Experimental Assessment of Compaction Pressure Distribution in Automated Fiber Placement: Model Validation and Unforeseen MechanismsPresentation: Session: Session 6: Automated Fiber Placement Room: Main Session start: 14:30 Wed 15 Apr 2026 Benjamin Francis bfranc2@clemson.edu Affifliation: Clemson University Matthew Godbold mjgodbo@clemson.edu Affifliation: Clemson University Ramy Harik harik@clemson.edu Affifliation: Clemson University Topics: - Process planning (All Topics), - Virtual manufacturing and digital technologies (All Topics) Abstract: The fabrication of large, low to medium contour composite shell structures is often achieved using Automated Fiber Placement (AFP). Among process parameters relevant to AFP, compaction pressure applied by the roller to the substrate is critical for reducing voids, ensuring interfacial bonding, and achieving target mechanical properties. To support process planning, a predictive compaction pressure model was previously developed, but experimental validation remained incomplete. This work presents an experimental campaign to validate the proposed model and pertinent phenomena identified in the resultant data. Trials were conducted using the Integrated Structural Assembly of Advanced Composites (ISAAC) AFP system at NASA Langley Research Center, and pressure fields were captured using a pressure mapping system. Low error (under 20%) was shown with predictive models, but large deviations (up to 330%) were observed on a complex tool surface. Beyond validation, new sources of variability were revealed by analysis. Vertical striping of elevated pressure was observed, corresponding to the perforation pattern on the roller, while lighter horizontal striping was observed and was attributed to small inter‑tow gaps. As highlighted by these findings, roller design and tow placement introduce pressure fluctuations not included in the current model. In this study the present model’s predictive accuracy is quantified, and previously unrecognized mechanisms with direct implications for AFP process parameter selection, roller design, and defect mitigation are identified. |