The Experts below are selected from a list of 268158 Experts worldwide ranked by ideXlab platform
Wim Desmet - One of the best experts on this subject based on the ideXlab platform.
-
a Parametric Model order reduction technique for inverse viscoelastic material identification
Computers & Structures, 2019Co-Authors: Hui Zheng, Xiang Xie, Stijn Jonckheere, Bert Pluymers, Wim DesmetAbstract:Abstract Viscoelastic materials are mostly used to passively suppress structural vibrations. The theoretical analysis and design of such system require the knowledge of damping properties which are highly frequency-dependent and proper mathematical Models for this dependency. The fractional derivative Model is attractive as very few empirical parameters are required. These parameters can be identified through inverse procedures, either by fitting the frequency dependent constitutive properties from a dedicated dynamical mechanical analyzer experiment, or by fitting response curves, e.g. frequency response functions (FRFs) by using a dedicated numerical Model. The optimization process requires frequently iterative prediction of the FRFs of large-scale full order Model and furthermore each Model inversion is expensive. To speed up numerical simulations, a Parametric Model order reduction technique is introduced. In the material parameter search space, quasi-random sequences are chosen and divided into two disjoint sets: a sample set is used to construct a reduced order Model (ROM); while a validation set is used to assess its performance. A global orthonormal basis can then be constructed by non-weighted singular value decomposition on all local bases. Since the parameter- and frequency-dependency can be suitably preserved, the generated single ROM in conjunction with optimization algorithms is very useful to identify the material parameters of viscoelastic damping. The versatility and efficiency of the present procedure are demonstrated through a number of validation cases.
-
An on-line time dependent Parametric Model order reduction scheme with focus on dynamic stress recovery
Computer Methods in Applied Mechanics and Engineering, 2014Co-Authors: T. Tamarozzi, G.h.k. Heirman, Wim DesmetAbstract:In view of the tendency towards ever lighter and more powerful machines and even shorter design cycles, it becomes essential to have virtual prototyping tools that allow for fast and reliable numerical simulations. Current state-of-the-art structural dynamics and flexible multibody simulation techniques usually involve the solution of matrix systems with thousands to millions of variables. Model order reduction schemes are used to keep computational effort affordable at the expense of a minimal loss of accuracy. These techniques typically face difficulties with systems in which flexible bodies can be loaded in many degrees of freedom and rarely allow for accurate local stress and strain evaluation. The present work proposes to address both issues for the particular but frequent case of moving loads or boundary conditions. This behavior is found in most of the contact problems and systems that include sliding components for which many loading or boundary locations are possible but only a few of them are active at a certain moment in time. The proposed scheme exploits a reduction vector space that continuously varies in time by means of a Parametric definition of the external load position. Contrary to the majority of the Parametric Model order reduction schemes that allow mainly for quasi-static Parametric variations, the proposed approach can be used efficiently for time simulation of dynamically varying Parametric Models. This is achieved by considering the implicit time dependency of the reduction vector space using Galerkin projections or alternatively by direct substitution of the reduced kinetic energy, potential energy and generalized forces in the Lagrange equations. It is shown, by developing a consistent mathematical framework, that the price to pay for the very compact reduction space obtained is the evaluation of some extra terms in the equations of motion. Numerical examples are used to assess the accuracy of the proposed method. Results show the potential of this strategy with particular focus on displacement and stress fields and furthermore highlight its real-time potential. Moreover the developed framework together with the numerical results allow for a deeper physical understanding of the complex phenomena related to this category of time varying multiple-input/multiple output systems.
Desmet Wim - One of the best experts on this subject based on the ideXlab platform.
-
A Parametric Model order reduction technique for inverse viscoelastic material identification
'Elsevier BV', 2018Co-Authors: Xie Xiang, Zheng Hui, Jonckheere Stijn, Pluymers Bert, Desmet WimAbstract:© 2018 Elsevier Ltd Viscoelastic materials are mostly used to passively suppress structural vibrations. The theoretical analysis and design of such system require the knowledge of damping properties which are highly frequency-dependent and proper mathematical Models for this dependency. The fractional derivative Model is attractive as very few empirical parameters are required. These parameters can be identified through inverse procedures, either by fitting the frequency dependent constitutive properties from a dedicated dynamical mechanical analyzer experiment, or by fitting response curves, e.g. frequency response functions (FRFs) by using a dedicated numerical Model. The optimization process requires frequently iterative prediction of the FRFs of large-scale full order Model and furthermore each Model inversion is expensive. To speed up numerical simulations, a Parametric Model order reduction technique is introduced. In the material parameter search space, quasi-random sequences are chosen and divided into two disjoint sets: a sample set is used to construct a reduced order Model (ROM); while a validation set is used to assess its performance. A global orthonormal basis can then be constructed by non-weighted singular value decomposition on all local bases. Since the parameter- and frequency-dependency can be suitably preserved, the generated single ROM in conjunction with optimization algorithms is very useful to identify the material parameters of viscoelastic damping. The versatility and efficiency of the present procedure are demonstrated through a number of validation cases.status: publishe
-
Semi-analytic contact technique in a non-linear Parametric Model order reduction method for gear simulations
'Springer Science and Business Media LLC', 2018Co-Authors: Cappellini Niccolo', Tamarozzi Tommaso, Blockmans Bart, Fiszer Jakob, Cosco Francesco, Desmet WimAbstract:In this work we present a novel method for the solution of gear contact problems in flexible multi-body. These problems are characterized by significant variation in the location and size of the contact area, typically requiring a high number of degrees of freedom to correctly capture deformation and stress fields. Therefore fully dynamic simulation is computationally prohibitive. To overcome these limitations, we exploit a combined analytic-numerical contact Model within a Parametric Model order reduction (PMOR) scheme. The reduction space consists of a truncated set of eigenvectors augmented with a parameter dependent set of residual static shape vectors. Each static shape is computed by interpolating among a set of displacement modes of the interacting bodies, obtained from a series of precomputed static contact analyses. During the contact analyses, an analytic Model based on the Hertz theory describes the teeth local deformation. We implement the proposed method in an in-house code and we apply it to spur and helical gears dynamic contact analyses. We compare the results with classical PMOR schemes highlighting how the combined use of the semi-analytic contact Model allows to decrease further the Model complexity as well as the computational burden, for both static and dynamic cases. Finally, we validate the methodology by means of a comparison with experimental data found in literature, showing that the numerical method is able to capture quantitatively the static transmission error measurements in case of both helical and spur geared transmission for different torque levelsstatus: publishe
-
Efficient vibro-acoustic Model updating of localized properties using low-rank Parametric Model order reduction schemes
2017Co-Authors: Van Ophem Sjoerd, Van De Walle, Axel, Deckers Elke, Desmet WimAbstract:The growth of computational power in the last decades has made it possible to perform more complicated vibro-acoustic simulations than ever. However, to predict the actual physical behavior of a vibro-acoustic system, an accurate estimation of important physical properties has to be available in order to produce useful simulation results. For localized features, such as bolt connections and welds, this is not always a straightforward task. This is where Model updating comes into play: It uses measurement data to update the numerical Model through an optimization procedure, so that it conforms more closely the real, physical system. One of the main drawbacks of the Model updating procedure is the time required to perform the optimization, because many frequency response evaluations are required on the full numerical Model. For a fully coupled vibro-acoustic analysis, often high-dimensional finite element Models are used, for which the calculation of a single frequency line can already consume a significant amount of computational resources. This means that Model updating cannot be performed on-line and is usually carried out on only a limited parameter set. Parametric Model order reduction schemes are a promising tool for reducing the calculation time, since they significantly reduce the system size, while maintaining a high accuracy, and still preserve the (explicit) parameter dependency in the reduced order Model. These resulting reduced order Models can thus be used directly in the optimization procedure. A drawback of most Parametric reduction schemes is that the calculation of the reduced basis can be time consuming due to the necessity to sample the parameter space beforehand. This also implies that the range of possible values for the chosen parameters has to be known. However, when the parameters are only acting locally, this is not necessary, because the low-rank character of these parameters can be exploited. Namely, the low-rank character allows the system to be rewritten so that non-Parametric Model reduction algorithms can be applied. In this presentation a novel approach for low-rank Parametric Model order reduction is presented, which significantly speeds up the Model updating process. It requires no a-priori sampling of the reduced basis and it can handle many parameters simultaneously, with only a moderate Model size. The presented scheme is applied to a fully coupled vibro-acoustic system consisting of a clamped plate with a backing cavity, where the goal is to detect the proper boundary conditions of the plate. Since in practice this clamping is imperfect, the proposed method is used to identify the actual degree of clamping. It is shown that the proposed method successfully identifies the boundary conditions in a short time frame, while the same calculation with the non-reduced Model would take several days.status: publishe
-
An on-line time dependent Parametric Model order reduction scheme with focus on dynamic stress recovery
'Elsevier BV', 2014Co-Authors: Tamarozzi Tommaso, G.h.k. Heirman, Desmet WimAbstract:In view of the tendency towards ever lighter and more powerful machines and even shorter design cycles, it becomes essential to have virtual prototyping tools that allow for fast and reliable numerical simulations. Current state-of-the-art structural dynamics and flexible multibody simulation techniques usually involve the solution of matrix systems with thousands to millions of variables. Model order reduction schemes are used to keep computational effort affordable at the expense of a minimal loss of accuracy. These techniques typically face difficulties with systems in which flexible bodies can be loaded in many degrees of freedom and rarely allow for accurate local stress and strain evaluation. The present work proposes to address both issues for the particular but frequent case of moving loads or boundary conditions. This behavior is found in most of the contact problems and systems that include sliding components for which many loading or boundary locations are possible but only a few of them are active at a certain moment in time. The proposed scheme exploits a reduction vector space that continuously varies in time by means of a Parametric definition of the external load position. Contrary to the majority of the Parametric Model order reduction schemes that allow mainly for quasi-static Parametric variations, the proposed approach can be used efficiently for time simulation of dynamically varying Parametric Models. This is achieved by considering the implicit time dependency of the reduction vector space using Galerkin projections or alternatively by direct substitution of the reduced kinetic energy, potential energy and generalized forces in the Lagrange equations. It is shown, by developing a consistent mathematical framework, that the price to pay for the very compact reduction space obtained is the evaluation of some extra terms in the equations of motion. Numerical examples are used to assess the accuracy of the proposed method. Results show the potential of this strategy with particular focus on displacement and stress fields and furthermore highlight its real-time potential. Moreover the developed framework together with the numerical results allow for a deeper physical understanding of the complex phenomena related to this category of time varying multiple-input/multiple output systems.publisher: Elsevier articletitle: An on-line time dependent Parametric Model order reduction scheme with focus on dynamic stress recovery journaltitle: Computer Methods in Applied Mechanics and Engineering articlelink: http://dx.doi.org/10.1016/j.cma.2013.09.021 content_type: article copyright: Copyright © 2013 Elsevier B.V. All rights reserved.status: publishe
T. Tamarozzi - One of the best experts on this subject based on the ideXlab platform.
-
An on-line time dependent Parametric Model order reduction scheme with focus on dynamic stress recovery
Computer Methods in Applied Mechanics and Engineering, 2014Co-Authors: T. Tamarozzi, G.h.k. Heirman, Wim DesmetAbstract:In view of the tendency towards ever lighter and more powerful machines and even shorter design cycles, it becomes essential to have virtual prototyping tools that allow for fast and reliable numerical simulations. Current state-of-the-art structural dynamics and flexible multibody simulation techniques usually involve the solution of matrix systems with thousands to millions of variables. Model order reduction schemes are used to keep computational effort affordable at the expense of a minimal loss of accuracy. These techniques typically face difficulties with systems in which flexible bodies can be loaded in many degrees of freedom and rarely allow for accurate local stress and strain evaluation. The present work proposes to address both issues for the particular but frequent case of moving loads or boundary conditions. This behavior is found in most of the contact problems and systems that include sliding components for which many loading or boundary locations are possible but only a few of them are active at a certain moment in time. The proposed scheme exploits a reduction vector space that continuously varies in time by means of a Parametric definition of the external load position. Contrary to the majority of the Parametric Model order reduction schemes that allow mainly for quasi-static Parametric variations, the proposed approach can be used efficiently for time simulation of dynamically varying Parametric Models. This is achieved by considering the implicit time dependency of the reduction vector space using Galerkin projections or alternatively by direct substitution of the reduced kinetic energy, potential energy and generalized forces in the Lagrange equations. It is shown, by developing a consistent mathematical framework, that the price to pay for the very compact reduction space obtained is the evaluation of some extra terms in the equations of motion. Numerical examples are used to assess the accuracy of the proposed method. Results show the potential of this strategy with particular focus on displacement and stress fields and furthermore highlight its real-time potential. Moreover the developed framework together with the numerical results allow for a deeper physical understanding of the complex phenomena related to this category of time varying multiple-input/multiple output systems.
G.h.k. Heirman - One of the best experts on this subject based on the ideXlab platform.
-
An on-line time dependent Parametric Model order reduction scheme with focus on dynamic stress recovery
Computer Methods in Applied Mechanics and Engineering, 2014Co-Authors: T. Tamarozzi, G.h.k. Heirman, Wim DesmetAbstract:In view of the tendency towards ever lighter and more powerful machines and even shorter design cycles, it becomes essential to have virtual prototyping tools that allow for fast and reliable numerical simulations. Current state-of-the-art structural dynamics and flexible multibody simulation techniques usually involve the solution of matrix systems with thousands to millions of variables. Model order reduction schemes are used to keep computational effort affordable at the expense of a minimal loss of accuracy. These techniques typically face difficulties with systems in which flexible bodies can be loaded in many degrees of freedom and rarely allow for accurate local stress and strain evaluation. The present work proposes to address both issues for the particular but frequent case of moving loads or boundary conditions. This behavior is found in most of the contact problems and systems that include sliding components for which many loading or boundary locations are possible but only a few of them are active at a certain moment in time. The proposed scheme exploits a reduction vector space that continuously varies in time by means of a Parametric definition of the external load position. Contrary to the majority of the Parametric Model order reduction schemes that allow mainly for quasi-static Parametric variations, the proposed approach can be used efficiently for time simulation of dynamically varying Parametric Models. This is achieved by considering the implicit time dependency of the reduction vector space using Galerkin projections or alternatively by direct substitution of the reduced kinetic energy, potential energy and generalized forces in the Lagrange equations. It is shown, by developing a consistent mathematical framework, that the price to pay for the very compact reduction space obtained is the evaluation of some extra terms in the equations of motion. Numerical examples are used to assess the accuracy of the proposed method. Results show the potential of this strategy with particular focus on displacement and stress fields and furthermore highlight its real-time potential. Moreover the developed framework together with the numerical results allow for a deeper physical understanding of the complex phenomena related to this category of time varying multiple-input/multiple output systems.
-
An on-line time dependent Parametric Model order reduction scheme with focus on dynamic stress recovery
'Elsevier BV', 2014Co-Authors: Tamarozzi Tommaso, G.h.k. Heirman, Desmet WimAbstract:In view of the tendency towards ever lighter and more powerful machines and even shorter design cycles, it becomes essential to have virtual prototyping tools that allow for fast and reliable numerical simulations. Current state-of-the-art structural dynamics and flexible multibody simulation techniques usually involve the solution of matrix systems with thousands to millions of variables. Model order reduction schemes are used to keep computational effort affordable at the expense of a minimal loss of accuracy. These techniques typically face difficulties with systems in which flexible bodies can be loaded in many degrees of freedom and rarely allow for accurate local stress and strain evaluation. The present work proposes to address both issues for the particular but frequent case of moving loads or boundary conditions. This behavior is found in most of the contact problems and systems that include sliding components for which many loading or boundary locations are possible but only a few of them are active at a certain moment in time. The proposed scheme exploits a reduction vector space that continuously varies in time by means of a Parametric definition of the external load position. Contrary to the majority of the Parametric Model order reduction schemes that allow mainly for quasi-static Parametric variations, the proposed approach can be used efficiently for time simulation of dynamically varying Parametric Models. This is achieved by considering the implicit time dependency of the reduction vector space using Galerkin projections or alternatively by direct substitution of the reduced kinetic energy, potential energy and generalized forces in the Lagrange equations. It is shown, by developing a consistent mathematical framework, that the price to pay for the very compact reduction space obtained is the evaluation of some extra terms in the equations of motion. Numerical examples are used to assess the accuracy of the proposed method. Results show the potential of this strategy with particular focus on displacement and stress fields and furthermore highlight its real-time potential. Moreover the developed framework together with the numerical results allow for a deeper physical understanding of the complex phenomena related to this category of time varying multiple-input/multiple output systems.publisher: Elsevier articletitle: An on-line time dependent Parametric Model order reduction scheme with focus on dynamic stress recovery journaltitle: Computer Methods in Applied Mechanics and Engineering articlelink: http://dx.doi.org/10.1016/j.cma.2013.09.021 content_type: article copyright: Copyright © 2013 Elsevier B.V. All rights reserved.status: publishe
Junghwan Chang - One of the best experts on this subject based on the ideXlab platform.
-
design and Parametric study of the magnetic sensor for position detection in linear motor based on nonlinear Parametric Model order reduction
Sensors, 2017Co-Authors: Sarbajit Paul, Junghwan ChangAbstract:This paper presents a design approach for a magnetic sensor module to detect mover position using the proper orthogonal decomposition-dynamic mode decomposition (POD-DMD)-based nonlinear Parametric Model order reduction (PMOR). The parameterization of the sensor module is achieved by using the multipolar moment matching method. Several geometric variables of the sensor module are considered while developing the Parametric study. The operation of the sensor module is based on the principle of the airgap flux density distribution detection by the Hall Effect IC. Therefore, the design objective is to achieve a peak flux density (PFD) greater than 0.1 T and total harmonic distortion (THD) less than 3%. To fulfill the constraint conditions, the specifications for the sensor module is achieved by using POD-DMD based reduced Model. The POD-DMD based reduced Model provides a platform to analyze the high number of design Models very fast, with less computational burden. Finally, with the final specifications, the experimental prototype is designed and tested. Two different modes, 90° and 120° modes respectively are used to obtain the position information of the linear motor mover. The position information thus obtained are compared with that of the linear scale data, used as a reference signal. The position information obtained using the 120° mode has a standard deviation of 0.10 mm from the reference linear scale signal, whereas the 90° mode position signal shows a deviation of 0.23 mm from the reference. The deviation in the output arises due to the mechanical tolerances introduced into the specification during the manufacturing process. This provides a scope for coupling the reliability based design optimization in the design process as a future extension.