Approximation Of Material Behavior In Polymer Processing

The objective of this work is to apply empirical models to approximate material behavior in polymers. Many of the models used to represent polymer-processing behavior are physics-based or chemistry-based when complexity allows, or simulation-based when complexity is large. There is a need in the industry, however, for models that are simple to code to predict different aspects of polymer behavior with moderate to large complexity. With this in mind, this work attempts the approximation of different phenomena in polymer molding processes through the use of artificial neural networks. The first results, pertaining to sheet molding compound, point to the feasibility of this approximation approach as well as its convenience. Similar results in injection molding will be seeked in the short term.