Characterization of flax fibres for application in the resin infusion process
Notice bibliographique
Résumé
Increasing concerns over depleting natural resources has led to the development of so-called biocomposites based on fibres from renewable resources such as flax. Although these fibres are seeing use in some applications, there is a lack of understanding concerning their processing requirements in relation to their unique physical and chemical properties. Furthermore, there is limited information regarding the links between their processing behaviour and mechanical performance. With the aim of addressing these missing links, this thesis presents a methodology for characterizing flax fibres for application in the resin infusion process and considers two important case studies with the overall goal of improving the state-of-the-art for this class of materials.Flax fibres were first characterized at the fibre level by advancing contact analysis, thermal gravimetric analysis, scanning electron microscopy and helium pycnometry. The advancing contact analysis revealed a reduction in the polar component of surface free energy after the application of silane and diluted epoxy treatments. A methodology was then developed for the characterization of the compaction and permeability of flax-based fabrics for the modelling of the resin infusion process. These parameters were quantified and used as input in a 1D process model that included capillary pressure. The model predictions for flow front evolution were shown to be in good agreement with experimental data. Alkaline treatments were shown to increase the required compaction pressure for a given porosity due to an increase in fibrillation. This had direct implications in the context of resin infusion processing due to the coupled nature of flow and compaction in this process. Consequently, a mechanical characterization revealed a decrease in flexural properties for alkaline-treated flax/epoxy composites manufactured by resin infusion due to a decrease in fibre volume fraction. A decrease in flexural properties was also noted with increasing void content.In an effort to improve the state-of-the-art for this class of materials, a case study was carried out on the incorporation of nano-modifiers in the resin infusion process. Nanocellulose was incorporated by two novel techniques; a 'grafting' method and a wet-layup method that incorporated an aqueous NC solution in the resin infusion pre-filling stage. Both methods were shown to lead to an increase in damage to the composites after subjection to a drop-weight impact event which suggested that the nano-modifier did not increase the interlaminar properties. However, an increase in interlaminar shear strength was observed by a short beam test due to an increase in fibre volume fraction as a result of softening and lubrication effects arising from the use of the aqueous NC solution.A second case study addressed the primary source of voids in a class of flax/epoxy prepregs which are generally used as a benchmark for composites manufactured by the resin infusion process. A series of compaction tests and thermal gravimetric analysis suggested that moisture and resin starvation were the primary source of voids in commercially available prepregs. Panels manufactured in an autoclave at varying pressures suggested that the latter of these issues was the dominant problem for the studied materials. The presence of voids was finally shown to lead to increased moisture sorption for flax/epoxy composites.This study stresses the coupled nature of the resin infusion process and the full implications of the use of chemical treated flax fibres. Additionally, it demonstrates the negative consequences of process-induced voids on the performance of flax/epoxy composites. It also provides useful data on the fibre surface chemistry, permeability, compaction and mechanical performance of flax-based composites. This assists in furthering the development of this class of materials with the goal of increasing their potential for use in load-bearing structures.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».