Model-based optimization of consolidation processing

Abstract

The performance of fiber reinforced titanium matrix composites (TMC) made by consolidation of spray deposited monotapes is strongly influenced by the processing conditions used. This high temperature consolidation step must simultaneously increase the relative density while minimizing fiber microbending/fracture and the interfacial reaction product layers at the fiber–matrix interface. These three microstructural variables have conflicting dependencies upon the consolidation process variables (temperature, pressure and time), and it has been difficult to experimentally identify process pathways that lead to composites of acceptable quality (where the fiber damage and the reaction layer thickness are kept below some bounds, while matrix porosity is eliminated). Here, models for predicting the microstructure's dependence upon process conditions (i.e. the time varying temperature and pressure) are combined with consolidation equipment dynamics to simulate the microstructure evolution. We then introduce the idea of process failure surfaces and show how a model predictive control algorithm, is able to design `locally' optimal process cycles that minimize fiber damage, reaction product layer thickness and porosity. As an example, we explore the planning of process schedules that process failure surfaces for several TMC systems.