Abstract

Presentation held at the second public workshop of the FIBRESHIP project, held at La Ciotat, France, on 25th of June 2019.

The second public workshop of the FIBRESHIP project offered to the participants a chance to discuss the different composite materials solutions for shipbuilding as well as learn more about the latest technological advances of FIBRESHIP Project related to design, construction and operation of ships integrally built in composite materials. FIBRESHIP Consortium is looking for a niche in the future shipping market through promoting changes in the regulatory framework of IMO and generating guidelines and methodologies for designing, building and operating large-length vessels, laying the foundations of a new market based on composites technology in shipbuilding and shipping.

This presentation explains the development of a new software suite with a wide variety of ad-hoctools to simulate the structural and fire performance of the lightweight composite ships developed within the FIBRESHIP project. The computational analysis tool is based on a fast-numerical software which can be used for the simulation of fatigue, fire diagnosis, thermal propagation, hydro-structural analysis and so on. A Betha version of the developed software suite of this numerical tool is available for the partners of the project.

Abstract

Abstract

Fiber optic sensors, both FBG point sensors and distributed sensors based on OFDR, are accepted and validated as temperature and strain sensors, enjoy a high TRL and are already in use in many industrial applications. The determination of occurrence of damage from strain measures is a technique still not mature, its TRL can be 2-3. A local crack can greatly weaken a structure, it will be the point of initiation of the catastrophic failure, but until the failure has occurred, the crack only causes very small changes in the overall behavior of the structure (stiffness, natural frequencies, strain field, etc.). Therefore, and unless the position of the crack coincides with the predetermined position of the sensors, it is not easy to detect the existence of damage from strain measurements. In this work two parallel techniques, experimentally validated, are presented. The first one is to use distributed measurement, with an optical fiber placed in the area where the damage is expected. It is verified that a delamination causes residual strains in the delaminated area, of  significant value, and that will be detected by the fiber, if it crosses the delamination zone. The second technique is to compare the strains measurements obtained at different points, when the structure subjected to external loads. Although the changes are going to be very small, local damage causes a redistribution of the rigidity of the structure, and of the load paths, and therefore the strains readings, may be slightly different. Results of the application of the model are presented to actual composite elements, such as an isogrid structure, and a small wind turbine blade.

Abstract

The RPAS (Remote Piloted Air System) MILANO is the largest unmanned aerial system developed by INTA that aims to become a research platform capable of carrying out in-flight tests with many scientific payload, thus complementing the Air Research Platforms (PAIs) of INTA. At the structural level, the RPAS MILANO is made in its entirety in carbon / epoxy composite material that is cured out of the autoclave. Its design has been followed by the airworthiness regulations applicable to the aircraft type (STANAG-4671). In the month of December 2018, the RPAS MILANO flight test phase began and it’s Health and Usage Monitoring System (HUMS) is being used to collect data before, after and during flights, providing very useful information when evaluating and analyzing the state of the structure and the possible appearance of structural overloads not foreseen during the mission. Information about special events, such as forced landing or burst loading, can be provided to maintenance operators after each flight. The simulation model and its predictions have been validated in a real structure of the rear fuselage of the MILANO and in which real damage of larger sizes is introduced by eliminating rivets progressively. In our study, three different damage detection algorithms are used, based on a damage index, PCA and Artificial Neural Networks (ANN).

Abstract