Enhancing Finite Element Simulations of 3D-Printed PLA Using Physics-Informed Neural Networks: Validation Through Experimental Tensile Testing and Benchmark Comparisons

Key Points

• Tensile testing results showed enhanced prediction accuracy of simulations, improving validation outcomes.
• The simulations demonstrated a significant reduction in prediction error, achieving parameters that closely matched experimental data.
• Utilizing physics-informed neural networks within finite element analysis led to better benchmarking against traditional methods.
• This approach may enable more effective material design but requires validation in varied conditions to generalize findings.