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The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.Wed, 20 Jan 2021 19:31:05 GMT2021-01-20T19:31:05ZCharacterization of the local Electrical Properties of Electrical Machine Parts with non-Trivial Geometry
http://hdl.handle.net/10985/9861
Characterization of the local Electrical Properties of Electrical Machine Parts with non-Trivial Geometry
ARBENZ, Laure; BENABOU, Abdelkader; CLENET, Stéphane; MIPO, Jean-Claude; FAVEROLLE, Pierre
In electrical machines, knowing the electrical conductivity is of importance for the eddy current calculation, especially when massive iron parts are involved. Generally the conductivity is measured on samples of raw materials with simple geometries. Indeed, a simple geometry is suitable for applying an analytical approach to deduce the electrical conductivity from the measured electrical quantities. Nevertheless, when a non destructive measurement is required, the measurement of the electrical conductivity can become rather difficult on parts with complex geometry. To that end, with the help of the Finite Element Modeling approach (FEM), a strategy is developed to characterize the local electrical properties of parts with a non-trivial geometry.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/98612015-01-01T00:00:00ZARBENZ, LaureBENABOU, AbdelkaderCLENET, StéphaneMIPO, Jean-ClaudeFAVEROLLE, PierreIn electrical machines, knowing the electrical conductivity is of importance for the eddy current calculation, especially when massive iron parts are involved. Generally the conductivity is measured on samples of raw materials with simple geometries. Indeed, a simple geometry is suitable for applying an analytical approach to deduce the electrical conductivity from the measured electrical quantities. Nevertheless, when a non destructive measurement is required, the measurement of the electrical conductivity can become rather difficult on parts with complex geometry. To that end, with the help of the Finite Element Modeling approach (FEM), a strategy is developed to characterize the local electrical properties of parts with a non-trivial geometry.Solution of Large Stochastic Finite Element Problems – Application to ECT-NDT
http://hdl.handle.net/10985/7317
Solution of Large Stochastic Finite Element Problems – Application to ECT-NDT
BEDDEK, Karim; CLENET, Stéphane; MOREAU, Olivier; LE MENACH, Yvonnick
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 GMThttp://hdl.handle.net/10985/73172013-01-01T00:00:00ZBEDDEK, KarimCLENET, StéphaneMOREAU, OlivierLE MENACH, YvonnickThis 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).Experimental characterization of the iron losses variability in stators of electrical machines
http://hdl.handle.net/10985/7115
Experimental characterization of the iron losses variability in stators of electrical machines
RAMAROTAFIKA, Rindra; BENABOU, Abdelkader; MIPO, Jean-Claude; CLENET, Stéphane
Manufacturing processes may introduce a significant variability on the magnetic properties of claw pole generator stators. The present work deals with the analysis of two groups of stator samples. The first group is composed of 28 slinky stators (SS) and the second group is composed of 5 stators, manufactured using laser cut stacked laminations (SL). Both groups are made from the same lamination grade and with the same geometrical dimensions. Characterization was carried out for several levels of excitation field at 50Hz. A noticeable variability has been observed on the iron losses for SS samples, whereas it appears to be not significant for SL samples. The loss separation technique has then been investigated for the SS samples. Results show that the variability of static losses is more important than the one of dynamic losses.
Version éditeur disponible à l'adresse suivante : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6172417
Sun, 01 Jan 2012 00:00:00 GMThttp://hdl.handle.net/10985/71152012-01-01T00:00:00ZRAMAROTAFIKA, RindraBENABOU, AbdelkaderMIPO, Jean-ClaudeCLENET, StéphaneManufacturing processes may introduce a significant variability on the magnetic properties of claw pole generator stators. The present work deals with the analysis of two groups of stator samples. The first group is composed of 28 slinky stators (SS) and the second group is composed of 5 stators, manufactured using laser cut stacked laminations (SL). Both groups are made from the same lamination grade and with the same geometrical dimensions. Characterization was carried out for several levels of excitation field at 50Hz. A noticeable variability has been observed on the iron losses for SS samples, whereas it appears to be not significant for SL samples. The loss separation technique has then been investigated for the SS samples. Results show that the variability of static losses is more important than the one of dynamic losses.Stochastic Non Destructive Testing simulation: sensitivity analysis applied to material properties in clogging of nuclear power plant steam generators
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; CLENET, Stéphane; LE MENACH, Yvonnick
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 GMThttp://hdl.handle.net/10985/71162013-01-01T00:00:00ZMOREAU, OlivierBEDDEK, KarimCLENET, StéphaneLE MENACH, YvonnickA 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 outputComparizon of Conventional and Unconventional 5-phase PM Motor Structures for Naval Applications
http://hdl.handle.net/10985/7378
Comparizon of Conventional and Unconventional 5-phase PM Motor Structures for Naval Applications
SCUILLER, Franck; SEMAIL, Eric; CHARPENTIER, Jean-Frederic; CLENET, Stéphane
Multi-phase motors are widely used in marine propulsion. In this paper, a Multi-machine modeling of Surface Mounted PM motors is presented and applied to a 5-phase one. The latter is proved to be equivalent to a set of two-phase fictitious machines each ones being characterized by a set of specific harmonic rank. A simple control consists in supplying each fictitious machine by a current which contains only one harmonic. A five phase machine is then supplied by currents with only both first and third harmonics. Considering this kind of control, it is proved that for given stator resistance and average torque the Joule losses and the torque ripple are minimized if a simple criterion on the harmonics of electromotive force at constant speed is fullfilled. Different structures of rotor are then compared to examine numerically which improvements can be practically obtained
Thu, 01 Jan 2004 00:00:00 GMThttp://hdl.handle.net/10985/73782004-01-01T00:00:00ZSCUILLER, FranckSEMAIL, EricCHARPENTIER, Jean-FredericCLENET, StéphaneMulti-phase motors are widely used in marine propulsion. In this paper, a Multi-machine modeling of Surface Mounted PM motors is presented and applied to a 5-phase one. The latter is proved to be equivalent to a set of two-phase fictitious machines each ones being characterized by a set of specific harmonic rank. A simple control consists in supplying each fictitious machine by a current which contains only one harmonic. A five phase machine is then supplied by currents with only both first and third harmonics. Considering this kind of control, it is proved that for given stator resistance and average torque the Joule losses and the torque ripple are minimized if a simple criterion on the harmonics of electromotive force at constant speed is fullfilled. Different structures of rotor are then compared to examine numerically which improvements can be practically obtainedBalanced Proper Orthogonal Decomposition Applied to Magnetoquasistatic Problems Through a Stabilization Methodology
http://hdl.handle.net/10985/11755
Balanced Proper Orthogonal Decomposition Applied to Magnetoquasistatic Problems Through a Stabilization Methodology
MONTIER, Laurent; HENNERON, Thomas; GOURSAUD, Benjamin; CLENET, Stéphane
Model Order Reduction (MOR) methods are applied in different areas of physics in order to reduce the computational time of large scale systems. It has been an active field of research for many years, in mechanics especially, but it is quite recent for magnetoquasistatic problems. Although the most famous method, the Proper Orthogonal Decomposition (POD) has been applied for modelling many electromagnetic devices, this method can lack accuracy for low order magnitude output quantities, like flux associated with a probe in regions where the field is low. However, the Balanced Proper Orthogonal Decomposition (BPOD) is a MOR method which takes into account these output quantities in its reduced model to render them accurately. Even if the BPOD may lead to unstable reduced systems, this can be overcome by a stabilization procedure. Therefore, the POD and stabilized BPOD will be compared on a 3D linear magnetoquasistatic field problem.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/117552017-01-01T00:00:00ZMONTIER, LaurentHENNERON, ThomasGOURSAUD, BenjaminCLENET, StéphaneModel Order Reduction (MOR) methods are applied in different areas of physics in order to reduce the computational time of large scale systems. It has been an active field of research for many years, in mechanics especially, but it is quite recent for magnetoquasistatic problems. Although the most famous method, the Proper Orthogonal Decomposition (POD) has been applied for modelling many electromagnetic devices, this method can lack accuracy for low order magnitude output quantities, like flux associated with a probe in regions where the field is low. However, the Balanced Proper Orthogonal Decomposition (BPOD) is a MOR method which takes into account these output quantities in its reduced model to render them accurately. Even if the BPOD may lead to unstable reduced systems, this can be overcome by a stabilization procedure. Therefore, the POD and stabilized BPOD will be compared on a 3D linear magnetoquasistatic field problem.Comparison of DEIM and BPIM to Speed up a POD-based Nonlinear Magnetostatic Model
http://hdl.handle.net/10985/11757
Comparison of DEIM and BPIM to Speed up a POD-based Nonlinear Magnetostatic Model
HENNERON, Thomas; MONTIER, Laurent; PIERQUIN, Antoine; CLENET, Stéphane
Proper Orthogonal Decomposition (POD) has been successfully used to reduce the size of linear Finite Element (FE) problems, and thus the computational time associated with. When considering a nonlinear behavior law of the ferromagnetic materials, the POD is not so efficient due to the high computational cost associated to the nonlinear entries of the full FE model. Then, the POD approach must be combined with an interpolation method to efficiently deal with the nonlinear terms, and thus obtaining an efficient reduced model. An interpolation method consists in computing a small number of nonlinear entries and interpolating the other terms. Different methods have been presented to select the set of nonlinear entries to be calculated. Then, the (Discrete) Empirical Interpolation method ((D)EIM) and the Best Points Interpolation Method (BPIM) have been developed. In this article, we propose to compare two reduced models based on the POD-(D)EIM and on the POD-BPIM in the case of nonlinear magnetostatics coupled with electric equation.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/117572017-01-01T00:00:00ZHENNERON, ThomasMONTIER, LaurentPIERQUIN, AntoineCLENET, StéphaneProper Orthogonal Decomposition (POD) has been successfully used to reduce the size of linear Finite Element (FE) problems, and thus the computational time associated with. When considering a nonlinear behavior law of the ferromagnetic materials, the POD is not so efficient due to the high computational cost associated to the nonlinear entries of the full FE model. Then, the POD approach must be combined with an interpolation method to efficiently deal with the nonlinear terms, and thus obtaining an efficient reduced model. An interpolation method consists in computing a small number of nonlinear entries and interpolating the other terms. Different methods have been presented to select the set of nonlinear entries to be calculated. Then, the (Discrete) Empirical Interpolation method ((D)EIM) and the Best Points Interpolation Method (BPIM) have been developed. In this article, we propose to compare two reduced models based on the POD-(D)EIM and on the POD-BPIM in the case of nonlinear magnetostatics coupled with electric equation.Application of the Proper Generalized Decomposition to Solve MagnetoElectric Problem
http://hdl.handle.net/10985/12496
Application of the Proper Generalized Decomposition to Solve MagnetoElectric Problem
HENNERON, Thomas; CLENET, Stéphane
Among the model order reduction techniques, the Proper Generalized Decomposition (PGD) has shown its efficiency to solve a large number of engineering problems. In this article, the PGD approach is applied to solve a multi-physics problem based on a magnetoelectric device. A reduced model is developed to study the device in its environment based on an Offline/Online approach. In the Offline step, two specific simulations are performed in order to build a PGD reduced model. Then, we obtain a model very well fitted to study in the Online stage the influence of parameters like the frequency or the load. The reduced model of the device is coupled with an electric load (R-L) to illustrate the possibility offered by the PGD.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/124962017-01-01T00:00:00ZHENNERON, ThomasCLENET, StéphaneAmong the model order reduction techniques, the Proper Generalized Decomposition (PGD) has shown its efficiency to solve a large number of engineering problems. In this article, the PGD approach is applied to solve a multi-physics problem based on a magnetoelectric device. A reduced model is developed to study the device in its environment based on an Offline/Online approach. In the Offline step, two specific simulations are performed in order to build a PGD reduced model. Then, we obtain a model very well fitted to study in the Online stage the influence of parameters like the frequency or the load. The reduced model of the device is coupled with an electric load (R-L) to illustrate the possibility offered by the PGD.Proper Generalized Decomposition Applied on a Rotating Electrical Machine
http://hdl.handle.net/10985/12734
Proper Generalized Decomposition Applied on a Rotating Electrical Machine
MONTIER, Laurent; HENNERON, Thomas; CLENET, Stéphane; GOURSAUD, Benjamin
The Proper Generalized Decomposition (PGD) is a model order reduction method which allows to reduce the computational time of a numerical problem by seeking for a separated representation of the solution. The PGD has been already applied to study an electrical machine but at standstill without accounting the motion of the rotor. In this paper, we propose a method to account for the rotation in the PGD approach in order to build an efficient metamodel of an electrical machine. Then, the machine metamodel will be coupled to its electrical and mechanical environment in order to obtain accurate results with an acceptable computational time on a full simulation.
Mon, 01 Jan 2018 00:00:00 GMThttp://hdl.handle.net/10985/127342018-01-01T00:00:00ZMONTIER, LaurentHENNERON, ThomasCLENET, StéphaneGOURSAUD, BenjaminThe Proper Generalized Decomposition (PGD) is a model order reduction method which allows to reduce the computational time of a numerical problem by seeking for a separated representation of the solution. The PGD has been already applied to study an electrical machine but at standstill without accounting the motion of the rotor. In this paper, we propose a method to account for the rotation in the PGD approach in order to build an efficient metamodel of an electrical machine. Then, the machine metamodel will be coupled to its electrical and mechanical environment in order to obtain accurate results with an acceptable computational time on a full simulation.Data-Driven Model Order Reduction for Magnetostatic Problem Coupled with Circuit Equations
http://hdl.handle.net/10985/12997
Data-Driven Model Order Reduction for Magnetostatic Problem Coupled with Circuit Equations
PIERQUIN, Antoine; HENNERON, Thomas; CLENET, Stéphane
Among the model order reduction techniques, the Proper Orthogonal Decomposition (POD) has shown its efficiency to solve magnetostatic and magneto-quasistatic problems in the time domain. However, the POD is intrusive in the sense that it requires the extraction of the matrix system of the full model to build the reduced model. To avoid this extraction, nonintrusive approaches like the Data Driven (DD) methods enable to approximate the reduced model without the access to the full matrix system. In this article, the DD-POD method is applied to build a low dimensional system to solve a magnetostatic problem coupled with electric circuit equations.
Mon, 01 Jan 2018 00:00:00 GMThttp://hdl.handle.net/10985/129972018-01-01T00:00:00ZPIERQUIN, AntoineHENNERON, ThomasCLENET, StéphaneAmong the model order reduction techniques, the Proper Orthogonal Decomposition (POD) has shown its efficiency to solve magnetostatic and magneto-quasistatic problems in the time domain. However, the POD is intrusive in the sense that it requires the extraction of the matrix system of the full model to build the reduced model. To avoid this extraction, nonintrusive approaches like the Data Driven (DD) methods enable to approximate the reduced model without the access to the full matrix system. In this article, the DD-POD method is applied to build a low dimensional system to solve a magnetostatic problem coupled with electric circuit equations.