Welcome to the homepage of the Composites Group at the University of Washington, Seattle. At composites group, we take advantage of experimental data, numerical data, and theory-guided machine learning methods to accelerate innovation while reducing risk for the industry. Examples are accelerating the development of next generation of high performance material systems, optimizing fabrication process of advanced composites, and accelerating material qualification and part certification for aerospace industry.
Selected Recent Publications
Schoenholz, C., Li, S., Bainbridge, K., Huynh, V., Gray, A., & Zobeiry, N. (2023). Accelerated In Situ Inspection of Release Coating and Tool Surface Condition in Composites Manufacturing Using Global Mapping, Sparse Sensing, and Machine Learning. Journal of Manufacturing and Materials Processing, 7(3), 81. Lee, A., Wynn, M., Quigley, L., Salviato, M., & Zobeiry, N. (2022). Effect of temperature history during additive manufacturing on crystalline morphology of PEEK. Advances in Industrial and Manufacturing Engineering, 4, 100085. Humfeld, K. D., Gu, D., Butler, G. A., Nelson, K., & Zobeiry, N. (2021). A machine learning framework for real-time inverse modeling and multi-objective process optimization of composites for active manufacturing control. Composites Part B: Engineering, 223, 109150.