Functionally Graded Additive Manufacturing
Functionally Graded Additive Manufacturing (FGAM) has been a core focus of my research, particularly during my doctoral work at Tennessee Tech University. The goal of this work was to explore the use of low-cost Fused Filament Fabrication (FFF) techniques to design, fabricate, and characterize multi-material structures with functionally graded properties.
🔍 Objective 1: Design & Fabrication of FGMs
We developed novel digital material designs and fabricated them using FFF. These materials showed enhanced interfacial integrity compared to direct bi-material joints. Microstructural analysis and mechanical testing validated the robustness of the interface.
- Key Insight: Graded transitions between materials significantly reduced delamination and stress concentrations at interfaces.
🔍 Objective 2: Multi-Scale Modeling
We implemented three-scale homogenization and finite element modeling to study the mechanical behavior of the composites. This involved:
- Micromechanical modeling of fiber morphology.
- Mesoscale simulation of bead structure.
- Macroscale property extraction using graded isoparametric FEA.
Result:
Experimental and numerical results confirmed that fiber distribution and gradient control play a critical role in stiffness and strength. Stress concentrations at direct interfaces were mitigated through graded transitions, as demonstrated in both test samples and simulations.
✅ Achievements:
- Developed a computational pipeline from material design to validation.
- Reduced interfacial stress concentrations by up to ~40%.
- Demonstrated manufacturing feasibility for aerospace-grade FGMs using affordable, desktop-scale FFF equipment.
- Potential applications in biomedical, automotive, and lightweight aerospace components.
🛠 Tools & Methods:
- Multiple regression for design optimization
- Homogenization and stiffness prediction
- SEM imaging for validation
- ANSYS and Matlab for simulation
