertainties of mechanical and