Crashworthiness experimental and multi-criteria decision-based evaluation of fused filament fabrication 3D-printed PLA tubular structures with varying infill architectures

Abstract

The purpose ofthis study is to quantify how infill geometry affects the crashworthiness of fused filament fabrication (FFF) 3D-printed polylactic acid (PLA) tubular structures subjected to axial compression, with the aim of identifying an infill pattern that maximizes energy management and deformation stability. PLA tubes were designed and manufactured via FFF using three infill configurations (triangles, zig-zag and square) while keeping all process parameters constant and fixing infill density at 30% to isolate geometric effects. Quasi-static axial compression tests were performed, and five crashworthiness indicators were extracted: initial peak load (IPL), absorbed energy (AE), specific energy absorption (SEA), mean crushing force (MCF) and crush force efficiency (CFE). Overall performance was ranked using TOPSIS multicriteria decision analysis, followed by sensitivity analysis under varying weighting scenarios to examine the robustness of the ranking. Infill geometry markedly affected crashworthiness performance. The square infill produced the most stable deformation mode and the strongest energy–absorption performance, achieving the highest IPL (11.44 kN), MCF (9.83 kN), AE (196.60 kJ) and SEA (23.61 kJ/g), while maintaining a stable deformation mode during crushing. TOPSIS analysis identified the square infill as the optimal configuration with the highest relative closeness coefficient (0.585). Sensitivity analysis confirmed that this superior ranking remains consistent across different weighting schemes, indicating a robust preference for the square infill among the evaluated configurations. This study offers a comprehensive, multimetric crashworthiness assessment of FFF-printed PLA tubular structures by simultaneously integrating five key performance criteria and validating conclusions through TOPSIS ranking and sensitivity analysis. The results demonstrate that infill-pattern optimization is an effective design lever for improving crash energy absorption and structural performance in additively manufactured polymer components for lightweight engineering applications.