Polymer matrices are usually reinforced with fibres giving a good strength/weight ratio. Currently, innovative research has been focussed in producing new composite materials using natural fibres as an alternative sustainable material. In the present work, the mechanical behaviour of a composite based on polylactic acid reinforced with bamboo fibre produced by additive manufacturing was evaluated. Specimens were manufactured using fused deposition modelling with different geometry depositions, layer thicknesses and fill densities. The results were evaluated performing an analysis of variance with a confidence level of 95%. The composites were subjected to mechanical testing to evaluate the influence of process parameters in tensile strength, strain, and elastic modulus. It was observed that the principal factors that influence the elasticity are the deposition geometry and fill density. Fracture zones and manufacturing defects were additionally studied using optical and scanning electron microscopy. The vertical orientation of the layers causes the premature rupture of the test samples due to the tension being reverted at the interface between the layers. The specimens showed slight adhesion between the polylactic acid matrix and the bamboo fibres. This effect was related with the presence of porosity, cracks and local deformations in the composite material.

This work investigates the microstructure evolution during the rotary friction welding (RFW) of Inconel 718 alloy. A cellular automata (CA) approach is implemented to evaluate a cylindrical component (at weld center and edge wall), predicting dynamic recrystallization (DRX) and grain size of friction welds. The input variables for RFW were rotational speed (500, 1000, and 1200 rpm), feed rate (2 mm/s), and feed distance (3.6 mm). The CA model is based on the Laasraoui-Jonas model and explains intricate grain transformation in terms of microstructure, temperature, strain, and strain rate. Calculated grain consists of very fine grain structure at the stir zone followed by the thermo-mechanical affected zone, where partial recrystallized microstructure was present. The average grain size was 2.5 µm, which is comparable to reported experimental values. The grain analysis revealed that temperature and strain are most affecting factors to attain a refined microstructure. The strain rates predicted for both center and edge locations of the weld were found to be higher as rotational speed increased. A steady strain distribution is noted at greater temperature for all the rotational speeds. The results of this work contribute toward the understanding of microstructure and mechanical response for RFW of Inconel 718.

The measurement of residual stress using the deep-hole drilling method relies on the evaluation of the distortion of a hole in a plate under the action of far-field direct and shear stresses. While closed-form solutions exist for the isotropic materials, in previous work for orthotropic materials, finite element analysis has been used to find the distortion. In this technical note, Lekhnitskii’s analysis is used to find closed-form solutions for the distortion of a circular hole in an orthotropic plate. The results are compared with those of finite element analysis for a range of material properties with excellent agreement.

Purpose: An experimental and numerical study of thermal profiles of 316 L stainless steel during selective laser melting (SLM) was developed. This study aims to present a novel approach to determine the significance and contribution of thermal numerical modeling enhancement factors of SLM. Design/methodology/approach: Surface and volumetric heat models were proposed to compare the laser interaction with the powder bed and substrate, considering the powder size, absorptance and propagation of the laser energy through the effective depth of the metal layer. The approach consists in evaluating the contribution of the thermal conductivity anisotropic enhancement factors to establish the factors that minimized the error of the predicted results vs the experimental data. Findings: The level of confidence of the carried-out analysis is of 97.8% for the width of the melt pool and of 99.8% for the depth of the melt pool. The enhancement factors of the y and z spatial coordinates influence the most in the predicted melt pool geometry. Research limitations/implications: Nevertheless, the methodology presented in this study is not limited to 316 L stainless steel and can be applied to any metallic material used for SLM processes. Practical implications: This study is focused on 316 L stainless steel, which is commonly used in SLM and is considered a durable material for high-temperature, high-corrosion and high-stress situations. Social implications: The additive manufacturing (AM) technology is a relatively new technology becoming global. The AM technology may have health benefits when compared to the conventional industrial processes, as the workers avoid extended periods of exposure present in conventional manufacturing. Originality/value: This study presents a novel approach to determine the significance and contribution of thermal numerical modeling enhancement factors of SLM. It was found that the volumetric heat model and anisotropic enhancement thermal approaches used in the present research, had a good agreement with experimental results.