Pneumatic conveying of fine powders is essential for many industrial processes, including Laser Metal Deposition (LMD), a Direct Metal Additive Manufacturing (DMAM) technology that builds solid objects layer-by-layer using a laser to melt metal powder. To optimize the process, it is necessary to have a correct understanding of the powder’s behaviour under the process condition. The coupled Computational Fluid Dynamics - Discrete Element Modelling (CFD-DEM) and MultiPhase - Particle In Cell (MP-PIC) are two popular Eulerian-Lagrangian models to simulate particle laden flows. This study compares them to analyse powder behaviour in a small channel of LMD machines. Results from the two methods differ significantly, with CFD-DEM offering a more accurate representation of the physical reality, while MP-PIC is more computationally efficient. The study finds that the CFD-DEM method produces higher fluctuations in the solids flow rate due to the formation of particle clusters, while MP-PIC displays a smooth and essentially uniform flow. The results suggest that CFD-DEM should be used for more accurate and detailed studies of solids flow rate in pneumatic conveying systems, while MP-PIC can be used for preliminary studies and design optimization.

Directed Energy Deposition (DED) processes necessitate a consistent material flow to the melt pool, typically achieved through pneumatic conveying of metal powder via thin pipes. This study aims to record and analyze the multiphase fluid–solid flow. An experimental setup utilizing a high-speed camera and specialized optics was constructed, and the flow through thin transparent pipes was recorded. The resulting information was analyzed and compared with coupled Computational Fluid Dynamics-Discrete Element Modeling (CFD-DEM) simulations, with special attention to the solids flow fluctuations. The proposed methodology shows a significant improvement in accuracy and reliability over existing approaches, particularly in capturing flow rate fluctuations and particle velocity distributions in small-scale systems. Moreover, it allows for accurately analyzing Particle Size Distribution (PSD) in the same setup. This paper details the experimental design, video analysis using particle tracking, and a novel method for deriving volumetric concentrations and flow rate from flat images. The findings confirm the accuracy of the CFD-DEM simulations and provide insights into the dynamics of pneumatic conveying and individual particle movement, with the potential to improve DED efficiency by reducing variability in material deposition rates.

La gran parte de los componentes usados en la industria aeronáutica, automovilista o del transporte están sometidos a cargas de fatiga. Esos componentes deberían ser diseñados considerando la vida a fatiga. En este artículo el diseño de una escuadra ha sido simulad por MEF teniendo en cuenta el tipo de material, cargas aplicadas y la geometría. La geometría de la escuadra se ha optimizado usando el método de optimización robusta de Taguchi. Hasta donde los autores han comprobado no hay ninguna publicación que emplee el método de optimización robusta de Taguchi aplicándolo al diseño geométrico de elementos industriales tomando como variable de salida el coeficiente de fatiga de Findley. Este artículo presenta un método para determinar los parámetros críticos en el diseño que afectan a la vida a fatiga del componente. Esta idea es pionera y aplicable a otros diseños o aplicaciones mecánicas que pueden emplear esta metodología para el diseño robusto a la fatiga de partes y componentes mecánicos.

The thermal conductivity of two-phase ceramics has been modelled by finite element method for a wide range of second phase contents, aspect ratios and thermal conductivities of the filler phase. The finite element method model has been validated with the experimental thermal conductivity data from exemplary ceramics to show the applicability of this model, namely alumina/silicon carbide composites and highly porous mullite materials, which show second phases of very different thermal conductivity (SiC and pores). The selection of the mesh element dimensions has been based on a schematic picture of the microstructure. For the first time, the finite element method simulation of a large number of random biphasic meshes has been used for estimating errors in the predicted thermal conductivity values that were comparable with the experimental error. The model can be very helpful in designing new materials with specific thermal conduction, limiting the more expensive and time consuming material preparation work.