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Injection molded plastics are widely used for mass production in auto industry. However, it is challenge to produce parts that do not warp. It is helpful to have an accurate way to measure the warpage when investigating and solving warpage issues. In this paper, a new technology is introduced to measure the part warpage quickly and accurately with the help of digital image correlation (DIC) method. The polypropylene plaque were fabricated by injection molding based on An L9 (3ˆ4) Taguchi design of experiments. The warpage of plaque are characterized for all the conditions and at different time after being ejected. Different kinds of warpage results are obtained by DIC method, such as maximum deflection, deflection distribution along desired path, warpage contour on the surface. The plaque warpage increases with the time. The maximum difference can reach as high as 64.9%. The cooling time has the largest influence on the warpage, while the packing pressure has the minor effect. Nevertheless, the warpage difference due to time varying depends on melt temperature, mold temperature, cooling time and packing pressure, in which mold temperature has the highest effects.

Failure analysis is a critical process for the lifetime evaluation of high density polyethylene (HDPE) under cyclic loading since HDPE may encounter different failure modes under different service environments. However, there are only a few investigations on the failure mechanism and failure mode of HDPE in cyclic-loading tests. The objective of this paper is to understand the failure mechanism and propose an approach to predict the failure mode of HDPE under cyclic loading. On the mechanism analysis, our results demonstrated that there could be three failure modes including necking, buckling and fatigue cracking for HDPE under cyclic loading. Both necking and buckling were strongly dependent on the increase of the specimen temperature, which led to the reduction of both yield stress defining necking and tangent modulus governing buckling. On the mode prediction, the yield stress and the tangent modulus could be computed as the functions of specimen temperature which was calculated by FEM heat transfer analysis considering heat generated by inelastic deformation energy and heat transferred with surroundings. Then, necking was predicted by comparing the decreased yield stress with the applied peak stress, and buckling was predicted by comparing the declined buckling stress proportional to tangent modulus with the absolute of the applied valley stress. The proposed methodology was validated as the predicted results were well matched with the experimental data for the tests of HDPE under different cyclic loadings.

The sink mark is one common defect of the injection-molded thermoplastics, which is harmful to the part appearance. A procedure for the sink mark prediction was proposed to build the finite element method (FEM) model in Abaqus. The temperature and pressure distributions were imported as boundary conditions at a different time from the injection molding simulation software Moldflow. The user subroutines UEXPAN and UMAT were coded and implemented in Abaqus to describe the pressure-volume-temperature (PVT) behaviors under actual cooling conditions and the polymer constitutive relationship. The PVT curves of the thermoplastic were obtained by the piston-die method at a cooling rate of 5 °C/min. The crystallizing behaviors were measured by a differential scanning calorimetry and adapted to modify the PVT curves at different cooling rates. The tension-compression tests at different temperatures were performed to obtain the stress-strain curves. The simulation of injection molding was conducted in the software Moldflow. The deflection tests were conducted on the coordinate measuring machine (CMM) to validate the predicted sink mark. It was found that the subroutines of UEXPAN described the volume variations under different cooling rates successfully. Furthermore, the subroutine UMAT predicted stress-strain curves successfully at different temperatures and strain rates. The predicted sink mark in Abaqus agreed well with the measured one. The sink mark depth from Abaqus reached one third of the experimental one and had obvious improvement than that from Moldflow.

In present study, the fatigue damage behavior of chopped carbon fiber chip-reinforced composite has been experimentally and numerically investigated. A large scatter is exhibited in the S-N diagram due to the random distribution of carbon fiber chips, and therefore a new analysis procedure is proposed to link the local microstructure to the fatigue behavior of the bulk material. Interrupted fatigue tests are also performed so that microstructure characterization can be conducted on the tested samples to analyze the crack initiation and propagation. Inspired from the experimental findings, a multi-scale progressive damage fatigue model is proposed to predict the fatigue behavior. The model incorporates a new stochastic chip-packing algorithm for microstructure reconstruction along with continuum damage models into the representative volume element (RVE) model in ABAQUS/Explicit. The simulation results based on the proposed model are in good agreement with the experimental data in terms of cracking modes and predicted life.

This paper presents a computational framework to predict the tensile failure of chopped carbon fiber SMC composites based on the Representative Volume Element (RVE) model. In the framework, a conforming mesh-based reconstruction algorithm is developed to generate mesostructure RVE models of SMC based on the statistical characteristics. Moreover, constitutive models are proposed for the three phases in SMC composites: fiber chip, matrix, and interface. The model predictions are validated by coupon-level experimental tests on SMC samples of various chip orientation distributions. The meso-scale failure mechanism and failure strength predicted by the RVE models are in good agreement with the experimental results. The presented study demonstrates the capability of the present modeling framework in the design of composites materials with complex micro- and meso- structure.

It is important to investigate the constitutive behavior of high density polyethylene (HDPE) under cyclic loading since it is widely used for industrial applications. However, there are only a few preliminary investigations on the constitutive behavior of HDPE under cyclic loading. This work aims at investigating the deformation mechanism, developing the constitutive model especially for the cyclic-loading behavior, and proposing an efficient approach for model calibration. Firstly, the deformation mechanism was successfully explored by conducting a special designed relaxation-unloading test by which the time-independent elastic-plastic behavior was decoupled from the time-dependent overall deformation behavior. Then, a nonlinear elastic-viscoplastic constitutive model was developed based on the parallel rheological framework (PRF) composed of an elastic-plastic network in parallel with multiple nonlinear viscoelastic networks. Finally, an approach was proposed to calibrate the constitutive model by means of relaxation-unloading tests and material parameter optimizations. The agreement between the prediction and the test data successfully demonstrated that the model could be used to precisely simulate the constitutive behavior of HDPE under static, quasi-static and dynamic cyclic loading. The developed constitutive model is beneficial to the long-term durability evaluation of HDPE. The methodology for exploring the deformation mechanism and calibrating the constitutive model may also be applicable to other polymers.

This study proposed a spatiotemporal algorithm to quantitatively characterize the in-situ 3D fracture behavior of carbon-fiber-reinforced polymer (CFRP) composites at microscale . In-situ micro X-ray computed tomography (µXCT) integrated with a tensile stage was applied to capture the 3D fracture evolution of the CFRP composites, where the initiation and propagation of fracture features (e.g., fiber tip-end crack and fiber/matrix debonding) were identified. After the reconstruction of the 3D material microstructure , the proposed spatiotemporal algorithm thereafter extracted the fracture features by employing multiple image processing techniques for quantitative analysis. A similar distribution of the 3D strain obtained from the volumetric digital image correlation demonstrated the feasibility of the developed spatiotemporal algorithm. Moreover, this algorithm provided in-depth and quantitative analysis of fracture features, which provided insights into the microscale failure mechanism and thus shed light on the improvement of failure criteria for CFRP composites with complex microstructures .

This paper presents a discontinuous Galerkin weak form for bond-based peridynamic models to predict the damage of fiber-reinforced composite laminates. To represent the anisotropy of a laminate in a peridynamic model, a lamina is simplified as a transversely isotropic medium under a plane stress condition. The laminated structure is modeled by stacking the surface mesh layers along the thickness direction according to the laminate sequence. To avoid a mesh dependence on either the fiber orientation or the discretization, the spherical harmonic expansion theory is employed to construct a function for the micro-elastic modulus in terms of the bond-fiber angle. The laminate material is decomposed into an isotropic matrix material part and a transversely isotropic material part. The bond stiffness can be evaluated using the engineering material constants, based on the equivalence between the elastic energy density in the peridynamic theory and the elastic energy density in the classic continuum mechanics theory. Benchmark tests are conducted to verify the proposed model. Numerical results illustrate that the convergence of simulations with different horizon sizes and meshes can be achieved. In terms of damage analysis, the proposed model can capture the dynamic process of the complex coupling of the inner-layer and delamination damage modes.

Digital image correlation (DIC) has become an industry standard to retrieve accurate displacement and strain measurement in tensile testing and other material characterization. Though traditional DIC offers a high precision estimation of deformation for general tensile testing cases, the prediction becomes unstable at large deformation or when the speckle patterns start to tear. In addition, traditional DIC requires a long computation time and often produces a low spatial resolution output affected by filtering and speckle pattern quality. To address these challenges, we propose a new deep learning-based DIC approach--Deep DIC, in which two convolutional neural networks, DisplacementNet and StrainNet, are designed to work together for end-to-end prediction of displacements and strains. DisplacementNet predicts the displacement field and adaptively tracks a region of interest. StrainNet predicts the strain field directly from the image input without relying on the displacement prediction, which significantly improves the strain prediction accuracy. A new dataset generation method is developed to synthesize a realistic and comprehensive dataset, including the generation of speckle patterns and the deformation of the speckle image with synthetic displacement fields. Though trained on synthetic datasets only, Deep DIC gives highly consistent and comparable predictions of displacement and strain with those obtained from commercial DIC software for real experiments, while it outperforms commercial software with very robust strain prediction even at large and localized deformation and varied pattern qualities. In addition, Deep DIC is capable of real-time prediction of deformation with a calculation time down to milliseconds., Comment: 39 pages, 19 figures

The mechanical properties and damage behaviors of carbon/epoxy woven fabric composite under in-plane tension and compression are studied at the meso-scale level through experiment and simulation. An efficient representative volume element (RVE) modeling method with consistent mesh, high yarn volume fraction and realistic geometry is proposed. The material constitutive laws with plasticity, tension-compression asymmetry and damage evolution are established for the three components - yarn, matrix and interface, respectively. Significantly different mechanical properties and damage evolutions are observed depending on loading conditions and initial geometry characteristics. It shows a non-linear stress-strain curve with clear transition region and intensive damage in tension, while a quasi-linear behavior up to facture is observed in compression with little damage prior to final fracture. Moreover, compared to the constant Poisson's ratio with straining in compression, a dramatic increase in Poisson's ratio appears in tension. Simulation shows damage mechanisms including transverse damage, matrix damage and delamination, which all play critical roles in the property evolution. In particular, the rapid damage accumulation after elastic deformation destroys the strong bonds and causes the easy deformation of transverse yarns which results in the transition region and large Poisson's ratio in tension. All the mechanical behaviors and damage evolutions are well captured and explained with the current RVE model.

Woven fiber composites have been increasingly employed as light-weight materials in aerospace, construction, and transportation industries due to their superior properties. These materials possess a hierarchical structure that necessitates the use of multiscale simulations in their modeling. To account for the inherent uncertainty in materials, such simulations must be integrated with statistical uncertainty quantification (UQ) and propagation (UP) methods. However, limited advancement has been made in this regard due to the significant computational costs and complexities in modeling spatially correlated structural variations coupled at different scales. In this work, a non-intrusive approach is proposed for multiscale UQ and UP to address these limitations. We introduce the top-down sampling method that allows to model non-stationary and continuous (but not differentiable) spatial variations of uncertainty sources by creating nested random fields (RFs) where the hyperparameters of an ensemble of RFs is characterized by yet another RF. We employ multi-response Gaussian RFs in top-down sampling and leverage statistical techniques (such as metamodeling and dimensionality reduction) to address the considerable computational costs of multiscale simulations. We apply our approach to quantify the uncertainty in a cured woven composite due to spatial variations of yarn angle, fiber volume fraction, and fiber misalignment angle. Our results indicate that, even in linear analysis, the effect of uncertainty sources on the material’s response could be significant.

Sheet metals such as advanced high strength steels often exhibit varying degrees of anisotropy due to the existence of preferred orientation of their grain structures from the rolling process. While extensive research has been devoted to characterize and model anisotropic plasticity behavior over the past decades, only recently people began to tackle their anisotropic fracture behavior. The focus of these studies is almost always on the in-plane anisotropy, and ignores out-of-plane fracture behavior. The reasons are two-folds: (1). Sheet metal deformation during a stamping or crash application is mostly thought as in a plane stress state and modeled as such, so there is no need to consider out-of-plane fracture behavior; and (2). It is very challenging to develop experimental techniques to reliably measure out-of-plane fracture strengths for sheet metals with a thickness only about 1 mm. In this paper, we theorize, based on strong empirical evidence, that the fracture strength of a thin sheet metal in out-of-plane shear is inherently weaker than that under in-plane shear, analogous to the interlaminar properties of composite laminates. This weakness is responsible for the so-called “shear fracture” behavior, often observed during the stamping operations of advanced high strength steels when the sheet metal flows around a tight radius. A new double-notched shear specimen with shear plane perpendicular to the thickness direction is carefully designed and tested to accurately measure the out-of-plane shear fracture strength. Simulations are executed to validate the rationality of the out-of-plane shear specimen design. Test results of a DP980 sheet show that the out-of-plane shear fracture strength is indeed about 15% lower than that measured under the in-plane shear condition. A new anisotropic ductile fracture model based on linear transformation of stresses is proposed to account for the out-of-plane fracture strength for AHSS sheets. The model is calibrated with experimental data, and the fracture surface is compared to the isotropic Mohr-Coulomb (M-C) fracture model to illustrate its effectiveness.

Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE) model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.

In current work, the crashworthiness of woven carbon fiber reinforced plastic (CFRP) hat section component is investigated under two types of loading experimentally and numerically, i.e., axial crushing and dynamic three-point bending. The crushing characteristics of woven CFRP hat section sample are evaluated at various impact velocities and layup orientations which exhibit different effects under two types of loading. With impact velocity/energy increasing, the bending behaviors illustrate different evolutions with distinct stages which are affected by the damage development. Layup orientation shows a little effect on the bending behaviors, while it exerts remarkable effects on the axial crushing which leads to different crushing modes and thus different energy absorption capabilities. The finite element model with multiple layers of thick shell element and cohesive element is shown to capture the crushing behaviors reasonably well in both axial crushing and dynamic bending. The corresponding damage evolutions are also analyzed with simulations to explain the crushing behaviors.

Woven composites are considered as a promising material choice for lightweight applications. An improved non-orthogonal material model that can decouple the strong tension and weak shear behavior of the woven composite under large shear deformation is proposed for simulating the preforming of woven composites. The tension, shear and compression moduli in the model are calibrated using the tension, bias-extension and bending experiments, respectively. The interaction between the composite layers is characterized by a sliding test. The newly developed material model is implemented in the commercial finite element software LS-DYNA® and validated by a double dome study.

Carbon fiber reinforced plastics (CFRPs) are attracting growing attention in industry because of their enhanced properties. Preforming of thermoset carbon fiber prepregs is one of the most common production techniques of CFRPs. To simulate preforming, several computational methods have been developed. Most of these methods, however, obtain the material properties directly from experiments such as uniaxial tension and bias-extension where the coupling effect between tension and shear is not considered. Neglecting this coupling effect deteriorates the prediction accuracy of simulations. To address this issue, we develop a Bayesian model calibration and material characterization approach in a multiscale finite element preforming simulation framework that utilizes mesoscopic representative volume element (RVE) to account for the tension-shear coupling. A new geometric modeling technique is first proposed to generate the RVE corresponding to the close-packed uncured prepreg. This RVE model is then calibrated with a modular Bayesian approach to estimate the yarn properties, test its potential biases against the experiments, and fit a stress emulator. The predictive capability of this multiscale approach is further demonstrated by employing the stress emulator in the macroscale preforming simulation which shows that this approach can provide accurate predictions.

In this work, we have developed a computational probabilistic method to quantify the permanent (non-zero strain) continuum/material deformation. Different from physical-based modeling, the method developed here is based on a data-driven statistics approach, which solves the problem without needing the information of physical deformation process. The proposed method relies only on the scanned material data from the thermal distorted configuration as well as the shape of the initial design configuration. We coined this artificial intelligence based algorithm as the material deformation finding (MDF) algorithm. In this work, the MDF algorithm was first validated by a 2D synthetic example. We then demonstrated that the proposed MDF method can accurately find the permanent thermal distortion of a complex 3D printed structural component, and hence to identify the thermal compensation design configuration. The results obtained in this work indicate that one can use this data-driven statistics approach to significantly mitigate thermal distortion of 3D printed products in additive manufacturing.

We present a data-driven nonlinear uncertainty quantification and propagation framework to study the microstructure-induced stochastic performance of unidirectional (UD) carbon fiber reinforced polymer (CFRP) composites. The proposed approach integrates (1) microscopic image characterization, (2) stochastic microstructure reconstruction, and (3) efficient multiscale finite element simulations enabled by self-consistent clustering (SCA) analysis. To model the complex microstructural variability, the proposed UQ methods take the non-Gaussian uncertainty sources into account through a distribution-free sampling approach leveraging nonparametric and asymptotic statistical tools. A hierarchical conditional sampling strategy enables the simultaneous sampling of multiple sources of uncertainties. Our approach provides insights into the impact of microstructural variabilities, which are shown to have an increasing impact on the nonlinear responses of UD CFRP parts under progressive compression loading and ultimately on the failure rate over time. We discover that before CFRP parts start to fail, a characteristic time period emerges with distinctive uncertainty distributions specific to the microstructure variability and the probability of failure. Identifying the failure time period is crucial to the reliability prediction, which is an essential component of CFRP design.

The mechanical behaviors and damage evolutions of carbon/epoxy woven fabric composites with three different geometries, i.e., one plain weave and two twill weave patterns with different areal densities, are studied under tensile loading. The effects of weave patterns on mechanical properties are investigated by monotonic and cyclic tension tests. Remarkable variations in stress–strain curve, Poisson’s ratio, residual strain and strain map exist in the three composites. Crimp ratio is found to be a critical factor to govern the mechanical properties. With smaller crimp ratio, a quasi-linear stress–strain curve with higher elastic modulus and strength is observed. The stress–strain curves of composites with higher crimp ratio contain transition stages with significant tangent modulus degradation. Elastic modulus, strength and damage initiation are all correlated with the crimp ratio linearly regardless of the fabric pattern. Dramatic nonlinear evolution in Poisson’s ratio occurs in the composite with higher crimp ratio. Cyclic tension results indicate that the residual strain is a more appropriate damage indicator than the unloading elastic modulus. Microstructure examination shows that damage developments are essentially related to the fabric geometry, and result in various mechanical behaviors. This study provides important insights into the geometry-deformation mechanism-mechanical property relationship of the woven composites.

To develop a composite with high in-plane properties and sufficient delamination resistance, a quasi-three-dimensional (Q3D) woven composite has been designed. In Q3D, some yarns in each layer are woven into those in the adjacent layers and form a 3D interlocking network. This study examines the performance of a carbon fiber/SC-15 epoxy triaxial Q3D [ (0°/60°/−60°)4 ] composite. For comparison, a [0°/60°/ − 60°]4 composite laminate with unidirectional (UD) plies and a [ 0°/60°/−60° ]4 laminate with two-dimensional woven (2DW) layers were fabricated using the same carbon fiber and epoxy system. The in-plane tensile, interlaminar fracture, and low-velocity impact tests were performed for all three types of composites. The results show that the Q3D composite has the in-plane tensile modulus and strength comparable to that of UD and 2DW composites, but offers a higher resistance to interlaminar crack propagation and impact damage. This work provides insights into the influences of fiber structures on composite properties and performances.

The mechanical properties and damage evolutions of carbon/epoxy woven fabric composites with three different fabric architectures, including one plain weave and two twill weave patterns, are experimentally investigated under multiaxial stress states. In particular, the effects of weave patterns are investigated by monotonic and cyclic off-axis tension tests. Both elastic modulus and strength degrade remarkably with increasing off-axis loading angle, while Poisson's ratio is much higher than that measured from on-axis tests and increases with loading strain gradually. Different fabric architectures show limited effects on the modulus and strength under multiaxial stress states, and they are well predicted by transformation equation and Tsai-Wu failure criteria, respectively. However, significantly different failure behaviors are observed in three fabric composites, and microstructure observation shows that fabric architecture affects the stress concentration and the damage development. Smaller crimp ratio and compacted structure postpone the damage development but result in more abrupt failure under multiaxial stress states.

The dynamic crushing characteristics of unidirectional carbon fiber reinforced plastic composites under two loading types, dynamic three-point bending and axial crushing, are investigated by experiment and finite element simulation. Hat section samples with two different layup orientations are tested at various impact velocities to investigate its effects. The experiment results show that delamination plays a critical role in dynamic bending deformation. Different layup orientations lead to similar crushing bending behaviors, but remarkable variations in delamination pattern evolutions. In contrast, layup orientation exerts more significant effects on failure modes and energy absorption in axial crushing. A finite element model with multiple layers of thick shell element and cohesive element is established, and simulations are performed for both dynamic three-point bending and axial crushing. The model can capture the crushing behaviors in the two loading types reasonably well. The damage evolution and energy absorption through various mechanisms at different loading conditions are discussed.

This paper addresses the challenge of reconstructing nonuniformly orientated fiber-reinforced polymer composites (FRPs) with three-dimensional (3D) geometric complexity, especially for fibers with curvatures, and proposes a framework using micro X-ray computed tomography (μXCT) images to quantify the fiber characteristics in 3D space for elastic modulus prediction. The FRP microstructure is first obtained from the μXCT images. Then, the fiber centerlines are efficiently extracted with the proposed fiber reconstruction algorithm, i.e., iterative template matching, and the 3D coordinates of the fiber centerlines are adopted for quantitative characterization of the fiber morphology. Finally, Young's modulus is predicted using the Halpin-Tsai model and laminate analogy approach, and the fiber configuration averaging method with the consideration of the fiber morphology. The new framework is demonstrated on both injection-molded short and long carbon fiber-reinforced polymer composites, whose fiber morphology and predicted mechanical properties are validated through previous pyrolysis and quasi-static tensile tests, respectively.

This paper presents a predictive multiscale modeling scheme for Unidirectional (UD) Carbon Fiber Reinforced Polymers (CFRP). A bottom-up modeling procedure is discussed for predicting the performance of UD structures. UD material responses are computed from high fidelity Representative Volume Elements (RVEs). A data-driven Reduced Order Modeling approach compresses RVEs into Reduced Order Models so material responses can be computed in a concurrent fashion along with the structural level simulation. The approach presented in this paper is validated against experimental data and is believed to provide design guidance for future fiber reinforced polymers development.

Carbon fiber reinforced composites have received growing attention because of their superior performance and high potential for lightweight systems. An economic method to manufacture the parts made of these composites is a sequence of forming followed by a compression molding. The first step in this sequence is called preforming that forms the prepreg, which is the fabric impregnated with the uncured resin, to the product geometry, while the molding process cures the resin. Slip between different prepreg layers is observed in the preforming step, and it is believed to have a non-negligible impact on the resulting geometry. This paper reports a method to characterize the interaction between different prepreg layers, which should be valuable for future predictive modeling and design optimization. An experimental device was built to evaluate the interactions with respect to various industrial production conditions. The experimental results were analyzed for an in-depth understanding about how temperature, relative sliding speed, and fiber orientation affect the tangential interaction between two prepreg layers. Moreover, a hydro-lubricant model was introduced to study the relative motion mechanism of this fabric-resin-fabric system, and the results agreed well with the experiment data. The interaction factors obtained from this research will be implemented in a preforming process finite element simulation model.

The fiber orientation distribution is one of the important microstructure variables for thermoplastic composites reinforced with discontinuous fibers. In this paper, the long fibers in the injection molded part are measured in detail by micro X-ray CT. A three dimensional (3D) structure of the sample is built and two dimensional images are generated for image analysis. The orientation tensor of fibers is calculated in the flow plane. It shows a symmetric distribution of fibers through the thickness direction, which consists of outer skin, transition zone and the core. The skin layer is so thin that it has only one layer of highly oriented fibers. The core layer also has highly oriented fibers but the direction of fibers is different from that in the skin layer. Nevertheless, the clustering of the fibers is characterized quantitatively in the core. The transition zone can be divided into two subzones by the principal directions of the tensor.

A6111 is an aluminum alloy, which exhibits good formability and excellent bake hardening property. This study aimed to reveal the influence of strain path, pre-strain orientation (α) as well as pre-strain level on the mechanical properties of A6111-T4P sheet under bake treatment through uniaxial tension test. (0–5)% pre-strain, 150–170 °C bake temperature and 20–30 min bake time were considered in the study by referring to the actual production process. The results show that both pre-strain level and strain path play significant roles in improving the material properties. In the condition that tensile orientation (β) parallel with pre-strain orientation (β = α), the yield strength can be remarkably improved, and much higher parameter of n in Hockett–Sherby model can be obtained than those when tensile orientation non-parallel with pre-strain orientation (α ≠ β). In addition, when the pre-strain level, paint bake process were settled and β = α, the curves obtained in five tension orientations are similar in the plastic deformation stage.

Carbon fiber composites have received growing attention because of their high performance. One economic method to manufacturing the composite parts is the sequence of forming followed by the compression molding process. In this sequence, the preforming procedure forms the prepreg, which is the composite with the uncured resin, to the product geometry while the molding process cures the resin. Slip between different prepreg layers is observed in the preforming step and this paper reports a method to characterize the properties of the interaction between different prepreg layers, which is critical to predictive modeling and design optimization. An experimental setup was established to evaluate the interactions at various industrial production conditions. The experimental results were analyzed for an in-depth understanding about how the temperature, the relative sliding speed, and the fiber orientation affect the tangential interaction between two prepreg layers. The interaction factors measured from these experiments will be implemented in the computational preforming program.

The path-dependence of the conventional Forming Limit Diagram (FLD) is an important issue for its applications in industry. Great efforts have been made to understand the nature of the path-dependence with both experimental and theoretical approaches, many of them attempting to find a path-independent way for the application of forming limits. In this paper, we focus on the nonlinear strain path effect on forming limit predictions using both isotropic and anisotropic hardening models. The Forming Limit Diagram (FLD), Forming Limit Stress Diagram (FLSD) and Forming Limit Effective Strain Diagram (epFLD) of sheet metals subject to linear and nonlinear strain paths are analyzed and compared using the Marciniak–Kuczynski approach. An anisotropic hardening model based on Yoshida and Uemori development is adopted in this study, and it is coupled with the traditional Hill’48 yield surface. This model is capable of describing the complex Bauschinger phenomenon after the material undergoes the reverse loading process such as the early re-yielding, work-hardening stagnation and permanent softening. Two different scenarios for the change of strain paths are also investigated. In the first scenario, the sheet material is initially loaded with a fixed strain increment ratio, unloaded to the free stress state, and then reloaded with a different strain increment ratio until the forming limit is reached. In the second scenario, the material does not undergo elastic unloading. Instead, the strain path is abruptly changed to a different strain increment ratio and the material undergoes continuous loading until the forming limit is reached. It is found that the work-hardening behavior after the pre-straining and the loading scenario plays an important role in the path dependent behavior of forming limits. Detailed analysis reveals that the M–K approach may have contributed to the significance of path-dependence observed in this study, especially at high pre-strain levels.

In most current works related to the structure analysis of cured woven composites, the influence of yarn angle variation on the local material properties is neglected. In this paper, its influence was studied, and an integrated preforming-performance simulation model, accounting for the influence of yarn angle variation, was proposed. The multi-scale modeling approach was adopted to predict the material properties of cured woven composites with different yarn angles. The results were compared with experiments to validate its effectiveness. In the integrated preforming-performance simulation model, non-orthogonal constitutive law was used in the preforming simulation to compute yarn orientations and yarn angle distribution. To demonstrate the capabilities of the integrated simulation model, simulations were conducted and compared with experiments. The results show that the proposed simulation model has more accurate prediction than the simulation model without considering the influence of yarn angle, and the impact of yarn angle shouldn’t be neglected.

One of the important failure criteria of press operations in industry for forming simulations is the Forming Limit Diagram (FLD). The complex loading effects on FLD, in particular the localized necking phenomenon under stretch-bending condition, have not been fully investigated and well understood. In practical sheet metal applications, the deformation is invariably three dimensional with a combination of stretching and bending. For most sheet materials under these complex loading processes used in industry, strong Bauschinger effect is observed, and the material hardening behavior tends to be anisotropic. This study aims to understand and evaluate such anisotropic hardening effect on the forming limit prediction under stretch-bending condition. The extended through-thickness Marciniak–Kuczynski (M–K) analysis is incorporated with Yoshida–Uemori (YU) two-surface kinematic hardening constitutive model, which has a more accurate description of the reverse loading behavior than that of the conventional isotropic hardening model. The material parameters used in this paper for YU model are calibrated with the experimental data from uniaxial large-strain tension-compression cyclic test. Both the isotropic hardening and YU kinematic hardening models with Hill'48 yield surface are employed in the analysis for the purpose of comparison. The Forming Limit Average Stress Diagram (FLASD) under stretch-bending condition is proposed to extend the understanding of Forming Limit Stress Diagram (FLSD) from in-plane to out-of-plane deformations. The “bending-ratio-dependent” phenomenon in forming limit diagram is predicted and observed in both stress/strain space with the proposed method. It suggests that the individual stress/strain state cannot represent system behavior. Forming limits under stretch-bending is suggested as an occurrence of system instability, not individual material instability. The system behavior of sheet metal deformation is reinforced as critical to the understanding of necking instability in stretch bending processes. The analysis shows that the Bauschinger effect provides positive effect in delaying the necking instability, predicting higher formability for sheet metals under stretch-bending. The insight obtained in this paper provides further understanding of the localized necking phenomenon under stretch-bending condition.

A new anisotropic material hardening model is introduced in this study for springback simulation. It is modified from the Mroz multi-yield surface hardening model and incorporated more realistic Bauschinger effect for cyclic loading and anisotropic yield surfaces for sheet metals. The model is targeted for sheet metal forming simulations where the accurate springback predictions are important, and where materials have more rapid hardening characteristics and ability to sustain higher stresses such as so-called advanced high-strength steels (AHSS). The constitutive integration algorithm is derived and it is numerically implemented in the commercial FEA code via a user-material subroutine. The new model is applied to a U-channel forming test with DP600 steel. Experiments are conducted and springback results are compared with numerical prediction to demonstrate the new model’s effectiveness.

Compared with the conventional steels, "shear fracture" is one of the main issues for advanced high strength steels (AHSS). Due to rolling, anisotropy is an intrinsic property for sheet metals. Not only the plastic responses of sheet metals but also the fracture strengths are orientation dependent. In the small radius forming process, for example, the stretch-bending deformation of sheet metals under small radius condition, the normal stress cannot be neglected. Three-dimensional loading condition constructs complex shear stress states of sheet metals especially the out-of-plane shear stress. The out-of-plane performance must be considered in order to better understand the "shear fracture" phenomenon of AHSS. Compared to in-plane shear test, the out-of-plane shear test is more difficult to carry out due to the severe restriction of the dimensions in the thickness direction. In this paper, a new specimen is presented for out-of-plane shear test. Failure of the specimen occurs in shear between two centrally located notches machined halfway through its thickness from opposing sides. Meanwhile, the finite element (FE) model and possible failure modes of this specimen are investigated in detail. At last, brief experimental results between out-of-plane shear fracture strength and the in-plane shear fracture strength are compared for DP980 sheets.

In this work, a multiscale modeling framework for CFRP is introduced to study hierarchical structure of CFRP. Four distinct scales are defined: nanoscale, microscale, mesoscale, and macroscale. Information at lower scales can be passed to higher scale, which is beneficial for studying effect of constituents on macroscale part’s mechanical property. This bottom-up modeling approach enables better understanding of CFRP from finest details. Current study focuses on microscale and mesoscale.