With the growing industrial demand for materials that can withstand dynamic loads, composite 3D printing, particularly utilizing continuous fiber reinforcements, presents a promising solution. This study investigates the toughness of three fiber-reinforced materials, namely carbon fiber, Kelvar, and fiberglass, by conducting Charpy impact tests. The results reveal that fiber-reinforced 3D materials significantly outperform standard 3D printed components, with fiberglass showing the highest toughness. These findings demonstrate that fiber-reinforced 3D printed materials offer a viable alternative for applications requiring high toughness and dynamic resistance.

This work presents a case study detailing an end-to-end workflow for reconstructing a damaged plastic component when no original design data are available. The approach integrates microscopic inspection of fracture surfaces, selective enhancement of 3D scan data, CAD-based modification of geometrically and functionally critical features, and continuous fibre-reinforced additive manufacturing. The component examined functions as a structural mounting element in an automotive lighting module, where it maintains correct alignment and provides mechanical support in service. The study concentrates on the cost-effective replacement of unique parts produced in very small batches. The results indicate that this fracture-analysis-informed reverse engineering strategy offers a practical solution for reproducing low-volume, custom, or replacement components in situations where standard manufacturing methods are not economically viable. The reconstructed part matched the geometry necessary for installation in the original assembly and successfully passed initial functional checks; however, this study did not include quantitative measurements of mechanical performance.

The objective of this study is to examine the Radar Cross Section (RCS) of instruments designed for Autonomous Driving Systems (ADAS) testing, with the intention of comparing the results to those of actual human subjects. The RCS values of both dummy and platform objects were documented at varying distances and positions, with the objective of ascertaining the extent to which dummies can serve as substitutes for human values in vehicle radar sensing tests. The findings, substantiated by graphical representations and statistical analyses (e.g., Pearson and Spearman correlation), reveal a moderately strong positive correlation between the RCS and human values, which is statistically significant. The outcomes of the tests demonstrate that the developed instruments can substitute for real human radar cross-section values within the range of 5-15 m. However, as the distance increases, larger deviations are observed. These discrepancies underscore the necessity for a refinement of the dummy design in future ADAS tests, ensuring that distance-sensitive tests accurately reflect real human measurements.