Fused deposition modeling (FDM) is one of the most used additive manufacturing processes in the current time. Predicting the impact of different 3D printing parameters on the quality of printed parts is one of the critical challenges facing researchers. The present paper aims to examine the effect of three FDM process parameters, namely deposition velocity, extrusion temperature, and raster orientation on the bending strength, stiffness, and deflection at break of polylactic acid (PLA) parts using Taguchi design of experiment technique. The results indicate that the temperature has the highest impact on the mechanical properties of PLA specimens followed by the velocity and the orientation. The optimum composition offering the best mechanical behavior was determined. The optimal predicted response was 159.78 N, 39.92 N/mm, and 12.55 mm for the bending strength, bending stiffness, and deflection at break, respectively. The R2 obtained from analysis of variance (ANOVA) showed good agreement between the experimental results and those predicted using a regression model.

Wood-polymer composites are increasingly produced through fused deposition modeling (FDM)—an additive manufacturing technique. The versatility of this technology has attracted several industries to print complex shapes and structures. This underscores the importance of studying the mechanical properties of the FDM parts, specifically, their elastic properties. A numerical homogenization methodology is introduced in the present study, focusing on the fundamental aspect of the elastic properties. Investigations were carried out on the influence of various parameters like wood volume fraction, aspect ratio, and internal porosity. The numerical results were validated using analytical models and experimental data. The comparison showed a satisfactory agreement with experimental data, where the relative error did not exceed 10%, leading to a strong conclusion about the validity and effectiveness of the proposed approach.

Purpose The purpose of this paper is to investigate numerically mixed convection of Al2O3-water nanofluids flowing through a horizontal ventilated cavity heated from below by a temperature varying sinusoidally along its lower wall. The simulations focus on the effects of different key parameters, such as Reynolds number (200 ≤ Re ≤ 5,000), nanoparticles’ concentration (0 ≤ ϕ ≤ 0.1) and phase shift of the heating temperature (0 ≤ γ ≤ π), on flow and thermal patterns and heat transfer performances. Design/methodology/approach The Navier–Stokes equations describing the nanofluid flow were discretized using a finite difference technique. The vorticity and energy equations were solved by the alternating direction implicit method. Values of the stream function were obtained by using the point successive over-relaxation method. Findings The simulations were performed for two modes of imposed external flow (injection and suction). The main findings are that the dynamical and thermal fields are affected by the parameters Re, ϕ, γ and the applied ventilation mode; the addition of nanoparticles leads to an improvement of heat transfer rate and an increase of mean temperature inside the enclosure; the heat exchange performance and the better cooling are more pronounced in suction mode; the phase shift of the heating temperature may lead to periodic solutions for weaker values of Re and contributes to an increase or a decrease of heat transfer depending on the value of ϕ and the convection regime. Originality/value To the best of the authors’ knowledge, the problem of mixed convection of a nanofluid inside a vented cavity using the injection or suction technics and submitted to non-uniform heating conditions has not been treated so far.

The characteristic of flow and heat transfer of Al2O3-water nanofluids flowing through a horizontal ventilated cavity is investigated numerically. The bottom wall is subjected to a sinusoidal hot temperature profile, whereas the other boundaries are assumed to be thermally insulated. In fact, the flow comes forcedly into the system from the bottom of the left vertical wall and leaves it from the top of the right one by suction. The simulations focus on the effects of different key parameters, such as Reynolds number (200 ≤ Re ≤ 5000), nanoparticle’s concentration (0 ≤ ϕ ≤ 0.05) and phase deviation of the sinusoidal heating (γ equal 0 or π), on the flow and thermal patterns and heat transfer performances. The obtained results show that the presence of nanoparticles increases the heat transfer and the mean temperature within the cavity. In addition, the phase shift of the heating temperature may lead to periodic solutions for weaker values of Re and contributes to an increase or a decrease of heat transfer depending on the value of ϕ and the convection regime.

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