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SAFE-10-T

financed

Safety of Transport Infrastructure on the TEN T Network

The SAFE-10-T project will develop a Safety Framework to ensure high safety performance while allowing longer life-cycles for critical infrastructure across the road, rail and inland waterway modes. Moving from considering critica... see more

30/04/2020

GDG

3M€

Project Budget: 3M€

Project leader

GAVIN AND DOHERTY GEOSOLUTIONS LTD No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

PARTICIPATION DEPralty Sin fecha límite de participación.

Ver 15 Participantes

Financing granted El organismo H2020 notifico la concesión del proyecto The day 2020-04-30

MG-3.4-2016: Transport infrastructure innovation... Specific Challenge:Infrastructure plays a vital role in increasing transport safety levels, in parti...

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

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15 Participantes

GDG

302.50K€ | Leader

FUCHO SOCIEDAD LIMITADA

338.83K€ | participant

HZ INFRA

26.25K€ | participant

DFKI

182.50K€ | participant

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Project duration: 36 months Date Start: 2017-04-04
End date: 2020-04-30

Project leader

GAVIN AND DOHERTY GEOSOLUTIONS LTD No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Project Budget 3M€

participation deadline Sin fecha límite de participación.

Project description The SAFE-10-T project will develop a Safety Framework to ensure high safety performance while allowing longer life-cycles for critical infrastructure across the road, rail and inland waterway modes. Moving from considering critical infrastructure such as bridges, tunnels and earthworks as inert objects to being intelligent (self-learning objects) the SAFE-10-T project will provide a means of virtually eradicating sudden failures. This will be achieved by: • The Safety framework will incorporate remote monitoring data stored in a BIM model that feeds into a decision support framework (DST) that enables decisions to be made automatically with maintenance prioritised for elements exhibiting stress. • A major advance that will be achieved in the project is that the algorithms at an object level and at a network level will incorporate machine learning to train the system to evolve with time using available monitoring data. • A trans-disciplinary approach with experts in Artificial Intelligence and big data management working with owners, engineers with expertise in risk and modelling and sociologists to make decisions. • Our major European infrastructure managers (Rijkswaterstaat for roads and inland waterways and Network Rail) will undertake demonstration projects at critical interchanges and nodes of the TEN-T transport network. The project will achieve significant impact in asset management by: (i) By moving to intelligent objects that communicate their safety condition during extreme events we will provide a means of virtually eradicating sudden catastrophic failure of infrastructure objects. (ii) The project will use Open Linked Data formats to manage all data and inputs from other sources. Mitigation actions can be taken and warnings of the increased risk level can be transmitted to other agencies and the public. (iii) Demonstrate the concept of fully interconnected transport networks on the TEN-T

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