This thesis addresses a novel finite element study in machining of long-fibre-reinforced polymers (LFRP). For this sake, the development of sophisticated Fortran VUMAT user-subroutines is performed to insert a new composite damage algorithm in the modelling of composite machining, which accounts for damage propagation and chip fracture. These damage algorithms are based on continuous damage mechanics (CDM) theory linked to fracture computational techniques to simulate damage propagation, while chip fracture is induced using wisely strain-based element deletion criteria.
The modelling of two main topics in composite machining have been investigated during this research: composite cutting basics (machining induced damage and chip formation) and tool wear influence in machining forces.
The influence of cutting tool morphologies and material in the machining induced damage in composite was investigated using a novel method of inserting the spring-back phenomenon in the numerical analysis. Significant conclusions are extracted from this research. For instance, high relief angles reduce the sub-surface damage, or the tool wear incidence is found not to be critical in the studied range.
The following step was the modelling of chip formation mechanisms in composite machining. It was achieved by inserting a strain-based element deletion algorithm in the user-defined finite element (FE) code to allow chip fracture. The numerical assessment of sub-surface damage and chip formation was performed, implementing a strain-based continuum damage mechanics (CDM) approach. The study of five common machining configurations was addressed to model the governing chip fracture mechanism for several fibre orientations. This factor would include substantial improvements in the accuracy of the oncoming works.
Finally, a common composite edge trimming operation is successfully modelled to prove the damage algorithm's versatility. Edge trimming has barely been modelled so far because of its complexity and high computational cost required. It was developed an FE model to predict the tool wear influence on the machining forces' increment. Interesting technical applications could be achieved using this FE model. For instance, it could detect the point where the tool should be replaced by just checking the machining forces saving manufacturing time and optimising its use.
