References of "Golinval, Jean-Claude"
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See detailPropagation of material and surface profile uncertainties on MEMS micro-resonators using a stochastic second-order computational multi-scale approach
Lucas, Vincent ULg; Golinval, Jean-Claude ULg; Voicu, Rodica et al

in International Journal for Numerical Methods in Engineering (in press)

This paper aims at accounting for the uncertainties due to material structure and surface topology of microbeams in a stochastic multiscale model. For micro-resonators made of anisotropic polycrystalline ... [more ▼]

This paper aims at accounting for the uncertainties due to material structure and surface topology of microbeams in a stochastic multiscale model. For micro-resonators made of anisotropic polycrystalline materials, micro-scale uncertainties are due to the grain size, grain orientation, and to the surface profile. First, microscale realizations of stochastic volume elements (SVEs) are obtained based on experimental measurements. To account for the surface roughness, the SVEs are defined as a volume element having the same thickness as the MEMS, with a view to the use of a plate model at the structural scale. The uncertainties are then propagated up to an intermediate scale, the meso-scale, through a second-order homogenization procedure.From the meso-scale plate resultant material property realizations, a spatially correlated random field of the in plane, out of plane, and cross resultant material tensors can be characterized. Owing to this characterized random field, realizations of MEMS-scale problems can be defined on a plate finite element model. Samples of the macro-scale quantity of interest can then be computed by relying on a Monte-Carlo simulation procedure. As a case study, the resonance frequency of MEMS micro-beams is investigated for different uncertainty cases, such as grain preferred orientations and surface roughness effects. [less ▲]

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See detailA computational stochastic multiscale methodology for MEMS structures involving adhesive contact
Hoang Truong, Vinh ULg; Wu, Ling ULg; Paquay, Stéphane et al

in Tribology International (in press)

This work aims at developing a computational stochastic multiscale methodology to quantify the uncertainties of the adhesive contact problems due to capillary effects and van der Waals forces in MEMS ... [more ▼]

This work aims at developing a computational stochastic multiscale methodology to quantify the uncertainties of the adhesive contact problems due to capillary effects and van der Waals forces in MEMS. Because the magnitudes of the adhesive forces strongly depend on the surface interaction distances, which in turn evolve with the roughness of the contacting surfaces, the involved structural behaviors suffer from a scatter. To numerically predict the probabilistic behaviors of structures involving adhesion, the proposed method introduces stochastic meso-scale random apparent contact forces which can be integrated into a stochastic finite element model. Because the evaluation of their realizations is expensive, a generator for the random apparent contact force using the polynomial chaos expansion is constructed in an efficient way. [less ▲]

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See detailIdentification of non-stationary dynamical systems using multivariate ARMA models
Bertha, Mathieu ULg; Golinval, Jean-Claude ULg

in Mechanical Systems and Signal Processing (2017), 88

This paper is concerned by the modal identification of time-varying mechanical systems. Based on previous works about autoregressive moving average models in vector form (ARMAV) for the modal ... [more ▼]

This paper is concerned by the modal identification of time-varying mechanical systems. Based on previous works about autoregressive moving average models in vector form (ARMAV) for the modal identification of linear time invariant systems, and time-varying autoregressive moving average models (TV-ARMA) for the identification of nonstationary systems, a time-varying ARMAV (TV-ARMAV) model is presented for the multivariate identification of time-varying systems. It results in the identification of not only the time-varying poles of the system but also of its respective time-varying mode shapes. The method is applied on a time-varying structure composed of a beam on which a mass is moving. [less ▲]

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See detailA Stochastic Multi-scale Model For Predicting MEMS Stiction Failure
Hoang Truong, Vinh ULg; Wu, Ling ULg; Paquay, Stéphane et al

in Starman, La Vern; Hay, Jennifer; Karanjgaokar, Nikhil (Eds.) Micro and Nanomechanics, Volume 5: Proceedings of the 2016 Annual Conference on Experimental and Applied Mechanics (2017)

Adhesion is an important phenomenon in the context of MEMS for which the surface forces become dominant in comparison with the body forces. Because the magnitudes of the adhesive forces strongly depend on ... [more ▼]

Adhesion is an important phenomenon in the context of MEMS for which the surface forces become dominant in comparison with the body forces. Because the magnitudes of the adhesive forces strongly depend on the surface interaction distances, which in turn evolve with the roughness of the contacting surfaces, the adhesive forces cannot be determined in a deterministic way. To quantify the uncertainties on the structural stiction behavior of a MEMS, this work proposes a “stochastic multi-scale methodology”. The key ingredient of the method is the evaluation of the random meso-scale apparent contact forces, which homogenize the effect of the nano-scale roughness and are integrated into a numerical model of the studied structure as a random contact law. To obtain the probabilistic behavior at the structural MEMS scale, a direct method needs to evaluate explicitly the meso-scale apparent contact forces in a concurrent way with the stochastic multi-scale approach. To reduce the computational cost, a stochastic model is constructed to generate the random meso-scale apparent contact forces. To this end, the apparent contact forces are parameterized by a vector of parameters before applying a polynomial chaos expansion in order to construct a mathematical model representing the probability of the random parameters vector. The problem of micro-beam stiction is then studied in a probabilistic way. [less ▲]

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See detailA Stochastic Multi-Scale Approach for the Modeling of Thermo-Elastic Damping in Micro-Resonators
Wu, Ling ULg; Lucas, Vincent ULg; Nguyen, Van Dung ULg et al

in Computer Methods in Applied Mechanics & Engineering (2016), 310

The aim of this work is to study the thermo-elastic quality factor (Q) of micro-resonators with a stochastic multi-scale approach. In the design of high-Q micro-resonators, thermo-elastic damping is one ... [more ▼]

The aim of this work is to study the thermo-elastic quality factor (Q) of micro-resonators with a stochastic multi-scale approach. In the design of high-Q micro-resonators, thermo-elastic damping is one of the major dissipation mechanisms, which may have detrimental effects on the quality factor, and has to be predicted accurately. Since material uncertainties are inherent to and unavoidable in micro-electromechanical systems (MEMS), the effects of those variations have to be considered in the modeling in order to ensure the required MEMS performance. To this end, a coupled thermo-mechanical stochastic multi-scale approach is developed in this paper. Thermo-mechanical micro-models of polycrystalline materials are used to represent micro-structure realizations. A computational homogenization procedure is then applied on these statistical volume elements to obtain the stochastic characterizations of the elasticity tensor, thermal expansion, and conductivity tensors at the meso-scale. Spatially correlated meso-scale random fields can thus be generated to represent the stochastic behavior of the homogenized material properties. Finally, the distribution of the thermo-elastic quality factor of MEMS resonators is studied through a stochastic finite element method using as input the generated stochastic random field. [less ▲]

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See detailProbabilistic prediction of the quality factor of micro-resonator using a stochastic thermo-mechanical multi-scale approach
Wu, Ling ULg; Lucas, Vincent ULg; Golinval, Jean-Claude ULg et al

Conference (2016, September 07)

As the size of the device is only one or two orders of magnitude higher than the size of the grains, the structural properties, such as the thermo-elastic quality factor (Q), of micro-electro-mechanical ... [more ▼]

As the size of the device is only one or two orders of magnitude higher than the size of the grains, the structural properties, such as the thermo-elastic quality factor (Q), of micro-electro-mechanical systems (MEMS) made of poly-crystalline materials exhibit a scatter, due to the existing randomness in the grain size, grain orientation, surface roughness... In order to predict the probabilistic behavior of micro-resonators, the authors extend herein a previously developed stochastic 3-scale approach [1] to the case of thermoelastic damping [2]. In this method, stochastic volume elements (SVEs) [3] are defined by considering random grain orientations in a tessellation. For each SVE realization, the mesoscopic apparent elasticity tensor, thermal conductivity tensor, and thermal dilatation tensor can be obtained using thermo-mechanical computational homogenization theory [4]. The extracted mesoscopic apparent properties tensors can then be used to define a spatially correlated meso-scale random field, which is in turn used as input for stochastic finite element simulations. As a result, the probabilistic distribution of the quality factor of micro-resonator can be extracted by considering Monte-Carlo simulations of coarse-meshed micro-resonators, accounting implicitly for the random micro-structure of the poly-silicon material. [1] V. Lucas, J.-C. Golinval, S. Paquay, V.-D. Nguyen, L. Noels, L. Wu, A stochastic computational multiscale approach; Application to MEMS resonators. Computer Methods in Applied Mechanics and Engineering, 294, 141-167, 2015. [2] L. Wu, V. Lucas, V.-D. Nguyen, J.-C. Golinval, S. Paquay, L. Noels, A Stochastic Multiscale Approach for the Modeling of Thermoelastic Damping in Micro-Resonators. Submitted. [3] M. Ostoja-Starzewski, X.Wang, Stochastic finite elements as a bridge between random material microstructure and global response, Computer Methods in Applied Mechanics and Engineering, 168, 35--49, 1999. [4] I. Özdemir, W. A. M. Brekelmans, M. G. D. Geers, Computational homogenization for heat conduction in heterogeneous solids, International Journal for Numerical Methods in Engineering 73, 185-204, 2008. [less ▲]

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See detailA stochastic 3-Scale approach to study the thermomechanical damping of MEMS
Wu, Ling ULg; Lucas, Vincent ULg; Nguyen, Van Dung ULg et al

Scientific conference (2016, June 20)

A stochastic 3-scale approach is developed to study the thermo-elastic quality factor (Q) of micro-electromechanical systems (MEMS) resonators. Thermo-elastic damping is one of the major dissipation ... [more ▼]

A stochastic 3-scale approach is developed to study the thermo-elastic quality factor (Q) of micro-electromechanical systems (MEMS) resonators. Thermo-elastic damping is one of the major dissipation mechanisms in high-Q micro-resonators, which may have detrimental effects on the quality factor, and has to be predicted accurately. Since material uncertainties are inherent to and unavoidable in MEMS, the effects of those variations have to be considered in the numerical models. To this end, a coupled thermo-mechanical stochastic 3-scale approach is considered. Thermo-mechanical micro-models of poly-silicon materials are used to represent micro-structure realizations. A computational stochastic homogenization procedure is then applied on these statistical volume elements to obtain the probabilistic distribution of the elasticity tensor, thermal expansion and conductivity tensors at the meso-scale. Spatially correlated meso-scale random fields are then generated in order to represent the probabilistic behavior of the homogenized material properties, feeding macro-scale stochastic finite element simulations. [less ▲]

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See detailMulti-scale stochastic study of the grain orientation and roughness effects on polycrystalline thin structures
Lucas, Vincent ULg; Wu, Ling ULg; Golinval, Jean-Claude ULg et al

Conference (2016, June 09)

When studying micro-electro-mechanical systems (MEMS) made of poly-crystalline materials, as the size of the device is only one or two orders of magnitude higher than the size of the the grains, the ... [more ▼]

When studying micro-electro-mechanical systems (MEMS) made of poly-crystalline materials, as the size of the device is only one or two orders of magnitude higher than the size of the the grains, the structural properties exhibit a scatter at the macro-scale due to the existing randomness in the grain size, grain orientation, surface roughness... In order to predict the probabilistic behavior at the structural scale, the authors have recently developed a stochastic 3-scale approach [1]. In this method, stochastic volume elements (SVEs) [2] are defined by considering random grain orientations in a tessellation. For each SVE realization, a meso-scopic apparent material tensor can be obtained using the computational homogenization theory. The extracted meso-scopic apparent material tensors can then be used to defined a spatially correlated meso-scale random field, which is in turn used as input for stochastic finite element simulations. In this work we intend to study the effect of different material-related uncertainty sources on the structural behavior of vibrating micro-devices manufactured using low pressure chemical vapor deposition. First, the effect of preferred grain orientation on vibrating micro-structures is assessed. To this end, SVEs are generated so that their grain orientation distributions follow XRD measurements. Second, the effect of the roughness of the vibrating micro-structures is studied. Toward this end, SVEs, whose rough surface statistical properties follow AFM measurements, are generated. A second-order computational homogenization [3] applied on the different SVE realizations allows defining a meso-scale random field of the in-plane and out-of-plane meso-scale shell properties. Stochastic shell finite elements can then be applied to predict the MEMS probabilistic behavior. [1] V. Lucas, et al., Comp. Meth. in Appl. Mech. and Eng., 294, 141-167, 2015 [2] M. Ostoja-Starzewski, X.Wang, Comp. Meth. in Appl. Mech. and Eng., 168, 35–49, 1999 [3] E.W.C. Coenen, V. Kouznetsova, M.G.D. Geers. Int. J. for Numer. Meth. in Eng., 83, 1180–1205, 2010. [less ▲]

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See detailA Stochastic Multi-scale Model For Predicting MEMS Stiction Failure
Hoang Truong, Vinh ULg; Paquay, Stéphane; Golinval, Jean-Claude ULg et al

in Proceedings of the SEM XIII International Congress and Exposition on Experimental and Applied Mechanics. (SEMXIII 2016) (2016, June 06)

Adhesion is an important phenomenon in the context of MEMS for which the surface forces become dominant in comparison with the body forces. Because the magnitudes of the adhesive forces strongly depend on ... [more ▼]

Adhesion is an important phenomenon in the context of MEMS for which the surface forces become dominant in comparison with the body forces. Because the magnitudes of the adhesive forces strongly depend on the surface interaction distances, which in turn evolve with the roughness of the contacting surfaces, the adhesive forces cannot be determined in a deterministic way. To quantify the uncertainties on the structural stiction behavior of a MEMS, this work proposes a “stochastic multi-scale methodology”. The key ingredient of the method is the evaluation of the random meso-scale apparent contact forces, which homogenize the effect of the nano-scale roughness and are integrated into a numerical model of the studied structure as a random contact law. To obtain the probabilistic behavior at the structural MEMS scale, a direct method needs to evaluate explicitly the meso-scale apparent contact forces in a concurrent way with the stochastic multi-scale approach. To reduce the computational cost, a stochastic model is constructed to generate the random meso-scale apparent contact forces. To this end, the apparent contact forces are parameterized by a vector of parameters before applying a polynomial chaos expansion in order to construct a mathematical model representing the probability of the random parameters vector. The problem of miro-beam stiction is then studied in a probabilistic way. [less ▲]

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See detailInfluence of the inter‐stage coupling flexibility on the dynamics of multi‐stage rotors
Nyssen, Florence ULg; Golinval, Jean-Claude ULg

in Proceedings of the ASME Turbo Expo 2016 (2016, June)

In this work, a characterization of the inter-stage coupling in a one-piece multi-stage bladed structure is performed. More particularly, the effect of the inter-stage coupling flexibility on the mode ... [more ▼]

In this work, a characterization of the inter-stage coupling in a one-piece multi-stage bladed structure is performed. More particularly, the effect of the inter-stage coupling flexibility on the mode-shapes is evaluated. To this purpose, the MAC matrix between the mono-stage and multi-stage modes is computed for different drum Young’s modulus of the inter-stage coupling. In parallel, the strain energy located in the blades and in the connecting structure is computed for different levels of inter-stage coupling. This enables to establish a criterion to determine when a multi-stage finite element analysis is necessary instead of only computing the different mono-stage models separately. This criterion is based on the localization of the energy in the structure. Numerical analyses are performed on a two-stages academic bladed structure. [less ▲]

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See detailProbabilistic prediction of the quality factor of micro-resonator using a stochastic thermo-mechanical multi-scale approach
Wu, Ling ULg; Lucas, Vincent ULg; Nguyen, Van Dung ULg et al

Scientific conference (2016, May 23)

As the size of the device is only one or two orders of magnitude higher than the size of the grains, the structural properties, such as the thermo-elastic quality factor (Q), of micro-electro-mechanical ... [more ▼]

As the size of the device is only one or two orders of magnitude higher than the size of the grains, the structural properties, such as the thermo-elastic quality factor (Q), of micro-electro-mechanical systems (MEMS) made of poly- crystalline materials exhibit a scatter, due to the existing randomness in the grain size, grain orientation, surface roughness. In order to predict the probabilistic behavior of micro-resonators, the authors extend herein a previously developed stochastic 3-scale approach to the case of thermoelastic damping. In this method, stochastic volume elements (SVEs) are defined by considering random grain orientations in a tessellation. For each SVE realization, the mesoscopic apparent elasticity tensor, thermal conductivity tensor, and thermal dilatation tensor can be obtained using thermo-mechanical computational homogenization theory. The extracted mesoscopic apparent properties tensors can then be used to define a spatially correlated mesoscale random field, which is in turn used as input for stochastic finite element simulations. As a result, the probabilistic distribution of the quality factor of micro-resonator can be extracted by considering Monte-Carlo simulations of coarse-meshed micro-resonators, accounting implicitly for the random microstructure of the poly-silicon material. [less ▲]

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See detailA Study Of Dry Stiction Phenomenon In MEMS Using A Computational Stochastic Multi-scale Methodology
Hoang Truong, Vinh ULg; Wu, Ling ULg; Paquay, Stéphane et al

in EuroSimE 2016 in Montpellier (2016, April 19)

This work studies the uncertainties of the adhesive contact problems for reduced size structures, e.g. the stiction failure of microelectromechanical systems (MEMS). In MEMS, because of the large surface ... [more ▼]

This work studies the uncertainties of the adhesive contact problems for reduced size structures, e.g. the stiction failure of microelectromechanical systems (MEMS). In MEMS, because of the large surface to volume ratio, the surfaces forces, such as van der Waals forces and capillary forces, are dominant in comparison with the body forces. As these force magnitudes strongly depend on the contact distance, when the two contacting surfaces are rough, the contact distances vary, and the physical contact areas are limited at the highest asperities of the contacting surfaces. Therefore, the adhesive contact forces between two rough surfaces can suffer from a scatter, and the involved structural behaviors can be indeterministic. To numerically predict the probability behaviors of structures involving adhesion in dry environments, in this paper, a computational stochastic model-based multi-scale method developed by the authors is applied. The effects of van der Waals is studied and compared with experimental data as well as with the effects of capillary forces. [less ▲]

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See detailDynamic calibration of piezoelectric transducers for ballistic high-pressure measurement
Elkarous, Lamine ULg; Robbe, Cyril; Pirlot, Marc et al

in International Journal of Metrology and Quality Engineering (2016)

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See detailExperimental modal identification of mistuning in an academic two-stage drum
Nyssen, Florence ULg; Epureanu, Bogdan; Golinval, Jean-Claude ULg

in Mechanical Systems & Signal Processing (2016)

Various assumptions are often made to model turbomachinery bladed assemblies. In particular, the cyclic symmetry of single rotor stages, and dynamically independence of isolated rotor stages are ... [more ▼]

Various assumptions are often made to model turbomachinery bladed assemblies. In particular, the cyclic symmetry of single rotor stages, and dynamically independence of isolated rotor stages are frequently used. The first assumption enables a drastic reduction of the required computational resources by considering only one sector instead of the entire assembly to model and analyze the dynamic behavior of the complete structure. However, small random blade-to-blade structural variations, known as mistuning, exist due to manufacturing tolerances, etc. and significantly affect the dynamic behavior of bladed disks. The second assumption also reduces the needed computational resources and time. However, ignore inter-stage coupling does not always describe accurately the disk or drum flexibility especially at the inter-stage boundaries. In this work, the component mode mistuning method is used for multi-stage assemblies to create a mistuning identification approach. An experimental modal analysis is performed on a two-stage monobloc academic bladed drum. The frequency response function is measured using a base excitation with an electrodynamic shaker and one measurement point per blade of each stage is used. The approach is used to identify mistuning in a multi-stage rotor. Numerical and experimental results are presented. Results show that the proposed approach is effective even for modes which are multi-stage. [less ▲]

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See detailTime-Varying Modal Parameters Identification in the Modal Domain
Bertha, Mathieu ULg; Golinval, Jean-Claude ULg

in Proceedings of ISMA 2016 - International Conference on Noise and Vibration Engineering (2016)

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See detailMultivariate ARMA Based Modal Identification of a Time-varying Beam
Bertha, Mathieu ULg; Golinval, Jean-Claude ULg

in Proceedings of the International Modal Analysis Conference (IMAC) XXXIV (2016)

The present paper addresses the problem of modal identification of time-varying systems. The identification is based on a multivariate autoregressive moving-average model in which the time variability of ... [more ▼]

The present paper addresses the problem of modal identification of time-varying systems. The identification is based on a multivariate autoregressive moving-average model in which the time variability of the system is caught using a basis functions approach. In this approach, the time-varying regressive coefficients in the model are expended in the chosen basis functions and only the projection coefficients have to be identified. In that way, the initial time-varying problem then becomes a time-invariant one that can be solved. Because a multivariate model is used, in addition to the time-varying poles, the time-varying mode shapes may be identified too. The method is first presented and then applied on an experimental demonstration structure. The experimental structure consists of a supported beam on which a mass is travelling. The mass is chosen sufficiently large to have a significant influence on the dynamics of the primary system. This kind of problem is a classical example commonly used by many authors to test time-varying identification methods. [less ▲]

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See detailA probabilistic model for predicting the uncertainties of the humid stiction phenomenon on hard materials
Hoang Truong, Vinh ULg; Wu, Ling ULg; Paquay, Stéphane et al

in Journal of Computational & Applied Mathematics (2015), 289

Stiction is a major failure in microelectromechanical system (MEMS) devices in which two contacting surfaces can remain stuck together because of the adhesive forces. Due to the difference between the ... [more ▼]

Stiction is a major failure in microelectromechanical system (MEMS) devices in which two contacting surfaces can remain stuck together because of the adhesive forces. Due to the difference between the surfaces roughness and the adhesive force range, the real contact areas are usually smaller than the apparent one, resulting in a scatter in the adhesive forces. Consequently, the stiction is an uncertain phenomenon. In this work, we develop a probabilistic model to predict the uncertainties of stiction due to the capillary forces acting on stiff materials. This model contains two levels: at the deterministic level, the model can predict the pull-out adhesive contact forces for a given surface topology; at the probabilistic level, the model generates independent identically distributed surfaces on which the deterministic solution can be applied to evaluate the uncertainties related to the stiction phenomenon. [less ▲]

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See detailA stochastic computational multiscale approach; Application to MEMS resonators
Lucas, Vincent ULg; Golinval, Jean-Claude ULg; Paquay, Stéphane et al

in Computer Methods in Applied Mechanics & Engineering (2015), 294

The aim of this work is to develop a stochastic multiscale model for polycrystalline materials, which accounts for the uncertainties in the micro-structure. At the finest scale, we model the micro ... [more ▼]

The aim of this work is to develop a stochastic multiscale model for polycrystalline materials, which accounts for the uncertainties in the micro-structure. At the finest scale, we model the micro-structure using a random Voronoi tessellation, each grain being assigned a random orientation. Then, we apply a computational homogenization procedure on statistical volume elements to obtain a stochastic characterization of the elasticity tensor at the meso-scale. A random field of the meso-scale elasticity tensor can then be generated based on the information obtained from the SVE simulations. Finally, using a stochastic finite element method, these meso-scale uncertainties are propagated to the coarser scale. As an illustration we study the resonance frequencies of MEMS micro-beams made of poly-silicon materials, and we show that the stochastic multiscale approach predicts results in agreement with a Monte Carlo analysis applied directly on the fine finite-element model, i.e. with an explicit discretization of the grains. [less ▲]

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See detailA probabilistic multi-scale model for polycrystalline MEMS resonators
Lucas, Vincent ULg; Wu, Ling ULg; Paquay, Stéphane et al

Conference (2015, July 09)

The size of micro-electro-mechanical systems (MEMS) is only one or two orders of magnitude higher than the size of their micro-structure, i.e. their grain size. As a result, the structural properties ... [more ▼]

The size of micro-electro-mechanical systems (MEMS) is only one or two orders of magnitude higher than the size of their micro-structure, i.e. their grain size. As a result, the structural properties exhibit a scatter. As an example we study the beam resonator illustrated in Fig. 1(a), made of poly-silicon material, in which each grain has a random orientation. Solving the problem with a full direct numerical simulation combined to a Monte-Carlo method allows the probability density function to be computed as illustrated in Fig. 1(b). However this methodology is computationally expensive due to the number of degrees of freedom required to study one sample, motivating the development of a non-deterministic 3-scale approach [3]. In a multiscale approach, at each macro-point of the macro-structure, the resolution of a microscale boundary value problem relates the macro-stress tensor to the macro-strain tensor. At the micro-level, the macro-point is viewed as the center of a Representative Volume Element (RVE). The resolution of the micro-scale boundary problem can be performed using finite-element simulations, as in the computational homogenization framework, e.g. [2]. However, to be representative, the micro-volume-element should have a size much bigger than the microstructure size. In the context of the MEMS resonator, this representativity is lost and Statistical Volume Elements (SVE) are considered. These SVEs are generated under the form of a Voronoi tessellation with a random orientation for each silicon grain. Hence, a Monte-Carlo procedure combined with a homogenization technique allows a distribution of the material tensor at the meso-scale to be estimated. The correlation between the meso-scale material tensors of two SVEs separated by a given distance can also be evaluated. A generator at the meso-scale based on the spectral method [4] is implemented. The generator [3] accounts for a lower bound [1] of the meso-scale material tensor in order to ensure the existence of the second-order moment of the Frobenius norm of the generated material tensor inverse [5]. Using the random meso-scale field obtained with the meso-scale generator, which accounts for the spatial correlation, a Monte-Carlo method can be used at the macro-scale to predict the probabilistic behavior of the MEMS resonator. [less ▲]

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