https://sam.ensam.eu:443 The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material. Sun, 07 Jun 2026 01:44:26 GMT 2026-06-07T01:44:26Z http://hdl.handle.net/10985/7116 Stochastic Non Destructive Testing simulation: sensitivity analysis applied to material properties in clogging of nuclear power plant steam generators MOREAU, Olivier; BEDDEK, Karim; LE MENACH, Yvonnick; CLENET, Stephane A Non destructive Testing (NDT) procedure is currently used to estimate the clogging of tube support plates in French nuclear power plant steam generators. A stochastic approach has been applied to Finite Element electromagnetic field simulation to evaluate the impact of material properties uncertainties on the monitoring signal. The Polynomial Chaos Expansion method makes it possible to easily derive the Sobol decomposition which measures how much the variability of each input parameter affects the model output La version éditeur de cette publication est disponible à l'adresse suivante : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6514684 Tue, 01 Jan 2013 00:00:00 GMT http://hdl.handle.net/10985/7116 2013-01-01T00:00:00Z MOREAU, Olivier BEDDEK, Karim LE MENACH, Yvonnick CLENET, Stephane A Non destructive Testing (NDT) procedure is currently used to estimate the clogging of tube support plates in French nuclear power plant steam generators. A stochastic approach has been applied to Finite Element electromagnetic field simulation to evaluate the impact of material properties uncertainties on the monitoring signal. The Polynomial Chaos Expansion method makes it possible to easily derive the Sobol decomposition which measures how much the variability of each input parameter affects the model output http://hdl.handle.net/10985/7317 Solution of Large Stochastic Finite Element Problems – Application to ECT-NDT BEDDEK, Karim; MOREAU, Olivier; LE MENACH, Yvonnick; CLENET, Stephane This paper describes an efficient bloc iterative solver for the Spectral Stochastic Finite Element Method (SSFEM). The SSFEM was widely used to quantify the effect of input data uncertainties on the outputs of finite element models. The bloc iterative solver allows reducing computational cost of the SSFEM. The method is applied on an industrial Non Destructive Testing (NDT) problem. The numerical performances of the method are compared with those of the Non-Intrusive Spectral Projection (NISP). Version éditeur disponible à cette adresse : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6514633 Tue, 01 Jan 2013 00:00:00 GMT http://hdl.handle.net/10985/7317 2013-01-01T00:00:00Z BEDDEK, Karim MOREAU, Olivier LE MENACH, Yvonnick CLENET, Stephane This paper describes an efficient bloc iterative solver for the Spectral Stochastic Finite Element Method (SSFEM). The SSFEM was widely used to quantify the effect of input data uncertainties on the outputs of finite element models. The bloc iterative solver allows reducing computational cost of the SSFEM. The method is applied on an industrial Non Destructive Testing (NDT) problem. The numerical performances of the method are compared with those of the Non-Intrusive Spectral Projection (NISP). http://hdl.handle.net/10985/7482 Influence of uncertainties on the B(H) curves on the flux linkage of a turboalternator MAC, Hung; BEDDEK, Karim; KORECKI, Julien; MOREAU, Olivier; CHEVALLIER, Loic; THOMAS, Pierre; CLENET, Stephane In this paper, we analyze the influence of the uncertainties on the behavior constitutive laws of ferromagnetic materials on the behavior of a turboalternator. A simple stochastic model of anhysteretic nonlinear B(H) curve is proposed for the ferromagnetic yokes of the stator and the rotor. The B(H) curve is defined by five random parameters. We quantify the influence of the variability of these five parameters on the flux linkage of one phase of the stator winding depending on the excitation current I. The influence of each parameter is analyzed via the Sobol indices. With this analysis, we can determine the most influential parameters for each state of magnetization (according to the level of I) and investigate where the characterization process of the B(H) curve should focus to improve the accuracy of the computed flux linkage. Tue, 01 Jan 2013 00:00:00 GMT http://hdl.handle.net/10985/7482 2013-01-01T00:00:00Z MAC, Hung BEDDEK, Karim KORECKI, Julien MOREAU, Olivier CHEVALLIER, Loic THOMAS, Pierre CLENET, Stephane In this paper, we analyze the influence of the uncertainties on the behavior constitutive laws of ferromagnetic materials on the behavior of a turboalternator. A simple stochastic model of anhysteretic nonlinear B(H) curve is proposed for the ferromagnetic yokes of the stator and the rotor. The B(H) curve is defined by five random parameters. We quantify the influence of the variability of these five parameters on the flux linkage of one phase of the stator winding depending on the excitation current I. The influence of each parameter is analyzed via the Sobol indices. With this analysis, we can determine the most influential parameters for each state of magnetization (according to the level of I) and investigate where the characterization process of the B(H) curve should focus to improve the accuracy of the computed flux linkage. http://hdl.handle.net/10985/7275 Solution of Static Field Problems With Random Domains MAC, Duy Hung; MIPO, Jean-Claude; MOREAU, Olivier; CLENET, Stephane A method to solve stochastic partial differential equations on random domains consists in using a one-to-one random mapping function which transforms the random domain into a deterministic domain. With this method, the randomness is then borne by the constitutive relationship of the material. In this paper, this method is applied in electrokinetics in the case of scalar potential and vector potential formulations. An example is treated and the proposed method is compared to a nonintrusive method (NIM) based on the remeshing of the random domains. Fri, 01 Jan 2010 00:00:00 GMT http://hdl.handle.net/10985/7275 2010-01-01T00:00:00Z MAC, Duy Hung MIPO, Jean-Claude MOREAU, Olivier CLENET, Stephane A method to solve stochastic partial differential equations on random domains consists in using a one-to-one random mapping function which transforms the random domain into a deterministic domain. With this method, the randomness is then borne by the constitutive relationship of the material. In this paper, this method is applied in electrokinetics in the case of scalar potential and vector potential formulations. An example is treated and the proposed method is compared to a nonintrusive method (NIM) based on the remeshing of the random domains.