X-ray computer tomography based numerical modelling of fibre reinforced composites

Non-crimp fabric reinforced polymers are commonly used to manufacture the load carrying parts in wind turbine blades. Since wind turbine blades have a large material usage, the favourable stiffness to price ratio of non-crimp fabric reinforced polymers is highly attractive for manufactures. Additionally, they are easy to manufacture, which is essential for mould sizes of up to approximately 100 m. Smaller turbine blades up to 75 m use glass fibres, lager blades require carbon fibres to meet the stiffness requirements.\ua0Wind turbine blades are ever increasing in length since the generated power is proportional to the length squared. In addition to the challenge to reduce the material usage, longer blades demand higher stiffness. Furthermore, wind turbines are one of the man-made structures that have to endure the highest numbers of load cycles. Even though wind turbine blades are mainly loaded in tension there are compressive loads present on the leeward side of the blade. Those three main material requirements demand highly tailored high-performance materials. At the same time wind turbine manufactures are under a high cost pressure as governments all over the world are cutting subsidies. As for any other high-performance material a constant production quality is essential. However, in particular composites are susceptible for manufacture flaws.\ua0X-ray computer tomography allows for the detection of some of the defects present after manufacture. X-ray computer tomography is a very promising tool for materials quality control and quantification when combined with numerical modelling. In the last years the image acquisition and analysis process has seen enormous progress that can now be exploited.\ua0In this research project the X-ray computer tomography aided engineering (XAE) process has been established. XAE systemically combines all work-steps from material image acquisition to the final finite element analysis results. The process provides an automated, accurate and fast image analysis and an element-wise and integration point-wise material orientation mapping. The analysis of the detailed stress and strain distributions after manufacture with XAE will allow for more reliable and low-cost wind turbine blades

Image-based numerical modelling of heterogeneous materials

In science there has always been a desire to visualise the invisible. Since the discovery of X-rays in 1895, imaging research has made remarkable progress. Nowadays, state-of-the-art technology allows to visualise the micro-structure of objects in three dimensions. However, merely visualising the structure is often insufficient. The quantitative information regarding morphology and structure is of great interest. Therefore, in addition to significant advancements in X-ray image acquisition and three-dimensional reconstruction, image analysis has become an active research field in recent years. Modern image analysis methods enable to extract even invisible information from image data. The heterogeneous micro-structure of composites imposes advanced material characterisation as even for the largest composite structures, such as wind turbine blades or airplane wings, the material properties are dictated on the micro-scale. Image-based modelling offers exceptional capabilities in analysing the micro-structure at the fibre level and numerically predicting material behaviour even at larger scales. However, image-based modelling is a complex process and all work-steps must be in line with the final modelling goal. Therefore, X-ray computed tomography aided engineering has been introduced to emphasise the importance of a holistic point of view on the image-based modelling process. The developed X-ray computed tomography aided engineering methodology has been developed based on micro X-ray computed tomography scans for non-crimp fabric glass-fibre reinforced composites. It is demonstrated that local fibre orientations and fibre volume fractions can be accurately imaged and transferred onto a finite element model. Thereby, the tensile modulus of the scanned samples can be accurately predicted and possible stress concentration regions detected. However, conventional micro X-ray computed tomography presents a major drawback. Achieving the required high resolutions to visualise carbon or glass fibres, typically ranging between 5 to 20 μm, limits the scanning field of view, which remains in the millimetre range. This drawback is overcome with new approaches in image-based modelling involving advances in imaging and image analysis. Therefore, targeted approaches for accurate image-based modelling are presented which increase the possible scanning field-of-view of fibrous composites by up to three to six orders of magnitude

X-ray tomography based numerical analysis of stress concentrations in non-crimp fabric reinforced composites - assessment of segmentation methods

In this study two automated segmentation methodologies of an X-ray computer tomography based numerical analysis are compared. These are then assessed based on their influence on the stress distribution results of finite element models of glass fibre reinforced composites made out of non-crimp fabrics. Non-crimp fabrics reinforced composites are commonly used for wind turbine blades due to their high stiffness to weight ratio for the dominating bending load. Finite element modelling based on X-ray computer tomography allows the reduction of the cost and can accelerate the development process of the key material parameters of wind turbine blades. Recent research progress in the last years has laid the basis for such a procedure. Those processes must be easy applicable, fast and accurate. The main challenge in current methodologies is the segmentation part. The segmentation methods applied for this study have overcome this issue by being automated. This allows for a comparatively fast transfer from X-ray computer tomographic data to finite element results

X-ray computed tomography data structure tensor orientation mapping for finite element models - STXAE

Accurate modelling of fibre-reinforced composites requires anisotropic material models. Structure tensor analysis of X-ray 3D images has been shown to provide fast and robust estimation of local structural orientations in fibre-reinforced composites. We present two mapping algorithms which can be used to map estimated local orientations onto finite element models for more accurate material modelling. The two functions allow for element-wise and integration point-wise mapping, respectively, and have been implemented using Python in a Jupyter notebook. Together with the previously published structure tensor code, these two functions demonstrate the concept of Structure Tensor X-ray computed tomography Aided Engineering (STXAE) (Phonetics: [stekseɪi:])

Robust numerical analysis of fibrous composites from X-ray computed tomography image data enabling low resolutions

X-ray computed tomography scans can provide detailed information about the state of the material after manufacture and in service. X-ray computed tomography aided engineering (XAE) was recently introduced as an automated process to transfer 3D image data to finite element models. The implementation of a structure tensor code for material orientation analysis in combination with a newly developed integration point-wise fibre orientation mapping allows an easy applicable, computationally cheap, fast, and accurate model set-up. The robustness of the proposed approach is demonstrated on a non-crimp fabric glass fibre reinforced composite for a low resolution case with a voxel size of 64 μm corresponding to more than three times the fibre diameter. Even though 99.8% of the original image data is removed, the simulated elastic modulus of the considered non-crimp fabric composite is only underestimated by 4.7% compared to the simulation result based on the original high resolution scan

Robust numerical analysis of fibrous composites from X-ray computed tomography image data enabling low resolutions

X-ray computed tomography scans can provide detailed information about the state of the material after manufacture and in service. X-ray computed tomography aided engineering (XAE) was recently introduced as an automated process to transfer 3D image data to finite element models. The implementation of a structure tensor code for material orientation analysis in combination with a newly developed integration point-wise fibre orientation mapping allows an easy applicable, computationally cheap, fast, and accurate model set-up. The robustness of the proposed approach is demonstrated on a non-crimp fabric glass fibre reinforced composite for a low resolution case with a voxel size of 64 μm corresponding to more than three times the fibre diameter. Even though 99.8% of the original image data is removed, the simulated elastic modulus of the considered non-crimp fabric composite is only underestimated by 4.7% compared to the simulation result based on the original high resolution scan

Sub-voxel based finite element modelling of fibre-reinforced composites

For fibre-reinforced composites, most of their mechanical properties is tied to the fibre scale. Thus, imaging-based characterisation demands resolving fibres to characterise these materials accurately. However, high resolutions limit the field of view and lead to lengthy acquisition times. Emerging non-destructive imaging technologies and algorithms now accurately provide fibre orientations without detecting individual fibres. Studies show that voxel sizes up to fifteen times the fibre diameter are feasible, still allowing accurate tensile modulus predictions. Our presented software incorporates sub-voxel fibre orientation distributions using ultra-low-resolution three-dimensional X-ray tomography data in a numerical model, providing an effective method for characterising these materials

Dataset of non-crimp fabric reinforced composites for an X-ray computer tomography aided engineering process

This data in brief article describes a dataset used for an X-ray computer tomography aided engineering process consisting of X-ray computer tomography data and finite element models of non-crimp fabric glass fibre reinforced composites. Additional scanning electron microscope images are provided for the validation of the fibre volume fraction. The specimens consist of 4 layers of unidirectional bundles each supported by off-axis backing bundles with an average orientation on \ub180\ub0. The finite element models, which were created solely on the image data, simulate the tensile stiffness of the samples. The data can be used as a benchmark dataset to apply different segmentation algorithms on the X-ray computer tomography data. It can be further used to run the models using different finite element solvers