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SCOPE

Financiado

Cerrado

Self sensing Curved composite panel under Operational load methodology Platform...

Self sensing Curved composite panel under Operational load methodology Platform for prediction of damage Event "This proposal will develop SHM methodology platform, as outlined in JTI call JTI-CS-2012-3-GRA-01-051, for impact and damage detection in curved fuselage panels under real load conditions. The platform will be able to detect BIVI... ver más

14/05/2015

IMPERIAL COLLEGE O...

400K€

Presupuesto del proyecto: 400K€

Líder del proyecto

IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND ME... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2015-05-14 No tenemos la información de la convocatoria

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1 Participantes

IMPERIAL COLLEGE OF SCIENCE...

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Líder del proyecto

IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND ME... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 400K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto "This proposal will develop SHM methodology platform, as outlined in JTI call JTI-CS-2012-3-GRA-01-051, for impact and damage detection in curved fuselage panels under real load conditions. The platform will be able to detect BIVID and VID on sensorised fuselage panels. Different SHM methodologies will be established based on piezoelectric transducers and Fibre Optic sensors. To allow for numerical simulation of impact events and wave propagation, non-linear Finite Element models will be developed using SMART Elements to run in parallel on High Performance Computing units. Moreover advanced Message Passing Interfaces will be utilised to cope with large size of data handling. The SCOPE platform will have the following features: SMART computational methodologies to accurately simulate sensing and actuating in real-time under real dynamic load conditions; Passive sensing methodologies by generating meta-models based on sensor signals to detect and identify various impact events which are likely to occur during service life of aircraft; Active sensing techniques based on Lamb wave and Electromechanical Impedance to detect and characterise damage; An optimisation algorithm resulting in optimum sensor layout (i.e. number and location) using sensor data from SMART FE simulations; A robust and reliable sensor system by utilising SMART sensor models with self-diagnostic properties to reduce the Probability of False Alarm; Full non-linear impact analysis incorporating damage models for advanced composite to identify damage development and propagation; Statistical analysis of the developed methodologies to result in a robust and reliable SHM platform; To set test procedures for collecting SHM data; Multiple impact data for impact identification; Validation and calibration of the developed methodologies."

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