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Test bed description

Material characterisation is a subject taught in all Engineering courses and provides designers with information about the properties and behaviour of materials. Obtaining reliable data is however a hard and involved lab-based activity, not accessible to most engineering students. AI and augmented reality/virtual reality applications can help to bridge this gap, as well as deliver reductions in the cost of material characterisation. Recent research at the OXR Hub in AI has already started to demonstrate the benefits of this approach.

The project's aim is to pilot the use of data-driven AI material modelling, and to put into educators’ hands a data-mining tool that solves real-life problems. To transfer and consolidate this knowledge into best engineering practice, the University is building a computing facility to support the AI workflow within teaching rooms. The focus is on lightweight materials for engineering applications, and success is measured in terms of the cost reduction of material modelling.

PIs: Mattia Montanari, Nik Petrinic

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