Summary
The training network NEWFRAC is a leading European research consortium composed by eight top university research teams and five high-tech companies. The high-level doctoral training offered by NEWFRAC to thirteen creative, entrepreneurial and innovative early-stage researchers is focused on new strategies for prediction and analysis of multi-field fracture phenomena in heterogeneous engineering systems at different scales. These researchers are developing new failure-predictive computational tools and apply them to relevant problems in strategic industrial sectors like Energy, Health and Transport. Their individual research projects address most relevant questions of current interest in failure prediction in heterogeneous systems, that will generate high-impact research outputs which go beyond the current state of the art in fracture modelling. To this aim, NEWFRAC integrates two new strategies for computational fracture modelling: Finite Fracture Mechanics and a variational approach to fracture referred to as Phase Field, and solves wide-ranging interconnected fundamental issues of fracture modelling like: fragmentation and dynamic crack propagation, toughening composites by micro- and meso-structural optimization, simultaneous crack initiation and propagation interacting with interfaces in: ultra-thin ply composites, curved laminates, injection molded fibre reinforced plastic, thermoplastics, layered ceramics, photovoltaics, solid oxide fuel cells and human bones, among others. NEWFRAC guarantees the attendance of early-stage researchers to all network-wide training activities, and favours their training through interdisciplinary and intersectoral research, mobility and exposure to industry, aiming at their transfer to industry after the network. These early stage researchers will become experts in fracture prediction in heterogeneous systems and will contribute to reduce the innovation gap by enhancing two ways academia-industry transfer of knowledge.
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| Web resources: | https://cordis.europa.eu/project/id/861061 |
| Start date: | 01-05-2020 |
| End date: | 31-10-2024 |
| Total budget - Public funding: | 3 359 824,20 Euro - 3 359 824,00 Euro |
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Original description
The training network NEWFRAC is a leading European research consortium composed by eight top university research teams and five high-tech companies. The high-level doctoral training offered by NEWFRAC to thirteen creative, entrepreneurial and innovative early-stage researchers is focused on new strategies for prediction and analysis of multi-field fracture phenomena in heterogeneous engineering systems at different scales. These researchers are developing new failure-predictive computational tools and apply them to relevant problems in strategic industrial sectors like Energy, Health and Transport. Their individual research projects address most relevant questions of current interest in failure prediction in heterogeneous systems, that will generate high-impact research outputs which go beyond the current state of the art in fracture modelling. To this aim, NEWFRAC integrates two new strategies for computational fracture modelling: Finite Fracture Mechanics and a variational approach to fracture referred to as Phase Field, and solves wide-ranging interconnected fundamental issues of fracture modelling like: fragmentation and dynamic crack propagation, toughening composites by micro- and meso-structural optimization, simultaneous crack initiation and propagation interacting with interfaces in: ultra-thin ply composites, curved laminates, injection molded fibre reinforced plastic, thermoplastics, layered ceramics, photovoltaics, solid oxide fuel cells and human bones, among others. NEWFRAC guarantees the attendance of early-stage researchers to all network-wide training activities, and favours their training through interdisciplinary and intersectoral research, mobility and exposure to industry, aiming at their transfer to industry after the network. These early stage researchers will become experts in fracture prediction in heterogeneous systems and will contribute to reduce the innovation gap by enhancing two ways academia-industry transfer of knowledge.Status
SIGNEDCall topic
MSCA-ITN-2019Update Date
28-04-2024
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