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The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.Thu, 22 Feb 2024 20:46:28 GMT2024-02-22T20:46:28ZMesh Deformation Based on Radial Basis Function Interpolation Applied to Low-Frequency Electromagnetic Problem
http://hdl.handle.net/10985/16535
Mesh Deformation Based on Radial Basis Function Interpolation Applied to Low-Frequency Electromagnetic Problem
HENNERON, Thomas; PIERQUIN, Antoine; CLENET, Stéphane
In order to take into account a modification of the geometry during an optimization process or due to a physical phenomenon, a deformation of the elements of the spatial discretization is preferable to conserve a conformal mesh and to apply the Finite Element (FE) method. To perform the displacement of nodes, interpolation method can be investigated in this context. In this paper, the Radial Basis Function (RBF) interpolation method is applied for low frequency electromagnetic problems solved by the FE method.. A 2D magnetostatic example is considered to study the influence of the parameters of the RBF interpolation. To test the extension in 3D, a non destructive testing (NDT) problem is treated where the shape of the crack is modified by applying the proposed method.
Tue, 01 Jan 2019 00:00:00 GMThttp://hdl.handle.net/10985/165352019-01-01T00:00:00ZHENNERON, ThomasPIERQUIN, AntoineCLENET, StéphaneIn order to take into account a modification of the geometry during an optimization process or due to a physical phenomenon, a deformation of the elements of the spatial discretization is preferable to conserve a conformal mesh and to apply the Finite Element (FE) method. To perform the displacement of nodes, interpolation method can be investigated in this context. In this paper, the Radial Basis Function (RBF) interpolation method is applied for low frequency electromagnetic problems solved by the FE method.. A 2D magnetostatic example is considered to study the influence of the parameters of the RBF interpolation. To test the extension in 3D, a non destructive testing (NDT) problem is treated where the shape of the crack is modified by applying the proposed method.Transient simulation of an electrical rotating machine achieved through model order reduction
http://hdl.handle.net/10985/16571
Transient simulation of an electrical rotating machine achieved through model order reduction
MONTIER, Laurent; HENNERON, Thomas; CLÉNET, Stéphane; GOURSAUD, Benjamin
Model Order Reduction (MOR) methods are more and more applied on many di erent elds of physics in order to reduce the number of unknowns and thus the computational time of large-scale systems. However, their application is quite recent in the eld of computational electromagnetics. In the case of electrical machine, the numerical model has to take into account the nonlinear behaviour of ferromagnetic materials, motion of the rotor, circuit equations and mechanical coupling. In this context, we propose to apply the Proper Orthogonal Decomposition combined with the (Discrete) Empirical Interpolation Method in order to reduce the computation time required to study the start-up of an electrical machine until it reaches the steady state. An empirical O ine/Online approach based on electrical engineering is proposed in order to build an e cient reduced model accurate on the whole operating range. Finally, a 2D example of a synchronous machine is studied with a reduced model deduced from the proposed approach.
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/10985/165712016-01-01T00:00:00ZMONTIER, LaurentHENNERON, ThomasCLÉNET, StéphaneGOURSAUD, BenjaminModel Order Reduction (MOR) methods are more and more applied on many di erent elds of physics in order to reduce the number of unknowns and thus the computational time of large-scale systems. However, their application is quite recent in the eld of computational electromagnetics. In the case of electrical machine, the numerical model has to take into account the nonlinear behaviour of ferromagnetic materials, motion of the rotor, circuit equations and mechanical coupling. In this context, we propose to apply the Proper Orthogonal Decomposition combined with the (Discrete) Empirical Interpolation Method in order to reduce the computation time required to study the start-up of an electrical machine until it reaches the steady state. An empirical O ine/Online approach based on electrical engineering is proposed in order to build an e cient reduced model accurate on the whole operating range. Finally, a 2D example of a synchronous machine is studied with a reduced model deduced from the proposed approach.Rotation Movement Based on the Spatial Fourier Interpolation Method
http://hdl.handle.net/10985/16568
Rotation Movement Based on the Spatial Fourier Interpolation Method
MONTIER, Laurent; CLENET, Stéphane; HENNERON, Thomas; GOURSAUD, Benjamin
In the field of computational electromagnetics, taking into account the rotation of a sub-domain is required to simulate certain devices such as electrical machines. Several methods have been proposed in the literature, but they remain quite difficult to implement. In this paper, we propose a sliding surface method based on a spatial Fourier interpolation in order to take into account any rotation angle with a very simple numerical implementation.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/165682017-01-01T00:00:00ZMONTIER, LaurentCLENET, StéphaneHENNERON, ThomasGOURSAUD, BenjaminIn the field of computational electromagnetics, taking into account the rotation of a sub-domain is required to simulate certain devices such as electrical machines. Several methods have been proposed in the literature, but they remain quite difficult to implement. In this paper, we propose a sliding surface method based on a spatial Fourier interpolation in order to take into account any rotation angle with a very simple numerical implementation.Optimisation process to solve multirate system
http://hdl.handle.net/10985/16567
Optimisation process to solve multirate system
PIERQUIN, Antoine; HENNERON, Thomas; CLENET, Stéphane; BRISSET, Stephane
The modelling of a multirate system -composed of components with heterogeneous time constants- can be done using fixed-point method. This method allows a time-discretization of each subsystem with respect to its own time constant. In an optimisation process, executing the loop of the fixed-point at each model evaluation can be time consuming. By adding one of the searched waveform of the system to the optimisation variables, the loop can be avoided. This strategy is applied to the optimisation of a transformer.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/165672015-01-01T00:00:00ZPIERQUIN, AntoineHENNERON, ThomasCLENET, StéphaneBRISSET, StephaneThe modelling of a multirate system -composed of components with heterogeneous time constants- can be done using fixed-point method. This method allows a time-discretization of each subsystem with respect to its own time constant. In an optimisation process, executing the loop of the fixed-point at each model evaluation can be time consuming. By adding one of the searched waveform of the system to the optimisation variables, the loop can be avoided. This strategy is applied to the optimisation of a transformer.Structure Preserving Model Reduction of Low-Frequency Electromagnetic Problem Based on POD and DEIM
http://hdl.handle.net/10985/16570
Structure Preserving Model Reduction of Low-Frequency Electromagnetic Problem Based on POD and DEIM
MONTIER, Laurent; PIERQUIN, Antoine; HENNERON, Thomas; CLENET, Stéphane
The Proper Orthogonal Decomposition (POD) combined with the (Discrete) Empirical Interpolation Method (DEIM) can be used to reduce the computation time of the solution of a Finite Element (FE) model. However, it can lead to numerical instabilities. To increase the robustness, the POD_DEIM model must be constructed by preserving the structure of the full FE model. In this article, the structure preserving is applied for different potential formulations used to solve electromagnetic problems.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/165702017-01-01T00:00:00ZMONTIER, LaurentPIERQUIN, AntoineHENNERON, ThomasCLENET, StéphaneThe Proper Orthogonal Decomposition (POD) combined with the (Discrete) Empirical Interpolation Method (DEIM) can be used to reduce the computation time of the solution of a Finite Element (FE) model. However, it can lead to numerical instabilities. To increase the robustness, the POD_DEIM model must be constructed by preserving the structure of the full FE model. In this article, the structure preserving is applied for different potential formulations used to solve electromagnetic problems.Error Estimation for Model Order Reduction of Finite Element Parametric Problems
http://hdl.handle.net/10985/11034
Error Estimation for Model Order Reduction of Finite Element Parametric Problems
CLENET, Stéphane; HENNERON, Thomas
To solve a parametric model in computational electromagnetics, the Finite Element method is often used. To reduce the computational time and the memory requirement, the Finite Element method can be combined with Model Order Reduction Technic like the Proper Orthogonal Decomposition (POD) and the (Discrete) Empirical Interpolation ((D)EI) Methods. These three numerical methods introduce errors of discretisation, reduction and interpolation respectively. The solution of the parametric model will be efficient if the three errors are of the same order and so they need to be evaluated and compared. In this paper, we propose an aposteriori error estimator based on the verification of the constitutive law which estimates the three different errors. An example of application in magnetostatics with 11 parameters is treated where it is shown how the error estimator can be used to control and to improve the accuracy of the solution of the reduced model.
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/10985/110342016-01-01T00:00:00ZCLENET, StéphaneHENNERON, ThomasTo solve a parametric model in computational electromagnetics, the Finite Element method is often used. To reduce the computational time and the memory requirement, the Finite Element method can be combined with Model Order Reduction Technic like the Proper Orthogonal Decomposition (POD) and the (Discrete) Empirical Interpolation ((D)EI) Methods. These three numerical methods introduce errors of discretisation, reduction and interpolation respectively. The solution of the parametric model will be efficient if the three errors are of the same order and so they need to be evaluated and compared. In this paper, we propose an aposteriori error estimator based on the verification of the constitutive law which estimates the three different errors. An example of application in magnetostatics with 11 parameters is treated where it is shown how the error estimator can be used to control and to improve the accuracy of the solution of the reduced model.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.Model Order Reduction of Non-Linear Magnetostatic Problems Based on POD and DEI Methods
http://hdl.handle.net/10985/7816
Model Order Reduction of Non-Linear Magnetostatic Problems Based on POD and DEI Methods
HENNERON, Thomas; CLENET, Stéphane
In the domain of numerical computation, Model Order Reduction approaches are more and more frequently applied in mechanics and have shown their efficiency in terms of reduction of computation time and memory storage requirements. One of these approaches, the Proper Orthogonal Decomposition (POD), can be very efficient in solving linear problems but encounters limitations in the non-linear case. In this paper, the Discret Empirical Interpolation Method coupled with the POD method is presented. This is an interesting alternative to reduce large-scale systems deriving from the discretization of non-linear magnetostatic problems coupled with an external electrical circuit.
Wed, 01 Jan 2014 00:00:00 GMThttp://hdl.handle.net/10985/78162014-01-01T00:00:00ZHENNERON, ThomasCLENET, StéphaneIn the domain of numerical computation, Model Order Reduction approaches are more and more frequently applied in mechanics and have shown their efficiency in terms of reduction of computation time and memory storage requirements. One of these approaches, the Proper Orthogonal Decomposition (POD), can be very efficient in solving linear problems but encounters limitations in the non-linear case. In this paper, the Discret Empirical Interpolation Method coupled with the POD method is presented. This is an interesting alternative to reduce large-scale systems deriving from the discretization of non-linear magnetostatic problems coupled with an external electrical circuit.Application of the Proper Generalized Decomposition to Solve MagnetoElectric Problem
http://hdl.handle.net/10985/12754
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 imulations 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.
Mon, 01 Jan 2018 00:00:00 GMThttp://hdl.handle.net/10985/127542018-01-01T00:00:00ZHENNERON, 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 imulations 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.