| About this Abstract |
| Meeting |
MS&T22: Materials Science & Technology
|
| Symposium
|
Additive Manufacturing of Polymeric-based Materials: Challenges and Potentials
|
| Presentation Title |
Estimation of 3D Statistics For Synthetic Generation of AM Carbon Fiber Composite Structures |
| Author(s) |
Andrew Abbott , Michael Chapman , Kenneth M. Clarke, Mark Flores , Michael Groeber, Michael Uchic , John Wertz |
| On-Site Speaker (Planned) |
Kenneth M. Clarke |
| Abstract Scope |
Synthetic generation of realistic materials for testing of process-structure-property relationships in additively manufactured materials continues to gain traction within the material science community. Unfortunately, generation tools lag in terms of realism, leading to difficulties in material testing software. The method of stereology allows for useful estimation of 3D statistics from 2D information but remains difficult to apply to fiber parameters such as orientation and clustering. With a combination of synthetic material generating software, Dream.3D, and stereological principles, an algorithm can iteratively create a synthetic microstructure matching 2D statistics collected from an empirical dataset. This iterative process creates a solid foundation for generation of realistic synthetic microstructure, allowing for digital testing and designing of materials. This paper introduces a framework for applying stereological principles to additively manufactured carbon fiber composite structures to estimate 3D parameters such as shape, size, orientation, and pack fraction from 2D information. |