| 1. |
- Auenhammer, Robert, 1991, et al.
(författare)
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Automated X-ray computer tomography segmentation method for finite element analysis of non-crimp fabric reinforced composites
- 2021
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Ingår i: Composite Structures. - : Elsevier BV. - 0263-8223. ; 256
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Tidskriftsartikel (refereegranskat)abstract
- In this study a complete procedure is presented of how to generate finite element models based on X-ray computer tomography data on the fibre bundle scale for non-crimp fabric reinforced composites. Non-crimp fabric reinforced composites are nowadays extensively used in the load carrying parts of wind turbine blades. Finite element analysis based on X-ray computer tomographic data will allow faster and cheaper developments of key material parameters. However, automated procedures for computer tomography data transfer into finite elements models are lacking. In the current study, an X-ray computer tomography aided engineering (XAE) process including a fully automated segmentation method and an element-wise material orientation mapping of X-Ray computer tomographic data is presented for the first time. The proposed methodology combines recent research progress and improvements in image analysis, and provides a fast, accurate and repeatable data transfer and analysis process with a high degree of automation.
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| 2. |
- Auenhammer, Robert, 1991, et al.
(författare)
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Dataset of non-crimp fabric reinforced composites for an X-ray computer tomography aided engineering process
- 2020
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Ingår i: Data in Brief. - : Elsevier BV. - 2352-3409. ; 33
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Tidskriftsartikel (refereegranskat)abstract
- 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 ±80°. 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.
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| 3. |
- Auenhammer, Robert, 1991, et al.
(författare)
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Fibre orientation distribution function mapping for short fibre polymer composite components from low resolution/large volume X-ray computed tomography
- 2024
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Ingår i: Composites Part B: Engineering. - 1359-8368. ; 275
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Tidskriftsartikel (refereegranskat)abstract
- Short glass fibre injection moulded composites, used in interior and exterior automotive parts, are exposed to complex stress states, for example during a crash. As the fibre scale dominates the composite’s material properties, numerical models need to account for the local fibre orientation. In recent years, mould flow simulation results have been exploited to predict the fibre orientations for finite element models, albeit with limited accuracy. Alternatively, X-ray computed tomography can be used to directly image and analyse fibre orientations. Traditionally, achieving the necessary resolution to image individual fibres restricts the imaging to small regions of the component. However, this study takes advantage of recent advancements in imaging and image analysis to overcome this limitation. As a result, it introduces, for the first time, a reliable, fast, and automated fibre orientation mapping for a full component based on image analysis at the individual fibre level; even for cases where the pixel size is significantly larger than the fibre diameter. By scanning at lower resolutions, a drastically larger volume of interest can be achieved. The resulting fibre orientation analysis and mapping algorithm, based on X-ray computed tomography, is well matched to the level of information required for automotive crash modelling with a standard element-size of a few millimetres. The entire process, encompassing image acquisition, image analysis and fibre orientation mapping, can be directly integrated into an industrial full component application in a matter of hours.
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| 4. |
- Auenhammer, Robert, 1991
(författare)
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Image-based numerical modelling of heterogeneous materials
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 5. |
- Auenhammer, Robert, 1991, et al.
(författare)
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Robust numerical analysis of fibrous composites from X-ray computed tomography image data enabling low resolutions
- 2022
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Ingår i: Composites Science and Technology. - : Elsevier BV. - 0266-3538. ; 224:16 June 2022
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 6. |
- Auenhammer, Robert, 1991, et al.
(författare)
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Sub-voxel based finite element modelling of fibre-reinforced composites
- 2024
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Ingår i: Software Impacts. - 2665-9638. ; 21
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 7. |
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| 8. |
- Auenhammer, Robert, 1991, et al.
(författare)
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X-ray computed tomography data structure tensor orientation mapping for finite element models - STXAE
- 2022
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Ingår i: Software Impacts. - : Elsevier BV. - 2665-9638. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- 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:]).
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| 9. |
- Auenhammer, Robert, 1991
(författare)
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X-ray computer tomography based numerical modelling of fibre reinforced composites
- 2021
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- 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. Wind 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. X-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. In 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.
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| 10. |
- Auenhammer, Robert, 1991, et al.
(författare)
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X-ray scattering tensor tomography based finite element modelling of heterogeneous materials
- 2024
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Ingår i: npj Computational Materials. - 2057-3960. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- Among micro-scale imaging technologies of materials, X-ray micro-computed tomography has evolved as most popular choice, even though it is restricted to limited field-of-views and long acquisition times. With recent progress in small-angle X-ray scattering these downsides of conventional absorption-based computed tomography have been overcome, allowing complete analysis of the micro-architecture for samples in the dimension of centimetres in a matter of minutes. These advances have been triggered through improved X-ray optical elements and acquisition methods. However, it has not yet been shown how to effectively transfer this small-angle X-ray scattering data into a numerical model capable of accurately predicting the actual material properties. Here, a method is presented to numerically predict mechanical properties of a carbon fibre-reinforced polymer based on imaging data with a voxel-size of 100 μm corresponding to approximately fifteen times the fibre diameter. This extremely low resolution requires a completely new way of constructing the material’s constitutive law based on the fibre orientation, the X-ray scattering anisotropy, and the X-ray scattering intensity. The proposed method combining the advances in X-ray imaging and the presented material model opens for an accurate tensile modulus prediction for volumes of interest between three to six orders of magnitude larger than those conventional carbon fibre orientation image-based models can cover.
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