Multi-scale Mechanics of 2D Triaxially Braided Composites

Dr. Chao Zhang is a professor in the School of Civil Aviation, at Northwestern Polytechnical University (Xi’an, China). He obtained his Ph.D. degree from The University of Akron, USA in 2013 and then went on to work as a postdoctoral fellow at The University of North Carolina at Charlotte and the National Renewable Energy Laboratory from 2014 to 2016. He joined NPU in 2016. Dr. Zhang has more than 10 years’ research experience working on the mechanics of composites for aerospace and energy applications, with a specific focus on textile composites and multi-scale modeling methods. Yulong Li is currently a full Professor in the School of Civil Aviation at Northwestern Polytechnical University, Xi-an, China. He received his PhD in Engineering Solid Mechanics, from Northwestern Polytechnical University (NPU), in 1991.During his career, he has held many visiting positions at the Université Pierre et Marie Curie in Paris and John Hopkins University in the United States. His main areas of research include numerical simulation of materials behavior and structural response under impact loading; dynamic behavior and failure evolution in composite materials and experimental techniques to determine materials behavior at high strain rates and elevated temperature. He has also been awarded many scientific awards throughout the course of his career.

• SECTION 1. Experimental Characterization1. Two-dimensional Triaxially Braided Composite (2DTBC) and its manufacturing2. Quasi-static failure behavior and free-edge effect3. Dynamic compressive failure behavior4. Low-velocity impact failure behavior5. High-velocity impact behavior6. Effect of hydrothermal agingSECTION 2. Mechanics-based Modeling7. Volume-average based analytical methods8. Three-dimensional generalized analytical model9. Meso-FE model10. Modelling the temperature-rise behavior11. Multi-scale modelsSECTION 3. Machine-learning based modeling12. Introduction of Machine-learning based modelling approaches13. Machine-learning based modelling approaches for isotropic elastoplastic materials14. Machine-learning based modelling approaches for anisotropic composites15. Machine-learning based modelling for textile composites16. Conclusion and Prospects