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The 14th International Conference on Industrial Computed Tomography

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The KU Leuven XCT Core Facility is excited to participate in the upcoming 14th international conference on industrial Computed Tomography (iCT), held on February 4-7, 2025 (Antwerp, Belgium). Jan Sijbers of the University of Antwerp: On behalf of the Organizing Committee, we would like to warmly welcome you to the 14th International Conference on Industrial […]

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Influence of Pore Network Parameters on Hygric Property Prediction for Porous Building Materials

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Abstract Hygric pore network modelling, which characterises the macroscopic moisture storage and transport properties by simulating the microscopic storage and transport of moisture in the pore elements of the pore network, is a novel method to characterise the hygric properties of building materials. To analyse, verify and/or compare pore networks, a wide array of parameters

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Material representativeness of a polymer matrix doped with nanoparticles as the random speckle pattern for digital volume correlation of fibre-reinforced composites

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Abstract Combining tomographic imaging with digital volume correlation allows in-situ 3D strain mapping, leading to a quantitative assessment of damage mechanisms and associated material properties in structural materials. Being based on pattern recognition, digital volume correlation is well-suited for materials with intrinsic and stable microstructural heterogeneity, such as certain biological tissues. Unfortunately, conventional polymers and

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Deep-learning image enhancement and fibre segmentation from time-resolved computed tomography of fibre-reinforced composites

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Abstract Monitoring the microstructure and damage development of fibre-reinforced composites during loading is crucial to understanding their mechanical properties. Time-resolved X-ray computed tomography enables such an in-situ, non-destructive study. However, the photon flux and fibre-matrix contrast limit its achievable spatial and temporal resolution. In this paper, we push the limits of temporal and spatial resolution

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Synthesising realistic 2D microstructures of unidirectional fibre-reinforced composites with a generative adversarial network

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Abstract The microstructure governs the behaviour of unidirectional fibre-reinforced composites. In this study, we developed a Deep Convolutional Generative Adversarial Network (DCGAN) to generate realistic 2D transverse microstructures of such composites. We evaluated the DCGAN-generated microstructures using three different methods: Fréchet inception distance, walking through the latent space, and feature matching. The results from these

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Fracture mode analysis of cementitious mortars by simultaneous application of 4D-XCT and acoustic emission technique

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Abstract Cementitious brittle construction materials are susceptible to fracturing due to their heterogeneous material composition and relatively weak bond between the aggregates and paste. Hence, enhanced methods of fracture analysis in these materials are an important subject of research. The acoustic emission technique (AET) is frequently used in the study of brittle construction materials, yet

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