Any composite manufacturing method requires an application of a carefully designed consolidation process to ensure the suppression of voids in the laminate, establish bonding in laminate layers and prevent dimensional or fibre-path defects. The optimisation of consolidation processes relies on the characterisation of the composite precursors’ deformability. There are multiple mechanisms occurring in consolidation and various experimental programmes have been suggested in the literature to describe these mechanisms and deduce relevant material properties. The selection of a testing methodology often relies on an initial hypothesis or prior knowledge regarding the deformation modes. This may be a source of significant errors. This paper poses questions on the testing rationales, on subjectivity in material testing and on how data-rich programmes should be designed. Two approaches are suggested – the first one is a real-time adaptive testing strategy that enables a “conversation with the material” – flexible autonomous steering of a testing programme reacting on the obtained output. This framework focuses on the identification of the underlying physical mechanisms rather than material properties identification in a rightly or wrongly assumed flow mode. The second approach examines favourable combinations of tests to maximise information obtained whilst minimising the amount of testing. The obtained results highlight a way forward in terms of rethinking experiments for materials used in manufacturing and beyond.
|Number of pages||15|
|Journal||Composites Part A: Applied Science and Manufacturing|
|Early online date||23 Oct 2021|
|Publication status||E-pub ahead of print - 23 Oct 2021|
Bibliographical noteFunding Information:
This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) through the Centre for Doctoral Training in Advanced Composites Collaboration for Innovation and Science (grant number EP/L016028/1) and SIMulation of new manufacturing PROcesses for Composite Structures (SIMPROCS) (grant number EP/P027350/1).
- Process modelling
- Process monitoring
- Resin flow