Volume Element Research Articles

Ultimate resistance and fatigue performance predictions of woven-based fiber reinforced polymers using a computational homogenization method

PurposeIn order to achieve the desired macroscopic mechanical properties of woven fiber reinforced polymer (FRP) materials, it is necessary to conduct a detailed analysis of their microscopic load-bearing capacity.Design/methodology/approachUtilizing the representative volume element (RVE) model, this study delves into how the material composition influences mechanical parameters and failure processes.FindingsTo study the ultimate strength of the materials, this study considers the damage situation in various parts and analyzes the stress-strain curves under uniaxial and multiaxial loading conditions. Furthermore, the study investigates the degradation of macroscopic mechanical properties of fiber and resin layers due to fatigue induced performance degradation. Additionally, the research explores the impact of fatigue damage on key material properties such as the elastic modulus, shear modulus and Poisson's ratio.Originality/valueBy studying the load-bearing mechanisms at different scales, a direct correlation is established between the macroscopic mechanical behavior of the material and the microstructure of woven FRP materials. This comprehensive analysis ultimately elucidates the material's mechanical response under conditions of fatigue damage.

A scale-span method to characterize the mechanical property of BCF/PEEK considering uncertain structural characteristics

The focus of this study is exploring a scale-span characterization method to predict the mechanical properties of Braided Carbon Fiber Reinforced Poly Ether Ether Ketone (BCF/PEEK) considering structural uncertainty. Firstly, a complicated micro-scale Representative Volume Element (RVE) model that considers the random position and size of fiber was established via the developed Python script. Analogously, a mathematical expression adopted by the trust region algorithm was proposed to accurately describe the detailed cross-sectional shapes and fluctuation amplitude characteristics of BCF/PEEK for the sake of establishing the precision meso-scale RVE model. Then, the corresponding elastic properties that consider fiber volume fraction and fiber distribution location were characterized via the span-scale characterization method. Meanwhile, the influence of fiber bundle fluctuation amplitude and fiber volume fraction on the mechanical properties was investigated as well. In addition, the mechanical properties of BCF/PEEK with the change of the braid angle between warp and weft yarn were predicted via the established meso-scale RVE model. Finally, a series of experiments have been carried out. The maximum and minimum absolute prediction deviation of all elastic property parameters were only 4.07 % and 1.41 %, respectively, which verified the proposed scale-span characterization method can predict the mechanical properties of composites well.

Determining the Size of Representative Volume Elements for a Two-Dimensional Random Aggregate Numerical Model of Asphalt Mortar without Damage.

The size of the representative volume element (RVE) for the two-dimensional (2D) random aggregate numerical model of asphalt mortar in a non-destructive state, which directly affects the time required to simulate the linear viscoelastic behavior from asphalt mastic to asphalt mortar. However, in the existing literature, limited research has been conducted on the size determination of the numerical model RVE for asphalt mortar. To provide a recommended size for the typical 2D random aggregate numerical model RVE of asphalt mortar in a nondestructive state, this paper first applies the virtual specimen manufacturing method of asphalt concrete 2D random aggregate to asphalt mortar. Then, it generates numerical model RVEs of asphalt mortar with different maximum particle sizes, after which geometric and numerical analyses are conducted on these models. Finally, based on the geometric and numerical analysis results, the recommended minimum sizes of RVE for the 2D asphalt mortar numerical model are provided.

Analysis of rolling contact and tooth root bending fatigue in a new high-strength steel: Experiments and micromechanical modelling

To find materials that meet the future requirements of increasing load density in wind turbine gear structures, the commonly used reference material, 18CrNiMo7-6, and another high-strength steel were analysed. Their fatigue properties were studied through rolling contact fatigue (RCF) and gear tooth root bending fatigue (TRBF) tests. The reference steel exhibited better fatigue performance under RCF conditions compared to the new steel; however, it was outperformed by the new steel under TRBF conditions. This study aims to understand gear contact fatigue at the microscopic level, moving beyond the macroscopic focus that dominates current research literature. To establish the causal link between the varied fatigue performance observed in these materials, we proposed a multiscale modelling workflow based on crystal plasticity. This crystal plasticity framework is combined with the fatigue indicator parameter (FIP) to explore the fatigue resistance of materials subjected to RCF and TRBF conditions. Emphasis has been placed on the role of retained austenite (RA) in fatigue performance. Utilizing representative elementary volumes (REVs) generated based on statistically representative crystallographic features and measured size distribution of RA, we examined the effects of various RA levels on fatigue resistance. Our findings reveals that the fatigue damage accumulation is significantly influenced by the level of RA. Different fatigue damage accumulation behaviours were observed under RCF and TRBF conditions. These insights offer new perspectives on RA’s role in fatigue resistance and highlight its complex influence under varied loading conditions.

Multiscale simulation of spatially correlated microstructure via a latent space representation

When deformation gradients act on the scale of the microstructure of a part due to geometry and loading, spatial correlations and finite-size effects in simulation cells cannot be neglected. We propose a multiscale method that accounts for these effects using a variational autoencoder to encode the structure–property map of the stochastic volume elements making up the statistical description of the part. In this paradigm the autoencoder can be used to directly encode the microstructure or, alternatively, its latent space can be sampled to provide likely realizations. We demonstrate the method on three examples using the common additively manufactured material AlSi10Mg in: (a) a comparison with direct numerical simulation of the part microstructure, (b) a push forward of microstructural uncertainty to performance quantities of interest, and (c) a simulation of functional gradation of a part with stochastic microstructure.

Multi deep learning-based stochastic microstructure reconstruction and high-fidelity micromechanics simulation of time-dependent ceramic matrix composite response

A multi deep learning-based framework is developed for efficient, automated microstructure reconstruction and generation of stochastic representative volume elements (SRVEs) with periodic boundary conditions (PBCs) for accurate modeling of ceramic matrix composite (CMC) response. The methodology comprises a convolutional neural network coupled with regression layers to act as a vanilla regression network for semantic segmentation of the microstructure, allowing accurate characterization of the phases and their distributions at the microscale. Scanning electron microscope and confocal microscope are used to obtain C/SiNC and SiC/SiNC CMCs micrographs for vanilla regression testing. Microstructure variability in terms of fiber volume fraction and porosity are quantified through the output regression layer, ensuring accurate representation of material variability in SRVE construction. Generative adversarial network (GAN) and its variants are designed to produce high-fidelity SRVE, spanning CMCs microstructure variability space. A circular padding algorithm is developed to generate SRVEs with PBCs during training of GANs. The accuracy of the generated SRVEs is established through micromechanics simulations, where an efficient formulation of the high-fidelity generalized methods of cells (HFGMC) approach is used to compute the effective mechanical properties. An iterative algorithm is implemented in the HFGMC solver to simulate time-dependent deformation of SiC/SiNC subjected to creep loading conditions.

Multi-scale Modeling and Finite Element Analyses of Thermal Conductivity of 3D C/SiC Composites Fabricating by Flexible-Oriented Woven Process

Thermal conductivity is one of the most significant criterion of three-dimensional carbon fiber-reinforced SiC matrix composites (3D C/SiC). Represent volume element (RVE) models of microscale, void/matrix and mesoscale proposed in this work are used to simulate the thermal conductivity behaviors of the 3D C/SiC composites. An entirely new process is introduced to weave the preform with three-dimensional orthogonal architecture. The 3D steady-state analysis step is created for assessing the thermal conductivity behaviors of the composites by applying periodic temperature boundary conditions. Three RVE models of cuboid, hexagonal and fiber random distribution are respectively developed to comparatively study the influence of fiber package pattern on the thermal conductivities at the microscale. Besides, the effect of void morphology on the thermal conductivity of the matrix is analyzed by the void/matrix models. The prediction results at the mesoscale correspond closely to the experimental values. The effect of the porosities and fiber volume fractions on the thermal conductivities is also taken into consideration. The multi-scale models mentioned in this paper can be used to predict the thermal conductivity behaviors of other composites with complex structures.

Gold nanoparticle-enhanced radiotherapy: Dependence of the macroscopic dose enhancement on the microscopic localization of the nanoparticles within the tumor vasculature.

In gold nanoparticle-enhanced radiotherapy, intravenously administered nanoparticles tend to accumulate in the tumor tissue by means of the so-called permeability and retention effect and upon irradiation with x-rays, the nanoparticles release a secondary electron field that increases the absorbed dose that would otherwise be obtained from the interaction of the x-rays with tissue alone. The concentration of the nanoparticles in the tumor, number of nanoparticles per unit of mass, which determines the total absorbed dose imparted, can be measured via magnetic resonance or computed tomography images, usually with a resolution of several millimeters. Using a tumor vasculature model with a resolution of 500 nm, we show that for a given concentration of nanoparticles, the dose enhancement that occurs upon irradiation with x-rays greatly depends on whether the nanoparticles are confined to the tumor vasculature or have already extravasated into the surrounding tumor tissue. We show that, compared to the reference irradiation with no nanoparticles present in the tumor model, irradiation with the nanoparticles confined to the tumor vasculature, either in the bloodstream or attached to the inner blood vessel walls, results in a two to three-fold increase in the absorbed dose to the whole tumor model, with respect to an irradiation when the nanoparticles have already extravasated into the tumor tissue. Therefore, it is not enough to measure the concentration of the nanoparticles in a tumor, but the location of the nanoparticles within each volume element of a tumor, be it inside the vasculature or the tumor tissue, needs to be determined as well if an accurate estimation of the resultant absorbed dose distribution, a key element in the success of a radiotherapy treatment, is to be made.

Intra-yarn fibre hybridisation effect on homogenised elastic properties and micro and meso-stress analysis of 2D woven laminae: Two-scale FE model

In this paper, the effect of intra-yarn fibre hybridisation on the homogenised elastic properties and micro- and meso-scale matrix stress fields in 2D woven composite laminae (i.e. plain, 2/2 basket, 2/2 twill and 5-harness satin) is studied with a two-scale homogenisation scheme—employing a representative volume element model at micro-scale and a repeating unit cell model at meso-scale. The study is focused on S-glass/polypropylene/epoxy woven laminae with intra-yarn fibre hybridisation. A modified random sequential expansion algorithm generates microstructure for the micro-mechanical model, and a periodic meso-structure is used to generate the weave architecture for the meso-mechanical model. Both models are verified using analytical models. It is found that intra-yarn fibre hybridisation can significantly alter the homogenised properties as well as the micro- and meso-scale matrix stress fields—depending on the degree of hybridisation (i.e. the combination of S-glass and PP fibre volume fractions). Moreover, the homogenised lamina properties are found to be less sensitive to weave architecture and yarn thickness, but more so to the degree of intra-yarn fibre hybridisation, yarn width and yarn spacing. It is shown that the lamina properties can be tailored, and the micro- and meso-stress fields can be manipulated, by intra-yarn fibre hybridisation and weave architectures.

Physically based modelling of orientation deviation effect on mechanical behavior for dual‐phase single‐crystal superalloy

AbstractThis work systematically investigates the orientation deviation effect on the elastoplastic deformation of a dual‐phase, nickel‐based single‐crystal superalloy through a combined experimental study and crystal plasticity finite element modelling method (CPFEM). Physically based, dual‐phase microstructural model was developed based on scanning electron microscopy (SEM), which was implemented by finite element (FE) modelling using a representative volume element (RVE) with periodic boundary conditions. An extended equivalent yield criterion coupled with CPFEM was adopted to describe the non‐uniform yield behavior induced by octahedral and cubic slip systems. The predicted results have shown that both the bulk behavior and localized stress–strain nature are orientation deviation dependent and that the first Euler angle plays a more important role in elastoplastic behavior than the second Euler angle. This study has thus advanced the basic understanding of the relationship between orientation deviation and the bulk deformation behavior of the dual‐phase nickel‐based single crystal.

Geometric estimates and comparability of Eisenman volume elements with the Bergman kernel on ([formula omitted]-)convex domains

We establish geometric upper and lower estimates for the Carathéodory and Kobayashi-Eisenman volume elements on the class of non-degenerate convex domains, as well as on the more general class of non-degenerate C-convex domains. As a consequence, we obtain explicit universal lower bounds for the quotient invariant both on non-degenerate convex and C-convex domains. Here the bounds we derive, for the above mentioned classes in Cn, only depend on the dimension n for a fixed n≥2. Finally, it is shown that the Bergman kernel is comparable with these volume elements up to small/large constants depending only on n.

Multiscale Modeling of Elastic Waves in Carbon-Nanotube-Based Composite Membranes

A multiscale model is developed for vertically aligned carbon nanotube (CNT)-based membranes that are made for water purification or gas separation. As a consequence of driving fluids through the membranes, they carry stress waves along the fiber direction. Hence, a continuum mixture theory is established for a representative volume element to characterize guided waves propagating in a periodically CNT-reinforced matrix material. The obtained coupled governing equations for the CNT-based composite are found to retain the integrity of the wave propagation phenomenon in each constituent, while allowing them to coexist under analytically derived multiscale interaction parameters. The influence of the mesoscale characteristics on the continuum behavior of the composite is demonstrated by dispersion curves of harmonic wave propagation. Analytically established continuum mixture theory for the CNT-based composite is strengthened by numerical simulations conducted in COMSOL for visualizing mode shapes and wave propagation patterns.

Enhanced multifunctionality in carbon fiber/carbon nanotube reinforced PEEK hybrid composites: Superior combination of mechanical properties, electrical conductivity, and EMI shielding

This study presents a novel approach to manufacturing carbon fiber and carbon nanotube-reinforced PEEK hybrid composites (CF/CNT/PEEK) using compression molding. The hybrid composite characteristics were compared with those of a control composite (CF/PEEK). Various tests were conducted on both composite types to investigate the impact of incorporating a carbon nanotube sock layer (an ultra-thin layer of a low-density CNT network), including three-point bend, electrical conductivity, and EMI shielding. The research also underscored the importance of EMI shielding simulation. An important aspect of the study involved performing multiscale simulations on control and hybrid composites, employing a digital twin methodology, and validating the results with experimental findings. For the hybrid composite, double multiscale simulations were performed by integrating two local-scale models, a CF/PEEK unit cell (micro-scale) and a CNT/PEEK representative volume element (RVE) (nano-scale), into a global-scale model. A detailed post-processing analysis of the simulation results was conducted to analyze stress distribution on local and global scale models. It was noted that there was an over 8 % increase in the flexural strength of the hybrid composite, along with a reduction of over 27 % in the standard deviation of the results. The introduction of CNTs enhanced the electrical conductivity by more than 36 %. It conferred remarkable EMI shielding effectiveness exceeding 50 dB across the entire X-band frequency range, attributed to enhanced reflection and absorption. EMI shielding simulations suggest that refining the manufacturing process of the hybrid composite could enhance its shielding properties. The developed multiscale simulation has been demonstrated as an efficient prediction tool, as the simulation outcomes closely align with experimental findings. The resultant hybrid composite is promising for potential multifunctional applications.

Concurrent multiscale topology optimization for size-dependent structures incorporating multiple-phase materials

The significant progress in additive manufacturing has resulted in the development of well-engineered microstructures with innovative topological configurations, showcasing exceptional performance across diverse fields. Topology optimization is widely recognized as an advanced design tool that provides engineers with new insights for creating lightweight structures. As integration devices continue to trend towards miniaturization, the size effect in small-scale structures remains a persistent challenge. The absence of characteristic parameters to describe this size effect hinders proper explanation through traditional multiscale topology optimization based on classical mechanics. Therefore, we propose a size-dependent topology optimization framework for concurrent multiscale design involving multiple-phase materials. The modified couple stress theory is proposed to account for the size effect in small-scale structures. The numerical findings suggest that the size effect is significantly influenced by the ratio of elastic modulus, volume fraction, and width-to-length ratio of the representative volume element as its characteristic size approaches the length of the material. These results highlight the importance of considering size-dependent effects in topology optimization for multiscale design and provide valuable insights for engineers and researchers in this field.

A multiscale mechanics model for elastic properties of densified wood

We introduce a multiscale mechanics model for analyzing the elastic properties of super-strong densified wood (DW). Our model incorporates microstructural features such as microfibril angle and densification ratio, along with chemical parameters including degree of polymerization, crystallinity, and density of hydrogen bonds. At the nanoscale and microscale, the elastic properties of cellulose nanofibril and cell wall layers are derived analytically using the mechanics of composite materials. Finite element simulations based on representative volume elements are conducted at the mesoscale to obtain homogenized effective elastic properties at the macroscale. Our quantitative investigations validate that microstructural changes and alterations in chemical components significantly enhance DW's mechanical performance. Densification and chemical changes, especially increased cellulose content and reduced lignin, emerge as vital mechanisms for strengthening DW. The model's insights offer valuable guidance for optimizing the two-step preparation process of DW to achieve superior mechanical performance. Additionally, the versatility of the model allows for exploring the influence of cell dimensions and potential applications in designing bioinspired materials.

Study on mechanical properties of natural fiber (Jute)/synthetic fiber (Glass) reinforced polymer hybrid composite by representative volume element using finite element analysis: A numerical approach and validated by experiment

The excellent mechanical strength with low weight of polymer-based composites makes them superior over conventional materials like steel and aluminum in terms of mechanical properties. Nowadays, researchers are working to develop natural fiber-based sustainable composite. Glass fiber, when combined with jute fiber, could greatly enhance the mechanical characteristics of composites; the sequence of the layers mostly determines these properties. In this study, the hybrid laminate of jute and glass fiber with resin polyester is developed with The representative volume element utilized in ANSYS. In ANSYS material design module, the 3D microstructure of composite material is created with various fiber volume fractions of glass fiber and jute fiber. After that, the effective elastic properties of hybrid jute/glass fiber and polyester as matrix, glass fiber/polyester, and jute fiber/polyester are evaluated and the simulation-based effective elastic property is validated by existing experiment value which showed good agreement. For further study, in Ansys ACP PrepPost, the composite laminate such as hybrid jute + glass fiber/polyester, glass fiber/polyester, and jute fiber/polyester is created with desired lamina thickness, stacking sequence, and fiber orientation. Thereafter, it was transferred to a static structure module to perform tensile and bending test analysis. Ansys ACP post-processing is utilized to investigate stress induced at each lamina of the composite specimen. This study revealed that by adding glass fiber to natural fiber, the mechanical performance is enhanced significantly, whereas hybrid jute + glass fiber/polyester (S2) demonstrated the highest tensile strength 259 MPa compared to other hybrid laminate composites. Astonishingly, The hybrid composite jute + glass/polyester (S2) exhibited 10 % higher bending strength than glass fiber/polyester (S1) and 64 % more than net jute fiber/polyester (S5). Additionally, S2 demonstrated 9.5 % higher shear strength compared to S1 and 64 % more than S5. This study will give a great understanding of how adding glass fiber to jute fiber, could enhance the mechanical properties, which will contribute to the design of an efficient composite part for automotive such as car interiors, car doors, trim panels, lightweight applications, and packaging industries.

A comprehensive study of carbon nanoparticle shape and orientation effects on composite elastic properties using FEA

In this study, three critical parameters that influence the effective composite properties of Carbon nanoparticles were tested and modeled using finite elements through Digimat Finite Element Analysis (FEA) software, employing representative volume elements (RVE). The primary parameters under consideration are the fiber shape, fiber orientation, and fiber volume fraction. Four of the many different shapes of Carbon nanoparticles, namely Tubes, Disk, Sphere, and Cylinder, were investigated, coupled with four distinct orientations for tubes: horizontal, aligned at 45°, random, and vertical each varying in the carbon fiber volume fraction. The material of choice was pure epoxy resin because of the nature of the bonding between its two phases and its wide range of usage. Forces were applied along the X-axis, coupled with shear in the XY plane. This study revealed that the orientation of CNTs primarily influences the Elastic Young’s modulus, whereas the size of the CNTs has the main effect on the shear modulus, followed by orientation. The horizontal CNTs demonstrated superior Young’s modulus, but the random orientation had a more pronounced impact on the shear modulus variation. Regarding the analysis of the nanoparticles shapes, the disk shape with fixed orientation revealed the highest elastic modulus, after which the cylinder shape and the sphere recorded the minimum elastic modulus among the three studied shapes.

Synergistic Exploration of Heat Transfer for Integration Magnetohydrodynamics of Nanofluids Peristaltic Transport within Annular Tubes

The problem of treating cancer is considered one of the most important daily challenges that affect the lives of people with cancer. This research deals with solving this problem theoretically. Through previous studies, it has been proven that gold nanoparticles are able to remove these cancer cells. The idea of this research is theoretically based on injecting a cancer patient with gold nanoparticles that are exposed to a magnetic field. When these particles penetrate cancerous cells and are exposed to a magnetic field, this causes their temperature to rise. The high temperature of the nanometer gold particles that penetrate the cells of the affected body leads to the explosion of the cancer cells. In this research, the various external forces that affect the flow movement of the nanofluid are studied and how its physical and thermal properties are affected by those external forces. The MHD peristaltic flow of a nanofluid in an annulus pipe as a result of the effect of the wall properties has been investigated. This has been achieved through slip and thermal conditions. Wave velocity leads to flow development. The inner annulus wall is rigid, while the outer wall of the artery moves under the influence of wave peristaltic movement. The nonlinear equations that describe the flow are solved under long-wavelength assumptions. The results were compared with other numerical methods, such as finite volume and finite element and the long wavelength method and proved to be accurate and effective. The expressions of pressure difference, velocity, stream function, wall shear stress, and temperature are analyzed. It is noted that the flow velocity increases with the Knudsen number, and the increased source heat suggests an increased temperature. The increasing amplitude ratio at most of the interface points between the artery wall and the catheter results in increased velocity. The streamlines are affected by the magnetic field, as increasing the influencing magnetic field leads to a decrease in flow lines. It is observed that this stress decreases when nanoparticles increase, in contrast to the effect of the magnetic field and also the occurrence of slipping. It was found that the mass of the wall cells relative to their area works to decrease the pressure difference, in contrast to the tension between those cells, which works to increase the pressure difference. Without slipping and with slipping , the temperature decreases with increasing in nanoparticle concentration . The temperature also increases with the amplitude ratio . This strongly affects the generated drag on the catheter wall, which is mainly responsible for the enhanced temperature on this wall.

In search for representative elementary volume (REV) within heterogeneous materials: A survey of scalar and vector metrics using porous media as an example

The Representative Elementary Volume (REV) concept, a cornerstone in porous system heterogeneity assessment, was initially conceived to determine the minimal domain volume suitable for homogenization and upscaling. However, the definition of REV and usability in continuum-scale models is vague. In this study, we conduct comprehensive REV analyses on multiple samples, encompassing a range of scalar and vector metrics. Our investigation probes the representativity of crucial medium characteristics, including porosity, permeability, and Euler density, alongside descriptors rooted in pore-network statistics, correlation functions, and persistence diagrams. We explore both deterministic and statistical REV sizes (dREV and sREV), facilitating a robust comparative assessment. Crucially, we introduce an novel methodology tailored for harnessing vector metrics, known for their ability to reveal intricate structural insights. Our results underscore the superiority of the sREV approach, particularly for low-content metrics, addressing inherent limitations of dREV in characterizing homogeneities in such cases. Furthermore, the sREV approach incorporates stationarity analysis into REV evaluation, ensuring result consistency between sREV and dREV under stationarity conditions. Encouragingly, our findings suggest that high-information-content metrics, notably correlation functions combined with persistence diagrams, have the potential to establish a universal REV for steady-state physical properties. This proposition warrants further verification through a comprehensive assessment and comparison of REV values across major physical properties. REV analysis plays a pivotal role not only in assessing medium properties but also in scrutinizing different descriptors of 3D images – we note that REV analysis and image/field stationarity analysis are ultimately the same techniques under the hood. The discussion based on obtained results and recent finding by other researchers advances the understanding of REV within porous media, introduces a versatile methodology with broader applications, and is expected to be useful in numerous fields including materials science, cosmology, machine learning, and more. We redefine the classical definition of REV by adding stationarity condition and upper/lower bounds on its volume. While for simplicity, in this work we shall mainly focus on porous media as immediately applicable to digital rock, petrophysics, hydrology and soil physics problems, the developed mythology can be applied to other material types - composites, biological tissues, granular matter, food engineering and numerous other types of matter.

Correlating mechanical properties of Al/Al bimetal composite and its constituents using combined experiment and microstructure-based multiscale modeling approach

A combined experiment and multiscale modeling approach was presented to correlate the mechanical properties of a roll-bonded AA1050/AA3004 bimetal clad sheet and constituents. The mechanical responses of the 2-ply AA1050/AA3004 and constituents were measured under various loading conditions. For the measurements, each constituent was separated from the clad sheet using electrical discharge machining and uniaxial tensile tests. Continuum-scale yield functions such as isotropic von Mises and anisotropic/non-quadratic Yld2000-2d were developed for the two constituents and the bimetal clad sheet. A grain-scale crystal plasticity finite element (CPFE) simulations were also performed incorporated with newly developed representative volume element considering measured microstructural attributes. These CPFE predictions were used to identify the anisotropy coefficients for Yld2000-2d. Using the identified yield functions, finite element modeling was followed in which the mechanical properties of each constituent sheet were addressed separately. This is a new approach developed in the current work and it enables a fundamental correlation between multilayered material and its constituents. The mechanical properties of the bimetal clad sheet under the uniaxial tensions were predicted using those of the constituents and compared with calculations based on known rule of mixture (ROM) approach. The two approaches well reproduced stress–strain curves and r–value evolutions. The two FE modeling approaches were also applied to an independent test (i.e., the limiting dome height). The predictions were in good agreement with the experimental data. Finally, the mechanical properties of the bimetal clad sheet and constituents were correlated, and proper modeling scheme for multilayered materials is proposed.