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This paper aims to investigate and explain the dual fracture behaviour of PA12 specimens sintered by selective laser sintering (SLS) as a function of wall thickness and build direction with a powder mixture 30:70. To achieve this objective, research related to chemical, thermal and structural behaviours as a function of the input variables was carried out to describe and explain why ductile-fragile behaviour occurs during fractures under uniaxial tension manufactured via a methodology of material analysis and manufacturing processes.

The factorial design 32 relates the fracture of PA12 tensile specimens to the horizontal, transverse and vertical build directions at 2.0, 2.5 and 3.0 mm thicknesses, respectively. Fractographic images revealed the fracture surfaces and their dual ductile-fragile behaviour related to the specimens’ measured crystalline, thermal, surface and chemical properties.

The study showed that thermal property variables differ depending on the input variables. The wall thickness variable affected this morphology the most, showing the highest percentage of the ductile area, followed by the transverse and vertical directions. It was determined that the failure in the vertical direction is due to crystalline gradients associated with the layer-by-layer construction process. The pore density may be closely related to generating ductile and brittle areas.

In this paper, fracture characterisation is performed based on the mechanical, chemical, structural, thermal and morphological properties of PA12 manufactured by SLS. In addition, a heatmap of porosities in cross-sections is constructed using a machine learning model (k-means) related to dual fracture behaviour. This research revealed significant differences in the fracture type according to the build direction. In addition, thin-section fractography provides a more detailed explanation of the fragile behaviour of the vertical direction associated with crystalline changes due to the direction of the sintering layers.

This study aims to evaluate the low energy impact characteristics of 3D printed carbon fiber thermoplastic and thermoset polymer composite using the Izod impact test. The effects of infill density are examined on the Izod impact properties of 3D printed thermoset polymer and thermoplastic composite specimens. Furthermore, a thorough investigation is conducted into the effect of heat treatment using a hot-air oven on both types of 3D printed composite specimens. To characterize the impact characteristics of each specimen, the fracture surfaces caused by impact load are inspected, and the fracture mechanism is studied using scanning electron micrographs.

Izod Impact specimens of thermoset (epoxy resin) and thermoplastic carbon fiber of different infill density (70, 75, 80, 85, 90 and 100%) are fabricated using the different fiber impregnation 3D printing process. To carry out the heat treatment process, printing of composites is done for each infill design from both thermoset and thermoplastic composites and the impact characteristics of specimens are evaluated on a pendulum test-rig using the ASTM D-256 standard. Using a scanning electron microscope, each fracture zone underwent four separate scanning processes, ranging in size from 2 µm to 100 µm.

The impact resistance of the 3D printed thermoset and thermoplastic composite material is significantly influenced by the type of fiber placement and infill density in the matrix substrate. Because of the weak interfacial strength between the layers of fiber and polyamide 6, the specimen printed with continuous fiber implanted at the part exhibited reduced impact resistance. At 75% infill density, the impact specimen printed with coextruded fiber showed the highest impact resistance with a 367.02% greater magnitude than the continuous fiber specimen with the same infill density.

This work presents a novel approach to analyze the low energy impact characteristics and three-dimensional printing of carbon fiber reinforced thermoplastic and carbon fiber reinforced thermoset and thermoplastic composite material.

Powder bed fusion-laser beam (PBF-LB) is a rapidly growing manufacturing technology for producing Al-Si alloys. This technology can be used to produce high-pressure die-casting (HPDC) prototypes. The purpose of this paper is to understand the similarities and differences in the microstructures and properties of PBF-LB and HPDC alloys.

PBF-LB AlSi10Mg and HPDC AlSi10Mn plates with different thicknesses were manufactured. Iso-thermal heat treatment was conducted on PBF-LB bending plates. A detailed meso-micro-nanostructure analysis was performed. Tensile, bending and microhardness tests were conducted on both alloys.

The PBF-LB skin was highly textured and softer than its core, opposite to what is observed in the HPDC alloy. Increasing sample thickness increased the bulk strength for the PBF-LB alloy, contrasting with the decrease for the HPDC alloy. In addition, the tolerance to fracture initiation during bending deformation is greater for the HPDC material, probably due to its stronger skin region.

This knowledge is crucial to understand how geometry of parts may affect the properties of PBF-LB components. In particular, understanding the role of geometry is important when using PBF-LB as a HPDC prototype.

This is the first comprehensive meso-micro-nanostructure comparison of both PBF-LB and HPDC alloys from the millimetre to nanometre scale reported to date that also considers variations in the skin versus core microstructure and mechanical properties.

This paper aims to present a predictive model approach to estimate the tensile behavior of polylactic acid (PLA) under uncertainty using the fused deposition modeling (FDM) and American Society for Testing and Materials (ASTM) D638’s Types I and II test standards.

The prediction approach combines artificial neural network (ANN) and finite element analysis (FEA), Monte Carlo simulation (MCS) and experimental testing for estimating tensile behavior for FDM considering uncertainties of input parameters. FEA with variance-based sensitivity analysis is used to quantify the impacts of uncertain variables, resulting in determining the significant variables for use in the ANN model. ANN surrogates FEA models of ASTM D638’s Types I and II standards to assess their prediction capabilities using MCS. The developed model is applied for testing the tensile behavior of PLA given probabilistic variables of geometry and material properties.

The results demonstrate that Type I is more appropriate than Type II for predicting tensile behavior under uncertainty. With a training accuracy of 98% and proven presence of overfitting, the tensile behavior can be successfully modeled using predictive methods that consider the probabilistic nature of input parameters. The proposed approach is generic and can be used for other testing standards, input parameters, materials and response variables.

Using the proposed predictive approach, to the best of the authors’ knowledge, the tensile behavior of PLA is predicted for the first time considering uncertainties of input parameters. Also, incorporating global sensitivity analysis for determining the most contributing parameters influencing the tensile behavior has not yet been studied for FDM. The use of only significant variables for FEA, ANN and MCS minimizes the computational effort, allowing to simulate more runs with reduced number of variables within acceptable time.

The purpose of this paper is to evaluate the effect of titanium oxide (TiO₂) and yttrium oxide (Y₂O₃) nanoparticles-reinforced pure aluminium (Al) on the mechanical properties of hybrid aluminium matrix nanocomposites (HAMNCs).

The HAMNCs were fabricated via a vacuum die-assisted stir casting route by a two-step feeding method. The varying weight percentages of TiO₂ and Y₂O₃ nanoparticles were added as 2.5, 5, 7.5 and 10 Wt.%.

Scanning electron microscope images showed the homogenous dispersion of nanoparticles in Al matrix. The tensile strength by 28.97%, yield strength by 50.60%, compression strength by 104.6% and micro-hardness by 50.90% were improved in HAMNC1 when compared to the base matrix. The highest values impact strength of 36.3 J was observed for HAMNC1. The elongation % was decreased by increasing the weight percentage of the nanoparticles. HAMNC1 improved the wear resistance by 23.68%, while increasing the coefficient of friction by 14.18%. Field emission scanning electron microscope analysis of the fractured surfaces of tensile samples revealed microcracks and the debonding of nanoparticles.

The combined effect of TiO₂ and Y₂O₃ nanoparticles with pure Al on mechanical properties has been studied. The composites were fabricated with two-step feeding vacuum-assisted stir casting.