The paper explores adaptive sampling techniques through an integrated data-driven, experimental, and numerical approach. This method efficiently narrows down the high-dimensional experimental strain space in composite materials. We developed a surrogate model that accurately predicts stress responses in architectural composites, such as woven structures. This milestone represents our first published work since joining the School of Mechanical and Materials Engineering, Washington State University and was accomplished in collaboration with Dr. Alberto Ciampaglia.
The paper is published on Computational Materials Science and can be accessed here: https://authors.elsevier.com/a/1kRvM3In-v4sYc