863 research outputs found

    The Correlation framework: bridging the gap between modeling and analysis for 3D woven composites

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    International audienceA large variety of dierent descriptors can be employed for describing 3D woven composites. Each of them is targeted to a specic application, ranging from design, weaving, molding, impregnation down to non-destructive testing, imaging and numerical modeling of the actual micro-structure. In order to relate these dierent representations, it is proposed herewith to rely on the inherent weaving pattern as an intrinsic common feature, and to resort to images as a common language to guaranty the continuity of information. To connect these 3D images (either real or synthesized), Digital Volume Correlation (DVC) is called for in order to exploit the conservation of topology. A complete test scenario is devised in which dierent manufactured woven samples are compared to the theoretical textile arrangement. The results conrm the eectiveness of the method

    Image-based numerical modelling of heterogeneous materials

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    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

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

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    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

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    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

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

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    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

    Fiber identification of braided composites using micro-computed tomography

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    Braided composites contain interwoven fibers that are embedded in a matrix material. Advanced measurement methods are required to accurately measure and characterize braided composites due to their interwoven composition. Micro-computed tomography (μCT) is an X-ray based measurement method that allows for the internal structure of objects to be examined. High-resolution μCT of braided composites allows for their internal geometry to be accurately measured. Braid samples were measured with a voxel size of 1.0 μm3, which resulted in a field of view of 4.904 x 4.904 x 3.064 mm3. With this field of view, individual fibers within the braid yarns could be identified and measured. The scientific visualization software package Avizo and the XFiber extension was used to identify and measure braid yarn fibers from the collected μCT measurements. Fiber properties such as orientation angles (ϕ and θ), curved fiber length, tortuosity, and fiber diameter were obtained. Additionally, finite element mesh geometries of the braid yarns within a braided structure were created. The presented methodology provides a roadmap for the accurate modeling of braided composite unit cell geometries using high-resolution μCT data.Natural Sciences and Engineering Research Council (NSERC) Canada RGPIN- 2018-05899. CMC Microsystems provided the software used in this study
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