Session: 03-08-01: Integrated Computational Materials Engineering

Paper Number: 183392

183392 - Autoclave Process Modeling: CFD Simulation With Experimental Verification and Parametric Study 

Autoclave processing of composite materials relies on precise temperature control to ensure proper resin flow, preform consolidation, and resin cure. Manufacturer-recommended cure cycles (MRCC) incorporate substantial safety margins to accommodate variations in part geometry, tooling thermal mass, and loading configurations, potentially resulting in conservative cycle times that limit manufacturing throughput. This study develops and validates a computational fluid dynamics (CFD) framework to investigate thermal response during autoclave processing of IM7-8552 composite material, with emphasis on quantifying the effects of heating rate and air velocity on mold temperature evolution.

A full-scale autoclave model was constructed in ConvergeCFD using conjugate heat transfer simulation and validated against experimental thermocouple measurements. Parametric studies examined heating rates from 3.0 to 7.5°F/min and air velocities from 1.5 to 7.5 m/s. Results show reasonable agreement between simulation and experimental data. Parametric studies show higher heating rates reduce absolute cycle time but result in longer thermal lag, while increased air velocity enhances convective heat transfer and reduces lag. The validated CFD framework demonstrates that cycle time reductions are achievable through optimized heating rate and air velocity combinations while maintaining thermal uniformity criteria required for complete cure development in the IM7-8552 system, enabling data-driven process optimization to improve manufacturing throughput without compromising part quality.

Presenting Author: Yao Sun Purdue University

Presenting Author Biography: Yao Sun is a PhD student in Aeronautics and Astronautics at Purdue University, where he serves as a Graduate Research Assistant. His research is focused on computational modeling to mitigate manufacturing process-induced defects as well as experiment design and validation. His current research utilizes Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) in manufacturing process modeling, with a specific emphasis on predicting and improving as-manufactured composite properties.