Environmentally friendly and energy efficient pultrusion

该项目的目的是开发一种环保的新型拉挤技术，并允许对新型快速固化树脂体系进行评估。在传统工艺中，将增强纤维浸渍在树脂浴中，然后通过加热模具使树脂交联并形成拉挤部件。在新的制造技术中，树脂的成分将存储在单独的容器中，并使用定制设计的液体输送系统按需泵送。使用注射头和电流体动力雾化的新组合，以及使用机械和静电技术的纤维扩散，将实现纤维的高效浸渍。当前提案的背景是EPSRC/DTI关于清洁纤维缠绕的项目的成功完成，该项目展示了无需使用树脂浴即可注入增强纤维的技术。然而，在目前的项目中，将为拉挤工艺开发新技术，在不使用传统树脂浴的情况下，将浸渍多达20个单独的纤维束。本文将对快速固化树脂的固化动力学进行评价，并采用适当的模型预测铺展纤维束的浸渍率。先前开发的光纤传感器将用于实现实时化学过程监控和服役中的结构完整性评估。将使用生命周期评估和生命周期成本分析来评估这种新制造技术的绿色证书。

The aim of this project is to develop a new pultrusion technique that is environmentally friendly and one that permits new and fast-curable resin systems to be evaluated. In the conventional process, the reinforcing fibres are impregnated in a resin bath and then passed through a heated die to cross-link the resin and to shape the pultruded component. In the new manufacturing technique, the components of the resin will be stored in separate containers and pumped on-demand using a custom-designed liquid delivery system. Efficient and effective impregnation of the fibres will be achieved using a novel combination of an injection-head and electro hydrodynamic atomisation, and fibre spreading using mechanical and electrostatic-based techniques. The background to this current proposal is the successful completion of an EPSRC/DTI project on Clean Filament Winding where the technology for injecting the reinforcing fibres without the use of a resin bath was demonstrated. However, in the current project, new technology will be developed for the pultrusion process where up to 20 individual fibre bundles will be impregnated without using a conventional resin bath. The cure kinetics of the fast-curing resins will be evaluated and appropriate models will be used to predict the impregnation rates for the spread fibre bundles. Previously developed fibre optic sensors will be used to enable real-time chemical process monitoring and structural integrity assessment in-service. The green credentials of this new manufacturing technique will be assessed using life cycle assessment and life cycle cost analysis.