Concrete is a heterogeneous material with a disordered material morphology that strongly governs the behaviour of the material. In this contribution, we present a computational tool called the Concrete Mesostructure Generator (CMG) for the generation of ultra-realistic virtual concrete morphologies for mesoscale and multiscale computational modelling and the simulation of concrete. Given an aggregate size distribution, realistic generic concrete aggregates are generated by a sequential reduction of a cuboid to generate a polyhedron with multiple faces. Thereafter, concave depressions are introduced in the polyhedron using Gaussian surfaces. The generated aggregates are assembled into the mesostructure using a hierarchic random sequential adsorption algorithm. The virtual mesostructures are first calibrated using laboratory measurements of aggregate distributions. The model is validated by comparing the elastic properties obtained from laboratory testing of concrete specimens with the elastic properties obtained using computational homogenisation of virtual concrete mesostructures. Finally, a 3D-convolutional neural network is trained to directly generate elastic properties from voxel data.

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Age-related macular degeneration (AMD) is a disease that affects the macular region of the outer retina. AMD is characterized by the presence of large extracellular debris called drusen between the Bruch's Membrane (BrM) in the choroid and the retinal pigment epithelium (RPE) in the outer retina. An important feature of AMD is the degenerative changes in the RPE and the photoreceptors that leads to the deterioration and loss of central vision. In this contribution, the effect of drusen size on the morphological changes in the RPE, BrM and photoreceptors are investigated using the cellular potts model (CPM) and machine learning. Numerical simulation of the influence of drusen growth and its effect on the morphology of the outer retinal layers of the macula is presented and the implications for AMD progression discussed.

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