Summary
Composite materials are high-performance engineering materials increasingly used by the aerospace, defence, and green-energy industries in part because of their high strength-to-weight ratios. However, internal damage represents one of the most important sources of concern for in-service performance, which has led to growing research interest for its implications in safety and maintenance cost. Realtime measurements of the structural performance are now possible through state-of-the art structural health monitoring techniques, and a large amount of response data can be readily acquired and further analysed to assess various health-related properties of structures. Due to the relative low cost of digitalisation technologies in relation to the operation and maintenance costs of composite structures, the amount of real-time data and information coming from monitored in-service structures is expected to increase exponentially over the coming decades. The research vision of this proposal is that this information has the potential to not only reduce by billions the expenditure on asset maintenance, but also to drastically change the way the composite structures (and their associated assets) are designed, built and operated. ENHAnCE's ambition is to produce a paradigm shift on the health management of composite structures by fusing ad-hoc predictive technologies within the structural system leading to a new concept of intelligent structures understood as cyber-physical systems. With ten employed Early Stage Researchers, ENHAnCE will perform the most cutting edge research and training in the field of intelligent prognostics of composite structures satisfying all Principles for Innovative Doctoral Training. Moreover, the direct industrial engagement through six industrial partners will ensure a multidisciplinary and multisectoral training for the ten employed Early
Stage Researchers, thus enabling an effective knowledge and training transfer to industry and practitioners.
Stage Researchers, thus enabling an effective knowledge and training transfer to industry and practitioners.
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More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/859957 |
Start date: | 01-01-2020 |
End date: | 30-06-2024 |
Total budget - Public funding: | 2 670 089,76 Euro - 2 670 089,00 Euro |
Cordis data
Original description
Composite materials are high-performance engineering materials increasingly used by the aerospace, defence, and green-energy industries in part because of their high strength-to-weight ratios. However, internal damage represents one of the most important sources of concern for in-service performance, which has led to growing research interest for its implications in safety and maintenance cost. Realtime measurements of the structural performance are now possible through state-of-the art structural health monitoring techniques, and a large amount of response data can be readily acquired and further analysed to assess various health-related properties of structures. Due to the relative low cost of digitalisation technologies in relation to the operation and maintenance costs of composite structures, the amount of real-time data and information coming from monitored in-service structures is expected to increase exponentially over the coming decades. The research vision of this proposal is that this information has the potential to not only reduce by billions the expenditure on asset maintenance, but also to drastically change the way the composite structures (and their associated assets) are designed, built and operated. ENHAnCE's ambition is to produce a paradigm shift on the health management of composite structures by fusing ad-hoc predictive technologies within the structural system leading to a new concept of intelligent structures understood as cyber-physical systems. With ten employed Early Stage Researchers, ENHAnCE will perform the most cutting edge research and training in the field of intelligent prognostics of composite structures satisfying all Principles for Innovative Doctoral Training. Moreover, the direct industrial engagement through six industrial partners will ensure a multidisciplinary and multisectoral training for the ten employed EarlyStage Researchers, thus enabling an effective knowledge and training transfer to industry and practitioners.
Status
SIGNEDCall topic
MSCA-ITN-2019Update Date
28-04-2024
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