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Material State Monitoring using Embedded Sensors for Validating Models for Detecting Process-Induced Damages in Polymer Composites

WARUNA SENEVIRATNE, JOHN TOMBLIN, SHAKYA LIYANAGE, HEMAL SHAH

Abstract


Composite material cure recipes are based on manufacturer-recommended cure cycle inputs, which are developed as a result of various stochastic cure kinetics models during the development of resin formulation. The time, temperature, pressure, and vacuum integrity are inputs for autoclave cure, but none of them are direct measurements of the material state and have no direct correlation to viscoelastic characteristics or mechanical performance of the cured material. The proposed process development system includes autoclave controls that are modified so that the set points are controlled based on externally determined material state of the laminate in the autoclave, which is monitored remotely by a rheological measurements and a material state estimate based on the process and cure state models. With the proposed process-control architecture, material will be cured to achieve the desired viscoelastic and mechanical properties with minimizing the variability cause by the initial material state (ex., shelf- and out-life) by monitoring the rheological response and managing the autoclave temperature to achieve the desired cure state. It also directly measures the initial viscoelastic state, which is a measure of material performance at the point of production rather than arbitrarily constraining the process solely to a time-temperature history, in order to achieve an assumed cure state. Furthermore, the methodology can also be used for interrogating the manufacturing-induced defects of polymer composites in a controlled environment (discrepancy analysis) and link them to boundary conditions. The material-state database developed through validated process models brings about the virtual environment, where the actual boundary conditions can be interrogated during the cure, to ensure that the material achieves its optimal performance. The database approach alleviates using the computationally-heavy simulations (ex., fluid dynamics) for every cure cycle.


DOI
10.12783/asc33/26064

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