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behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help of the simulation tool To support in the development and
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dynamics resulting from varying compositions. An adaptive Model Predictive Control strategy is envisaged for this challenge. During the four-year doctoral programme, you will contribute to the group's R&D
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composites. Position 1 – Ply and blank bending during hot press forming Wrinkling is one of the primary process-induced defects in press-formed thermoplastic composite parts. Predicting wrinkling requires
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coexisting phases, one can model their distribution during magmatic processes, and crucially the locations within pegmatite mineral systems that are predisposed to form lithium mineralisation. We currently
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of the primary process-induced defects in press-formed thermoplastic composite parts. Predicting wrinkling requires accurate constitutive models for the bending behavior of molten reinforced thermoplastic plies
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laboratory is organized into four research groups: - MSC Group: Composite Materials and Structures - SUMO Group: Surface, Machining, Materials, and Tools - MS2M Group: Modeling of Mechanical Systems and
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9 Oct 2025 Job Information Organisation/Company Ghent University Department Materials, Textiles and Chemical Engineering Research Field Chemistry » Organic chemistry Computer science » Modelling
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corrosion-fatigue conditions by integrating multiscale physics-based models combined with mesoscale experimental tests. This research will study the effects of corrosion-induced changes in composition
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Wrinkling is one of the primary process-induced defects in press-formed thermoplastic composite parts. Predicting wrinkling requires accurate constitutive models for the bending behavior of molten reinforced
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partner You will combine laboratory-based analytical work with modelling approaches to identify trends in material composition, chemical presence, and contamination across the product lifecycle