DOI: 10.5281/zenodo.6599213
title: Pre-Preg (PP) Manufacturing and Spring-in monitoring through FBGs, DCs and 3D CMM measurements

description: ELADINE project is aiming to implement a numerical tool that can reduce reoccurring costs of low-volume production in composite manufacturing of primary structural elements and thus reducing overall manufacturing effort and carbon emissions. A<strong> primary goal of this project is to eliminate tolerance non-compliancy in the manufactured structures caused by natural and unavoidable post-manufacturing distortions, typical for composite materials</strong>. These distortions might render otherwise qualitative components unusable due to their final geometry. Objectives of the Numerical model validation are: To understand the dominant factors which affects the spring-in phenomenon. To provide the simulation tool with the required values of the properties that influence on spring-in. To verify the simulation tool ability to predict spring-in for a variety of conditions. To develop a procedure of adapting and embedding sensors (dielectric and fiber optic) to obtain proper, useful and accurate signals of the manufacturing parameters (T, degree of cure, strain). To develop interpretation procedures of the signal/curves of sensors to obtain on-line process monitoring information. To obtain the data to feed and develop the numerical tool able to estimate the component distortions after its manufacturing, a combination of Fiber Optic Sensors (FOS) based on Fiber Bragg Grating (FBG) technology, Dielectric Curing sensors (DC) and 3D scanning were used to monitor the composite coupon manufacturing and the distortions the days after being demoulded. During the manufacturing process embedded FBGs and DC sensors were used to monitor the coupon temperature and strain distribution and resin curing evolution. After the manufacturing and the demolding, the distortions evolution were monitored by the embedded FBGs and by 3D CMM measurements. <strong>In the ELADINE project, the distortion monitoring was made to two Out-of-Autoclave manufacturing technologies: liquid resin infusion and oven cured Pre-Preg (PP)</strong>. For both material systems, slightly curved coupons and C-shaped coupons were the geometries selected as representative for the Skin and spars of the wing box. The Skin coupon was curved panel with a 1475 mm radius (with edge rise of 7,65 mm) that was thought to best replicate the wing profile geometry. The C-spar coupon geometry selected for the study was a non-tapered spar section with two different angle with radius of curvature of 5mm and 12mm. This geometry was chosen to simplify measuring and comparisons with wing demo. Furthermore, three different thickness are studied for the Skin coupons and two for the C-spar coupons which were selected from different zones along the wing. Moreover, a C-spar coupon with variable thickness was studied, as a simulation of the transition between zones with different thickness in the wing. <strong>In this dataset, the data obtained from the FBGs, DCs and 3D CMM meassurements during a PP manufacturing process and spring-in distortions monitoring can be found.</strong>
description: {"references": ["https://www.eladine-project.eu/index.html", "A. TORRE-POZA, A. M. R. PINTO, T. GRANDAL, N. GONZALEZ-CASTRO, L. CARRAL, & E. RODRIGUEZ-SENIN. (2021). Challenges of complex monitoring of the curing parameters in coupons for LRI manufacturing.https://doi.org/10.13111/2066-8201.2021.13.1.21", "A Torre-Poza, A M R Pinto, T Grandal, N Gonz\u00e1lez-Castro, L Carral, R Travieso-Puente, E Rodr\u00edguez-Sen\u00edn, C Banu, A Paval, M Bocioaga, (2021),ELADINE: sensor monitoring and numerical model approach for composite material wing box shape distortions prediction. IOP Conference Series: Materials Science and Engineering,.10.1088/1757-899x/1226/1/012001", "Tania Grandal, Ana M R Pinto, Andrea Torre Poza, & Noelia Gonz\u00e1lez-Castro. (2021). Liquid Resin Infusion (LRI) manufacturing and Spring_In monitoring by FBGs, DCs and 3D CMM meassurements (Version v0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5482076"]}