Computational Materials: Peridynamics & Solid-Fuel Void Closure

Developing a high-fidelity peridynamics workflow to investigate void closure and damage sensing in solid rocket fuel geometries. The simulation pipeline converts high-resolution microstructure images into particle-based discretizations (hundreds of thousands of particles) for large-scale peridynamic analyses executed on remote computing clusters. Post-processing and visualization are conducted in Tecplot, with MobaXterm supporting remote computing and data management. The long-term goal is to design a “nervous system” of carbon nanotubes within the solid fuel that detects internal damage via electrical resistance changes—enabling early diagnosis of microstructural degradation in otherwise opaque energetic materials.