BUILD SIMULATION AND EXPERIMENTAL STUDY OF LARGE-FORMAT ADDITIVE MANUFACTURING OF THERMOPLASTIC POLYMER COMPOSITES

Large-Format Additive Manufacturing (LFAM) is emerging as a transformative technology with considerable potential across multiple sectors, provided that key implementation challenges are effectively addressed. Traditional trial-and-error methods are not practical due to their high costs and limited success in tackling the unique issues associated with LFAM, such as precise control of temperature, layer time, and problems related to layer adhesion, warping, and delamination. To overcome these challenges, the use of physics-based numerical simulations is essential for predicting and mitigating potential build defects, thereby improving build quality and reducing costs. This study presents a physics-based Integrated Computational Materials Engineering (ICME) approach for LFAM, demonstrated through a comprehensive case study of an LFAM-printed modular housing unit. The simulation framework incorporates micro-mechanics-based material modeling to characterize temperature-dependent mechanical properties, along with thermal analysis driven by machine GCode to accurately forecast temperature distribution during the printing process. This allows for the identification of optimal layer time parameters for recoating, enhancing layer adhesion, and minimizing defects. Additionally, mechanical analysis considers the raft and part clamping mechanisms during printing to identify issues such as warping, delamination, and Z-stress accumulation. The case study demonstrates the effectiveness of this simulation methodology through the fabrication of a 240” x 132” x 110” housing unit using recycled polyethylene terephthalate glycol with 30% glass fiber (PETG 30GF) material. This study not only highlights potential defects linked to the Gcode, but also identifies design features susceptible to high-stress concentrations and localized failures. Once the simulation methodology is validated, a compensated geometry is generated and printed to verify the quality improvement. Overall, this research underscores the critical role of physics-based simulations in addressing the inherent challenges of LFAM, facilitating informed decision-making, and accelerating technology adoption.