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The fatigue behaviour of a biaxial carbon/epoxy Non-Crimp-Fabric (NCF) composite is evaluated at room temperature and 130o C for automotive applications. A new specimen geometry is developed allowing three stress ratios R = 0.1, R = −1 and R = 10 to be tested at 130o C without the use of anti-buckling fixtures for axial loadings. The three stress ratios show good agreement in fatigue life using an equivalent stress amplitude. The fracture surfaces from failed fatigue test specimens are compared to those of monotonic loading to evaluate the changes to failure modes under the different loading conditions. Tensile dominated loading such as uniaxial tension and fatigue testing with R = 0.1 result in delamination of the NCF material coupled with fibre failure along the loading direction as the primary failure modes. Compressive fatigue failures at 130 °C occur at an inclined angle through thickness due to a shearing process along with fibre kinking. The matrix material exhibits more ductile characteristics at 130o C altering the fracture surfaces at elevated temperature.

This is the first of two manuscripts that presents a computationally efficient full field deterministic model for laser powder bed fusion (LPBF). A new Hybrid Line (HL) heat input model integrates an exponentially decaying (ED) heat input over a portion of a laser path to significantly reduce the computational time. Experimentally measured properties of the high gamma prime nickel-based superalloy RENÉ 65 are implemented in the model to predict the in-process temperature distribution, stresses, and distortions. The model accounts for specific properties of the material as different phases. The first manuscript presents the HL heat transfer model, which is compared with the beam-scale exponentially decaying model, along with the melt pool geometry obtained experimentally by varying the laser parameters. The predicted melt pool geometry of the beam-scale ED model is shown to have good agreement with experimental measurements. While the proposed HL model exhibits lesser accuracy in predicting the melt pool geometries, it can predict the cooling rates and nodal temperatures as accurately as to the ED model. Moreover, under large time integration steps, the HL model becomes more than 1,500 times faster than the ED model.

Facing the stringent requirements for fuel economy in automotive industry, composite materials are seen to be utilized for structural lightweighting. This paper focuses on the fatigue test development and fatigue behavior of a biaxial [0/90] carbon/epoxy non-crimp fabric composites for automotive applications. A new fatigue test specimen was successfully developed for fatigue testing under fully reversed loading, i.e. stress ratio R=-1, at room temperature and 130 ℃. The developed test specimen prevents buckling during testing without use of an anti-buckling fixture. 3D Digital image correlation strain mapping also revealed a uniform strain distribution on the surface of this specimen geometry. Fatigue test results indicate that the fatigue behavior at both room temperature and 130 ℃ is matrix dominated. The fatigue data is a good fit to the Basquin equation σa=σf(2N)b.

Phenomenological models are required to predict the behaviour of a glass fibre reinforced Sheet Moulding Compound (SMC) composite material for use in the automotive industry. Material testing is conducted in tension, compression, in-plane shear, and three-point bending. The SMC composite exhibits tension-compression asymmetry and in-plane anisotropy. A model, which incorporates an anisotropic and asymmetric yield function, is developed. The model is calibrated to the experimental tension, compression and in-plane shear tests and are validated using the three-point flexure test. The model captures the flexure response within 8.1% of the experimental observations. The importance of including tension compression asymmetry within the model is demonstrated.

Discontinuous fiber reinforced polymers (DicoFRP) like Sheet Molding Compounds (SMC) are frequently applied in modern lightweight designs, due to their good formability and mechanical properties at low density. The DicoFRP microstructure affects the mechanical properties and has to be taken into account in the design process. X-ray Micro-Computed Tomography (μCT) systems acquire volumetric images of microstructures in a non-destructive way. The fiber orientation is determined by using state-of-the-art image processing tools. The resolution of volumetric images and the specimen size are directly coupled due to the cone-beam μCT geometry. In order to identify all individual fibers, high resolution images are needed and consequently, only small specimen volumes are scanned. The present contribution makes use of the property that fibers are arranged as bundles within SMC. Consequently, fiber bundles instead of individual fibers are used to analyze microstructures in order to overcome the μCT-cone-beam-related conflict between sample size and image resolution. The fiber bundles are determined by means of orientation data and an introduced tracking method, facing the challenge of crossing fiber bundles. Subsequently, the tracked fiber bundles, which are related to the same mesoscopic fiber bundle are merged by using a hierarchical agglomerative clustering method. The presented method is applied to a typical SMC microstructure. This contribution introduces an image processing method for analyzing SMC microstructures based on fiber bundles, opening up the possibility to investigate large specimen volumes. This enables to characterize representative SMC microstructures and utilize the data for art modeling approaches.

The effect of fibre length distribution on the fatigue behaviour of an injection-moulded PA66 carbon fibre composite is investigated. Two materials, short carbon fibre with a mean length of 100 microns, and long carbon fibre with a mean length of 580 microns, are subjected to fully reversed fatigue loading at room temperature and three stress ratios at 120 °C. The fatigue results are compared, and fracture surfaces are analyzed to determine the differing failure modes between the materials and loading conditions. At 120 °C, the fibre length has a significant effect on the fatigue behaviour with order of magnitudes of different fatigue life for a given stress amplitude during tensile fatigue loading. Under tensile loading, fatigue failure initates as fibre matrix debonding with pits present due to end effects in the short carbon fibre material. Under compression–compression loading, the fatigue life is matrix-dominated and should be treated as a maximum stress failure. Under this loading, a smooth crack propagates across the sample with buckling as the final failure mode.

A more efficient integrated computational approach for the design of injection and compression moulded composites which maps the results of manufacturing simulations as input to structural simulations is proposed. This methodology overcomes the limitations caused by insufficient detail provided by the second order fibre orientation tensor (FOT) output from manufacturing simulations which are needed in advanced structural finite element models that incorporate damage and failure. An artificial neural network (ANN) framework is proposed to predict a fibre orientation distribution function (ODF) from the FOT. The ANN contains the equation for calculating the FOT from the ODF such that the ODF is optimized to reproduce the input FOT. It is shown that the proposed framework is nearly as accurate as using experimentally measured ODF for predicting the stress strain response and failure of a compression moulded composite.

Fatigue characterization of injection moulded carbon fibre is conducted on specimens from ten locations on a flat plaque and two locations from an automotive oil pan. Fatigue testing was carried out using tension–tension and fully reversed loading at room temperature and 120 °C using the specimens from the flat plaques. The stiffness and microstructure of the ten locations are used to calibrate a micromechanics model to evaluate the maximum interface stress for the stresses applied during the fatigue tests. Using the peak interface stress as a failure criteria is proposed and verified by the reduction in variability in the fatigue results. The model is validated on the data set for the two automotive component locations under fully reversed loading at 120 °C.

A unit cell model is developed to capture the elasto-visco-plastic response of a long fibre composite using a 3-dimensional finite element model. Using a glass rubber model, the elasto-visco-plastic response of the matrix is analysed and the fibre is considered to deform elastically. A functionally graded interphase zone is defined in the region surrounding and encompassing a reinforcing fibre. The model subdivides the interphase zone into an infinite number of concentric rings where stress and strain compatibility is preserved. This model aims to improve on the computational efficiency of micromechanics models where the fibre and matrix are modeled as separate materials. The mechanics of the fibre deformation are governed by a transformation tensor for transversely isotropic materials based on Eshelby’s method. The model is calibrated using experimental data for the transverse compression of a unidirectional composite; it is then validated using axial compression and shear data for quasi static strain rates. For moderate strain rate the model is also calibrated for one of the transverse strain rates then validated using the other strain rates and axial compression. The proposed unit cell model is capable of predicting the elasto-visco-plastic response of long fibre composites to a very high accuracy.

A unit cell model based on the interaction between the fibre and a matrix at the micromechanics scale for a long fibre reinforced composite is developed. An interphase zone is defined to describe the load transfer between the fibre and matrix. The interphase zone has functionally graded properties, and occupies a region including the physical boundary between the fibre and matrix. Material paring constants k and l are introduced to define the size of the interphase zone, independent of the volume fraction of reinforcement for a given set of materials. This model allows the prediction of the average stress in the composite as well as the constituents.

A micromechanics model that utilizes microstructural characteristics for predicting the bending stress-strain response of a SMC composite is presented. The model integrates matrix, interphase and fibre damage models to form a framework that is able to accurately represent the damage response of the SMC using a single parameter damage model that is equivalent to the von mises interfacial stress. This is a valuable capability given the inherent random nature of SMC properties. Before being subjected to three-point bending tests, three SMC samples from different areas of a molded plate were characterized using X-ray computed tomography. The through thickness properties such as fibre orientation and volume fraction were characterized for multiple layers and then used as input data for a finite element model to predict the stress-strain behaviour. It was found that prediction accuracy increased with more layer properties. The model was able to represent the stress strain results within 2% of the experimentally measured response using 12 microstructural layers for a 2.8 mm thick specimen.

The material properties of compression moulded composites depends on the fibre orientation within a component, which changes as a function of position due to the flow of the material during the manufacturing process. Existing analytical tools are incapable of capturing all of the underlying physics of the problem involving long fibres which deform and interact with one another during the flow process. Artificial neural networks are used to predict the fibre orientation within a compression moulded composite by training the network on fibre orientation data. The fibre orientation data was produced using X-ray micro computed tomography measurements. The proposed artificial neural network framework is able to predict the orientation of the in plane orientation tensor normal components within 0.103 and the through thickness orientation tensor normal component within 0.0095 which is lower than the variability orientation of neighbouring microstructural units. Once trained the artificial neural network framework allows for near instantaneous predictions of fibre orientation presenting an opportunity for increased efficiency of the virtual design process of compression moulded composite materials.

For predicting the mechanical response of mis aligned short fibre composite materials a two step homogenization procedure coupled with orientation averaging of the elastic material properties is often used. Orientation averaging is not valid for long fibre composites due to non-symmetric strain localization tensors. A method to homogenize the stress for mis aligned long fibre composites using the Functionally Graded Interphase (FGI) approach is presented and the results are compared to two step Mori Tanaka homogenization. The microstructure of long fibre Sheet Moulding Compound (SMC) composite is evaluated using X-ray micro computed tomography. The measured fibre orientation distributions are used to evaluate the number of representative fibre orientations required to predict the stress state of the SMC due to applied strains. It is found that 60 orientations are required to capture the stress response of the long fibre SMC composite using the FGI model and two step Mori Tanaka model.

In order to improve the predictive accuracy of homogenized micro mechanics models the strain partitioning between the fibres and the matrix must be accurate. Early homogenization schemes are only applicable for elastic deformations of composites; however, it has become important to be able to predict the response of composite materials up to the point of failure to improve the design of lightweight structural composite structures. Approaches to improve the strain partitioning for homogenized schemes where the material undergoes elasto-viscoplastic response are discussed. For complex polymer materials models where the composite has an elastic fibre which is perfectly bonded to the matrix it is proposed that the fibre strain is related to the recoverable elastic strain of the matrix material. Simulation results are shown for a unidirectional carbon fibre epoxy composite at various strain rates under transverse loading.

The second order fibre orientation tensor has been used to predict the mechanical response of injection and compression moulded composites with the capability to couple mould filling with structural finite element simulations to account for the microstructure. In order to accurately model these materials the mesh size used simulations must be representative of the actual microstructure of the composite. Herein a method to determine the microstructure size required to achieve a near constant value of the orientation tensor based on its derivative is presented. The method is demonstrated with the microstructure of a sheet moulding compound composite which has been evaluated using X-ray micro computed tomography. The average values of the derivative of the orientation tensor and its standard deviation approach constant values with increasing microstructure size. For the material considered a microstructure size of 5 mm square is sufficient to achieve a near constant value of the fibre orientation tensor, which is called a microstructural unit.