| About this Abstract |
| Meeting |
2024 ASC Technical Conference, US-Japan Joint Symposium, D30 Meeting
|
| Symposium
|
2024 ASC Technical Conference, US-Japan Joint Symposium, D30 Meeting
|
| Presentation Title |
Point Cloud Failure Criterion for Orthotropic Composite Materials |
| Author(s) |
Subramaniam D. Rajan, Ashutosh Maurya |
| On-Site Speaker (Planned) |
Ashutosh Maurya |
| Abstract Scope |
A new failure criterion has been developed to improve modeling of orthotropic structural composites subjected to impact loadings. Instead of using an analytical expression as failure predictor, a discrete set of points called point cloud failure surface is constructed in the stress/strain space. Multi-scale modeling scheme based on a combination of virtual and laboratory testing is used. Representative volume elements (RVE) are used to model the constituent parts of the composite that are then subjected to multi-axial state of stress and the first instance of failure in the RVE is detected and tagged as a point in the point cloud data. The generated data is used during impact (explicit FEA) analysis such that at every stress Gauss point and every time step, the point cloud data is queried to check if the current state of stress in the finite element is inside or outside the failure surface using k-nearest neighbor (k-NN) classification concept. A representative unidirectional composite is used to illustrate the developed procedure for a flat panel that is subjected to impact loading. The developed multi-scale point cloud concept shows promise and potentially the developed framework can be extended to support a variety of composite architectures. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |