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http://hdl.handle.net/10985/23082
Extended mean-field homogenization of unidirectional piezoelectric nanocomposites with generalized Gurtin-Murdoch interfaces
CHEN, Qiang; CHATZIGEORGIOU, George; MERAGHNI, Fodil
This paper presents for the first time an extended Mori-Tanaka approach aimed at identifying the little-explored piezoelectric response of unidirectional nanoporous composites with energetic surfaces. The interface is simulated using the generalized Gurtin-Murdoch coherent interface model considering nonvanishing in-plane surface stress and surface electric displacement. The analytical solutions for Eshelby’s inhomogeneity problems are obtained by solving four systems of equations, generated from the known macroscopic electromechanical loading conditions. The dilute concentration tensors for the fiber and energetic surface are evaluated exactly for coupled electromechanical fields, which are then utilized in the extended multiphysics Mori-Tanaka homogenization scheme. The reliability and accuracy of the extended theory are demonstrated through an extensive comparison with the predictions of the composite cylinder assemblage (CCA), the generalized self-consistent method (GSCM), as well as the finite-element (FE) homogenization technique. New results generated in this work demonstrate that, except for the transverse shear
modulus, the extended Mori-Tanaka, CCA, and FE provide indistinguishable results under axisymmetric, axial shear, and electric loading, even at high volume fractions and small pore sizes where the surface piezoelectric effects are significant.
Thu, 01 Dec 2022 00:00:00 GMThttp://hdl.handle.net/10985/230822022-12-01T00:00:00ZCHEN, QiangCHATZIGEORGIOU, GeorgeMERAGHNI, FodilThis paper presents for the first time an extended Mori-Tanaka approach aimed at identifying the little-explored piezoelectric response of unidirectional nanoporous composites with energetic surfaces. The interface is simulated using the generalized Gurtin-Murdoch coherent interface model considering nonvanishing in-plane surface stress and surface electric displacement. The analytical solutions for Eshelby’s inhomogeneity problems are obtained by solving four systems of equations, generated from the known macroscopic electromechanical loading conditions. The dilute concentration tensors for the fiber and energetic surface are evaluated exactly for coupled electromechanical fields, which are then utilized in the extended multiphysics Mori-Tanaka homogenization scheme. The reliability and accuracy of the extended theory are demonstrated through an extensive comparison with the predictions of the composite cylinder assemblage (CCA), the generalized self-consistent method (GSCM), as well as the finite-element (FE) homogenization technique. New results generated in this work demonstrate that, except for the transverse shear
modulus, the extended Mori-Tanaka, CCA, and FE provide indistinguishable results under axisymmetric, axial shear, and electric loading, even at high volume fractions and small pore sizes where the surface piezoelectric effects are significant.Combination of mean-field micromechanics and cycle jump technique for cyclic response of PA66/GF composites with viscoelastic–viscoplastic and damage mechanisms
http://hdl.handle.net/10985/23081
Combination of mean-field micromechanics and cycle jump technique for cyclic response of PA66/GF composites with viscoelastic–viscoplastic and damage mechanisms
CHEN, Qiang; CHATZIGEORGIOU, George; ROBERT, Gilles; MERAGHNI, Fodil
An accelerated micromechanics framework based on the extended Mori–Tanaka transformation field analysis (TFA) and cycle jump technique is proposed to predict the homogenized response of short glass fiber-reinforced polyamide 66 composites (PA66/GF) under a large number of loading cycles (> 100,000 cycles). The extended theory accounts for microscopic viscoelastic–viscoplastic and damage mechanisms, and realistic microstructures induced by the injection molding process. Toward this end, a number of training cycles are first conducted using the extended Mori–Tanaka TFA to obtain the global evolution functions of material state-dependent variables (SDVs) for each phase. These SDVs are extrapolated linearly to a certain jump length with the help of global evolution functions such that direct numerical simulation of the cycles during this interval can be skipped, leading to a large computational cost reduction. After the cycle jump, a set of complete cycles are performed based on the extrapolated SDVs using the Mori–Tanaka TFA simulation to re-establish the global evolution functions. The implementation of the cycle jump procedure is facilitated by introducing an extrapolation control function to allow adaptive jump size control as well as to minimize the extrapolating error. The capabilities of the extended theory with the cycle jump technique have been validated extensively vis-à-vis cycle-by-cycle benchmark calculations under various loading conditions. It has been further verified with the experimental results of actual PA66/GF composites under high-cycle loading beyond which the cycle-by-cycle simulations can achieve.
Sun, 01 Jan 2023 00:00:00 GMThttp://hdl.handle.net/10985/230812023-01-01T00:00:00ZCHEN, QiangCHATZIGEORGIOU, GeorgeROBERT, GillesMERAGHNI, FodilAn accelerated micromechanics framework based on the extended Mori–Tanaka transformation field analysis (TFA) and cycle jump technique is proposed to predict the homogenized response of short glass fiber-reinforced polyamide 66 composites (PA66/GF) under a large number of loading cycles (> 100,000 cycles). The extended theory accounts for microscopic viscoelastic–viscoplastic and damage mechanisms, and realistic microstructures induced by the injection molding process. Toward this end, a number of training cycles are first conducted using the extended Mori–Tanaka TFA to obtain the global evolution functions of material state-dependent variables (SDVs) for each phase. These SDVs are extrapolated linearly to a certain jump length with the help of global evolution functions such that direct numerical simulation of the cycles during this interval can be skipped, leading to a large computational cost reduction. After the cycle jump, a set of complete cycles are performed based on the extrapolated SDVs using the Mori–Tanaka TFA simulation to re-establish the global evolution functions. The implementation of the cycle jump procedure is facilitated by introducing an extrapolation control function to allow adaptive jump size control as well as to minimize the extrapolating error. The capabilities of the extended theory with the cycle jump technique have been validated extensively vis-à-vis cycle-by-cycle benchmark calculations under various loading conditions. It has been further verified with the experimental results of actual PA66/GF composites under high-cycle loading beyond which the cycle-by-cycle simulations can achieve.Fully-coupled electro-magneto-elastic behavior of unidirectional multiphased composites via finite-volume homogenization
http://hdl.handle.net/10985/19876
Fully-coupled electro-magneto-elastic behavior of unidirectional multiphased composites via finite-volume homogenization
CHEN, Qiang; CHEN, Weiqiu; WANG, Guannan
The effective and localized electro-magneto-elastic behavior of periodic unidirectional composites is investigated in this work. Instead of adopting the classical micromechanics models or variational principle-based finite-element (FE) techniques, the finite-volume direct averaging micromechanics (FVDAM) is extended to fulfill this task by incorporating fully-coupled electro-magneto-elastic constitutive relations. Consistent with the mathematical homogenization theories, the mechanical displacements and electric/magnetic potentials are partitioned using two-scale expansion involving the macroscopic and fluctuating contributions. The generalized local stiffness matrices are constructed explicitly by relating the surface-averaged tractions, electric displacements, and magnetic inductions to the surface-averaged mechanical displacements and electric/magnetic potentials, followed which the continuity and periodic boundary conditions are applied. The homogenized coefficients and localized stress, electric/magnetic field distributions are validated extensively against the exact generalized Eshelby solution and an in-house FE program, as well as the experimental measurements, where perfect agreements are observed for all cases. The efficiency and convergence of the proposed multiphysics FVDAM (MFVDAM) are tested by comparing the execution time and localized fields as a function of mesh discretization, with the multiphysics FE (MFEM) results as references. Besides, the MFVDAM is encapsulated into the particle swarm optimization algorithm to deduce the optimal fiber volume fraction at which maximum magnetoelectric coupling effect may occur in the composite system with piezomagnetic ceramics reinforced with piezoelectric unidirectional fibers.
Fri, 01 Jan 2021 00:00:00 GMThttp://hdl.handle.net/10985/198762021-01-01T00:00:00ZCHEN, QiangCHEN, WeiqiuWANG, GuannanThe effective and localized electro-magneto-elastic behavior of periodic unidirectional composites is investigated in this work. Instead of adopting the classical micromechanics models or variational principle-based finite-element (FE) techniques, the finite-volume direct averaging micromechanics (FVDAM) is extended to fulfill this task by incorporating fully-coupled electro-magneto-elastic constitutive relations. Consistent with the mathematical homogenization theories, the mechanical displacements and electric/magnetic potentials are partitioned using two-scale expansion involving the macroscopic and fluctuating contributions. The generalized local stiffness matrices are constructed explicitly by relating the surface-averaged tractions, electric displacements, and magnetic inductions to the surface-averaged mechanical displacements and electric/magnetic potentials, followed which the continuity and periodic boundary conditions are applied. The homogenized coefficients and localized stress, electric/magnetic field distributions are validated extensively against the exact generalized Eshelby solution and an in-house FE program, as well as the experimental measurements, where perfect agreements are observed for all cases. The efficiency and convergence of the proposed multiphysics FVDAM (MFVDAM) are tested by comparing the execution time and localized fields as a function of mesh discretization, with the multiphysics FE (MFEM) results as references. Besides, the MFVDAM is encapsulated into the particle swarm optimization algorithm to deduce the optimal fiber volume fraction at which maximum magnetoelectric coupling effect may occur in the composite system with piezomagnetic ceramics reinforced with piezoelectric unidirectional fibers.Electromechanical response of multilayered piezoelectric BaTiO3/PZT-7A composites with wavy architecture
http://hdl.handle.net/10985/19877
Electromechanical response of multilayered piezoelectric BaTiO3/PZT-7A composites with wavy architecture
TU, Wenqiong; CHEN, Qiang
Electromechanical laminated composites with piezoelectric phases are increasingly being explored as multifunctional materials providing energy conversion between electric and mechanical energies. The current work explores thus-far undocumented combined microstructural effects of amplitude-to-wavelength ratio, volume fraction, poling direction of piezoelectric phases on both the homogenized properties and localized stress/electric field distributions in multilayered configurations under fully coupled electro-mechanical loading. In particular, the Multiphysics Finite-Volume Direct Averaging Micromechanics (FVDAM) and its counterpart, an in-house micromechanical multiphysics finite-element model, are utilized to investigate the homogenized and localized responses of wavy multilayered piezoelectric BaTiO3/PZT-7A architectures. These two methods generate highly agreeable results. Moreover, we critically examine the convergence of the finite-volume and finite element-based approaches via the Average Stress Theorem and Average Electric Displacement Theorem. The comparison shows the finite volume-based approach possesses a better numerical convergence. This study illustrates the FVDAM’s ability toward the analysis and design of engineered multilayered piezoelectric materials with wavy architecture.
Fri, 01 Jan 2021 00:00:00 GMThttp://hdl.handle.net/10985/198772021-01-01T00:00:00ZTU, WenqiongCHEN, QiangElectromechanical laminated composites with piezoelectric phases are increasingly being explored as multifunctional materials providing energy conversion between electric and mechanical energies. The current work explores thus-far undocumented combined microstructural effects of amplitude-to-wavelength ratio, volume fraction, poling direction of piezoelectric phases on both the homogenized properties and localized stress/electric field distributions in multilayered configurations under fully coupled electro-mechanical loading. In particular, the Multiphysics Finite-Volume Direct Averaging Micromechanics (FVDAM) and its counterpart, an in-house micromechanical multiphysics finite-element model, are utilized to investigate the homogenized and localized responses of wavy multilayered piezoelectric BaTiO3/PZT-7A architectures. These two methods generate highly agreeable results. Moreover, we critically examine the convergence of the finite-volume and finite element-based approaches via the Average Stress Theorem and Average Electric Displacement Theorem. The comparison shows the finite volume-based approach possesses a better numerical convergence. This study illustrates the FVDAM’s ability toward the analysis and design of engineered multilayered piezoelectric materials with wavy architecture.Deep learning in heterogeneous materials: Targeting the thermo-mechanical response of unidirectional composites
http://hdl.handle.net/10985/19895
Deep learning in heterogeneous materials: Targeting the thermo-mechanical response of unidirectional composites
CHEN, Qiang; TU, Wenqiong; MA, Meng
In this communication, a multi-task deep learning-driven homogenization scheme is proposed for predicting the effective thermomechanical response of unidirectional composites consisting of a random array of inhomogeneity. Toward this end, 40 000 repeating unit cells (RUCs) comprising an arbitrary number of locally irregular inclusions are generated over a wide range of fiber volume fractions. The finite-volume direct averaging micromechanics is then employed to evaluate the homogenized thermo-mechanical moduli of each RUC. Subsequently, a two-dimensional deep convolution neural network (CNN) is constructed as a surrogate model to extract the statistical correlations between the RUC geometrical information and the corresponding homogenized response. The RUC images together with their homogenized moduli are divided into two datasets in a ratio of 9:1 with the former part used for training the CNN model and the latter part used for verification. The results presented in this contribution demonstrate that the deep CNN predictions exhibit remarkable correlations with the theoretical values generated by the finite-volume micromechanics, with a maximum relative prediction error of less than 8%, providing good support for the data-based homogenization approach.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10985/198952020-01-01T00:00:00ZCHEN, QiangTU, WenqiongMA, MengIn this communication, a multi-task deep learning-driven homogenization scheme is proposed for predicting the effective thermomechanical response of unidirectional composites consisting of a random array of inhomogeneity. Toward this end, 40 000 repeating unit cells (RUCs) comprising an arbitrary number of locally irregular inclusions are generated over a wide range of fiber volume fractions. The finite-volume direct averaging micromechanics is then employed to evaluate the homogenized thermo-mechanical moduli of each RUC. Subsequently, a two-dimensional deep convolution neural network (CNN) is constructed as a surrogate model to extract the statistical correlations between the RUC geometrical information and the corresponding homogenized response. The RUC images together with their homogenized moduli are divided into two datasets in a ratio of 9:1 with the former part used for training the CNN model and the latter part used for verification. The results presented in this contribution demonstrate that the deep CNN predictions exhibit remarkable correlations with the theoretical values generated by the finite-volume micromechanics, with a maximum relative prediction error of less than 8%, providing good support for the data-based homogenization approach.Physically informed deep homogenization neural network for unidirectional multiphase/multi-inclusion thermoconductive composites
http://hdl.handle.net/10985/23502
Physically informed deep homogenization neural network for unidirectional multiphase/multi-inclusion thermoconductive composites
JIANG, Jindong; WU, Jiajun; CHEN, Qiang; CHATZIGEORGIOU, George; MERAGHNI, Fodil
Elements of the periodic homogenization framework and deep neural network were seamlessly connected for the first time to construct a new micromechanics theory for thermoconductive composites called physically informed Deep Homogenization Network (DHN). This method utilizes a two-scale expansion of the temperature field of spatially uniform composites in terms of macroscopic and fluctuating contributions. The latter is estimated using deep neural network layers. The DHN is trained on a set of collocation points to obtain the fluctuating temperature field over the unit cell domain by minimizing a cost function given in terms of residuals of strong form steady-state heat conduction governing differential equations. Novel use of a periodic layer with several independent periodic functions with adjustable training parameters ensures that periodic boundary conditions of temperature and temperature gradients at the unit cell edges are exactly satisfied. Automatic differentiation is utilized to correctly compute the fluctuating temperature gradients. Homogenized properties and local temperature and gradient distributions of unit cells reinforced by unidirectional fiber or weakened by a hole are compared with finite-element reference results, demonstrating remarkable correlation but without discontinuities associated with temperature gradient distributions in the finite-element simulations. We also illustrate that the DHN enhanced with transfer learning provides a substantially more efficient and accurate simulation of multiple random fiber distributions relative to training the network from scratch.
Mon, 01 May 2023 00:00:00 GMThttp://hdl.handle.net/10985/235022023-05-01T00:00:00ZJIANG, JindongWU, JiajunCHEN, QiangCHATZIGEORGIOU, GeorgeMERAGHNI, FodilElements of the periodic homogenization framework and deep neural network were seamlessly connected for the first time to construct a new micromechanics theory for thermoconductive composites called physically informed Deep Homogenization Network (DHN). This method utilizes a two-scale expansion of the temperature field of spatially uniform composites in terms of macroscopic and fluctuating contributions. The latter is estimated using deep neural network layers. The DHN is trained on a set of collocation points to obtain the fluctuating temperature field over the unit cell domain by minimizing a cost function given in terms of residuals of strong form steady-state heat conduction governing differential equations. Novel use of a periodic layer with several independent periodic functions with adjustable training parameters ensures that periodic boundary conditions of temperature and temperature gradients at the unit cell edges are exactly satisfied. Automatic differentiation is utilized to correctly compute the fluctuating temperature gradients. Homogenized properties and local temperature and gradient distributions of unit cells reinforced by unidirectional fiber or weakened by a hole are compared with finite-element reference results, demonstrating remarkable correlation but without discontinuities associated with temperature gradient distributions in the finite-element simulations. We also illustrate that the DHN enhanced with transfer learning provides a substantially more efficient and accurate simulation of multiple random fiber distributions relative to training the network from scratch.Isogeometric homogenization of viscoelastic polymer composites via correspondence principle
http://hdl.handle.net/10985/24061
Isogeometric homogenization of viscoelastic polymer composites via correspondence principle
CHEN, Qiang; DU, Xiaoxiao; WANG, Wei; CHATZIGEORGIOU, George; MERAGHNI, Fodil; ZHAO, Gang
We present an isogeometric homogenization theory (IGH) for efficiently identifying homogenized and local creep and relaxation response of linearly viscoelastic polymer composites with different microstructural parameters. The principal idea is to construct exact geometric representations of both two- and three-dimensional unit cell microstructures for periodic materials by utilizing
multiple conforming NURBS patches that are also employed for the displacement field interpolation function at the local scale. The IGH-based unit cell formulation is then converted to the viscoelastic solution with the Laplace-Carson space parameters via the correspondence principle. Subsequently, we leverage the Zakian formula to reverse the transformed IGH solution and obtain the homogenized creep and relaxation response of the composite in the original time space. The modelling and predictive capabilities of the IGH theory have been extensively validated vis-à-vis the elasticity-based and conventional finite-element homogenization techniques, and the advantages of the proposed technique over the reference techniques were demonstrated.
Dr. Xiaoxiao Du would like to thank the financial support of the National Natural Science Foundation of China (Project No. 62102012) and the Young Elite Scientists Sponsorship Program by CAST (Project No. 2022QNRC001).
Wed, 01 Nov 2023 00:00:00 GMThttp://hdl.handle.net/10985/240612023-11-01T00:00:00ZCHEN, QiangDU, XiaoxiaoWANG, WeiCHATZIGEORGIOU, GeorgeMERAGHNI, FodilZHAO, GangWe present an isogeometric homogenization theory (IGH) for efficiently identifying homogenized and local creep and relaxation response of linearly viscoelastic polymer composites with different microstructural parameters. The principal idea is to construct exact geometric representations of both two- and three-dimensional unit cell microstructures for periodic materials by utilizing
multiple conforming NURBS patches that are also employed for the displacement field interpolation function at the local scale. The IGH-based unit cell formulation is then converted to the viscoelastic solution with the Laplace-Carson space parameters via the correspondence principle. Subsequently, we leverage the Zakian formula to reverse the transformed IGH solution and obtain the homogenized creep and relaxation response of the composite in the original time space. The modelling and predictive capabilities of the IGH theory have been extensively validated vis-à-vis the elasticity-based and conventional finite-element homogenization techniques, and the advantages of the proposed technique over the reference techniques were demonstrated.Cycle jump technique combined with mean-field micromechanics towards predicting the cyclic response of PA66/GF composites under viscoelastic- viscoplastic regime and damage mechanisms
http://hdl.handle.net/10985/23925
Cycle jump technique combined with mean-field micromechanics towards predicting the cyclic response of PA66/GF composites under viscoelastic- viscoplastic regime and damage mechanisms
CHEN, Qiang; CHATZIGEORGIOU, George; ROBERT, Gilles; MERAGHNI, Fodil
This work proposes a probabilistic micromechanics damage framework to predict the uniaxial and cyclic stress-strain response and progressive damage in random glass-reinforced polyamide composites. Motivated by different microscopic degradation modes observed experimentally, the damage mechanism in the vicinity of the fibers is characterized by the onset and the coalescence of voids, whose evolution can be formulated through a Weibull probabilistic density function. In contrast, the ductile progressive degradation of matrix initial stiffness is analyzed via the continuum damage theory. Towards this end, a 2N+1-phase Mori-Tanaka (MT) method combined with the transformation field analysis approach (TFA) is established within a unified framework. Moreover, the rate-dependent viscoelastic and viscoplastic response of the polymer matrix phase is formulated through a phenomenological model consisting of four Kelvin-Voigt branches and a viscoplastic branch under the thermodynamics framework. Comparison of numerical predictions with experimental data demonstrates the model’s capabilities. In a second step of this work, the micromechanics scheme is combined with the cycle-jump technique in order to simulate moderate and high cycle fatigue tests. This modeling strategy is validated through comparison with experimental results.
Sat, 01 Jul 2023 00:00:00 GMThttp://hdl.handle.net/10985/239252023-07-01T00:00:00ZCHEN, QiangCHATZIGEORGIOU, GeorgeROBERT, GillesMERAGHNI, FodilThis work proposes a probabilistic micromechanics damage framework to predict the uniaxial and cyclic stress-strain response and progressive damage in random glass-reinforced polyamide composites. Motivated by different microscopic degradation modes observed experimentally, the damage mechanism in the vicinity of the fibers is characterized by the onset and the coalescence of voids, whose evolution can be formulated through a Weibull probabilistic density function. In contrast, the ductile progressive degradation of matrix initial stiffness is analyzed via the continuum damage theory. Towards this end, a 2N+1-phase Mori-Tanaka (MT) method combined with the transformation field analysis approach (TFA) is established within a unified framework. Moreover, the rate-dependent viscoelastic and viscoplastic response of the polymer matrix phase is formulated through a phenomenological model consisting of four Kelvin-Voigt branches and a viscoplastic branch under the thermodynamics framework. Comparison of numerical predictions with experimental data demonstrates the model’s capabilities. In a second step of this work, the micromechanics scheme is combined with the cycle-jump technique in order to simulate moderate and high cycle fatigue tests. This modeling strategy is validated through comparison with experimental results.Deep homogenization networks for elastic heterogeneous materials with two- and three-dimensional periodicity
http://hdl.handle.net/10985/24281
Deep homogenization networks for elastic heterogeneous materials with two- and three-dimensional periodicity
WU, Jiajun; JIANG, Jindong; CHEN, Qiang; CHATZIGEORGIOU, George; MERAGHNI, Fodil
We present a deep learning framework that leverages computational homogenization expertise to predict the local stress field and homogenized moduli of heterogeneous materials with two- and three-dimensional periodicity, which is named physics-informed Deep Homogenization Networks (DHN). To this end, the displacement field of a repeating unit cell is expressed as two-scale expansion in terms of averaging and fluctuating contributions dependent on the global and local coordinates, respectively, under arbitrary multi-axial loading conditions. The latter is regarded as a mesh-free periodic domain estimated using fully connected neural network layers by minimizing residuals of Navier's displacement equations of anisotropic microstructured materials for specified macroscopic strains with the help of automatic differentiation. Enabled by the novel use of a periodic layer, the boundary conditions are encoded directly in the DHN architecture which ensures exact satisfaction of the periodicity conditions of displacements and tractions without introducing additional penalty terms. To verify the proposed model, the local field variables and homogenized moduli were examined for various composites against the finite-element technique. We also demonstrate the feasibility of the proposed framework for simulating unit cells with locally irregular fibers via transfer learning and find a significant enhancement in the accuracy of stress field recovery during neural network retraining.
Fri, 01 Dec 2023 00:00:00 GMThttp://hdl.handle.net/10985/242812023-12-01T00:00:00ZWU, JiajunJIANG, JindongCHEN, QiangCHATZIGEORGIOU, GeorgeMERAGHNI, FodilWe present a deep learning framework that leverages computational homogenization expertise to predict the local stress field and homogenized moduli of heterogeneous materials with two- and three-dimensional periodicity, which is named physics-informed Deep Homogenization Networks (DHN). To this end, the displacement field of a repeating unit cell is expressed as two-scale expansion in terms of averaging and fluctuating contributions dependent on the global and local coordinates, respectively, under arbitrary multi-axial loading conditions. The latter is regarded as a mesh-free periodic domain estimated using fully connected neural network layers by minimizing residuals of Navier's displacement equations of anisotropic microstructured materials for specified macroscopic strains with the help of automatic differentiation. Enabled by the novel use of a periodic layer, the boundary conditions are encoded directly in the DHN architecture which ensures exact satisfaction of the periodicity conditions of displacements and tractions without introducing additional penalty terms. To verify the proposed model, the local field variables and homogenized moduli were examined for various composites against the finite-element technique. We also demonstrate the feasibility of the proposed framework for simulating unit cells with locally irregular fibers via transfer learning and find a significant enhancement in the accuracy of stress field recovery during neural network retraining.Recursive multiscale homogenization of multiphysics behavior of fuzzy fiber composites reinforced by hollow carbon nanotubes
http://hdl.handle.net/10985/22398
Recursive multiscale homogenization of multiphysics behavior of fuzzy fiber composites reinforced by hollow carbon nanotubes
CHEN, Qiang; CHATZIGEORGIOU, George; MERAGHNI, Fodil
Fuzzy fibers are fibers enhanced in terms of multiphysics properties with radially oriented carbon nanotubes grown on their surface through the chemical deposition process. For the first time, this paper attempts to present two generalized zeroth-order asymptotic homogenization schemes aimed at identifying the homogenized and local response of fuzzy fiber-reinforced composites, accounting for both multiphysics piezoelectric effect and cylindrically orthotropic material behavior. The unit cell problems are solved using the multiphysics finite-volume and the multiphysics finite-element techniques, respectively. While the former approach is based on the strong form solution of the equilibrium and conservation equations in an averaged sense in the discretized domain, the latter is based on the minimization of the total potential energy over the entire unit cell. A recursive multiscale analysis algorithm is developed wherein homogenized moduli (or local fields) obtained from the homogenization (or localization) analysis at one scale are utilized in the calculation of homogenized moduli (or local fields) at the next scale. Numerical examples indicate that good agreement of the homogenized properties and local field distributions generated by the two approaches is observed hence confirming the accuracy of the new homogenization methods for fuzzy fiber composites with multiphysics behaviors.
Sat, 01 Jan 2022 00:00:00 GMThttp://hdl.handle.net/10985/223982022-01-01T00:00:00ZCHEN, QiangCHATZIGEORGIOU, GeorgeMERAGHNI, FodilFuzzy fibers are fibers enhanced in terms of multiphysics properties with radially oriented carbon nanotubes grown on their surface through the chemical deposition process. For the first time, this paper attempts to present two generalized zeroth-order asymptotic homogenization schemes aimed at identifying the homogenized and local response of fuzzy fiber-reinforced composites, accounting for both multiphysics piezoelectric effect and cylindrically orthotropic material behavior. The unit cell problems are solved using the multiphysics finite-volume and the multiphysics finite-element techniques, respectively. While the former approach is based on the strong form solution of the equilibrium and conservation equations in an averaged sense in the discretized domain, the latter is based on the minimization of the total potential energy over the entire unit cell. A recursive multiscale analysis algorithm is developed wherein homogenized moduli (or local fields) obtained from the homogenization (or localization) analysis at one scale are utilized in the calculation of homogenized moduli (or local fields) at the next scale. Numerical examples indicate that good agreement of the homogenized properties and local field distributions generated by the two approaches is observed hence confirming the accuracy of the new homogenization methods for fuzzy fiber composites with multiphysics behaviors.