Influence of Fibre Fill Pattern and Stacking Sequence on Open-Hole Tensile Behaviour in Additive Manufactured Fibre-Reinforced Composites

Abstract

Additive manufacturing has revolutionised the field of manufacturing, allowing for the production of complex geometries with high precision and accuracy. One of the most promising applications of additive manufacturing is in the production of composites, which are materials made by combining two or more substances with different properties to achieve specific functional characteristics. In recent years, the use of Continuous Filament Fabrication (CFF) in additive manufacturing has become increasingly popular due to its ability to produce high-quality composite parts which have fibres with a complex orientation and high curvature. This paper aims to investigate the influence of fill pattern and stacking sequence on the open-hole tensile strength of composites manufactured using CFF and made of an innovative matrix composed of nylon and short carbon fibres, i.e., Onyx, and with continuous carbon fibre as reinforcement. By systematically varying the fill pattern and stacking sequence, we aim to identify the optimal combination that can achieve the highest open-hole tensile strength in these composites. The results of this study will provide valuable insights into the design and manufacture of high-strength composites using additive manufacturing. Open-hole strength and elastic properties are strongly influenced by the infill strategy and stacking sequences adopted, and show different failure modes. The results also point out a technological issue characterising the process and indicate some guidelines for designing and manufacturing 3D printing composites.

On the suitability of redundant accelerometers for the implementation of smart oscillation monitoring system: Preliminary assessment

“…Figure 2 shows the controlled oscillation generator and the measurement setup. In particular, the mechanical parts are realized by the 3D printing process [41], [42] and are highlighted in black color, while the stepper motor and motor driver are highlighted in orange color. The measurement setup is mainly composed of the modules, i.e., the proposed redundant low-cost accelerometers (red) as well as the STIM318 by SensoNor TM , the marine-grade (green) accelerometer exploited as a comparison reference.…”

The Use of Artificial Intelligence Approaches for Performance Improvement of Low-Cost Integrated Navigation Systems

“…Accurate measurements of the state of motion of a vehicle or object turn out to be a key aspect of several fields peculiar to the current industrial revolution [1]. These range from autonomous navigation systems of air and ground vehicles for smart city applications, to the autonomous and fast transportation of goods and products within warehouses, and from the control of robotic arms to the positioning and monitoring of large building structures [2][3][4][5][6][7]. For each of these applications, knowledge of kinetic parameters consisting of position, velocity, and attitude is required in order to determine any maneuvers and/or activities necessary to achieve the final task.…”