| Abstract Scope |
This study extends a computational approach, originally developed for predicting linear elastic properties of nano-porous materials, to estimate probability of failure initiation sites in Phenolic Impregnated Carbon Ablator (PICA), which consists of carbon fibers preforms reinforcements infused with a porous phenolic resin matrix. PICA has desirable thermal insulation and mechanical properties suited for thermal protection systems in aerospace applications. Accurately predicting the material properties and mechanically weak points of PICA, essential for safety and performance, is a challenging task as it depends upon its microscopic features like random fiber size, orientation and distribution, and PICA porosity. We address this by stochastically generating 3D Representative Volume Elements (RVEs) to capture important microstructural features and performing virtual experiments on RVEs using Finite Element Method to estimate the macroscopic linear elastic properties and strain maps, used to predict the probability of weak regions, which will help in minimizing vulnerabilities during design of TPS. |