The flow through geometrically complex structures is an important engineering problem. In this work, the laminar flow through Triply Periodic Minimal Surface (TPMS) structures is numerically analyzed using Computational Fluid Dynamics (CFD) simulations. Two different TPMS structures were designed, and their porosity was characterized as a function of the isovalue. Then, CFD simulations were implemented to compute the pressure drop by systematically varying the flow velocity and the porosity of the structure. A Darcy–Forchheimer model was fitted to CFD results to calculate the inertial and permeability coefficients as functions of the porosity. These types of results can be very useful for designing fluid flow applications and devices (for instance, heat exchangers), as well as for integrating these TPMS structures since the flow can be very well estimated when using the porous medium model.

The dynamics and heat transfer of an electrically conducting fluid in a toroidal duct with square cross section is numerically analyzed. The flow is driven by an azimuthal Lorentz force produced by the interaction between the radial electric current density, and a constant and uniform magnetic field imposed in the axial direction. For the heat transfer analysis, the temperature distribution of the fluid confined within the toroidal duct depends on a non-uniform volumetric internal heating that emulates the exponentially decaying heating profile typical to blanket conditions of a fusion power reactor. Dimensionless equations that govern the magnetohydrodynamic flow and heat transfer are solved using the spectral element method, and the resulting control parameters involved are the Hartmann (Ha) and Reynolds (Re) numbers. This paper aims to identify the flow characteristics that affect heat transfer under forced convection conditions, with a focus on the interaction between Lorentz and viscous forces. Furthermore, the study explores how different flow patterns that depend on the interaction parameter N=Ha2/Re in the range 0.1<N<3.6, influence the overall heat transfer rate quantified by a global Nusselt number. It is shown that flow instabilities identified as symmetric or asymmetric in the r and z planes, depends on the magnetic strength at a given Reynolds number, Re=2000. We also identify the onset of the secondary flow and determine the critical interaction parameter, N, required to maximize or minimize convective heat transfer, as well as the stationary flow patterns responsible for such behavior.

This study presents an experimental analysis and computational fluid dynamics (CFD) model for studying single-track formation in the Laser Powder Bed Fusion (LPBF) process, implemented in OpenFOAM. The model incorporates key physical phenomena, including Marangoni convection, recoil pressure, and phase change, to accurately capture melt pool dynamics. A stochastic powder size distribution, statistically characterized from experimental observations, is used as the initial condition to enhance the fidelity of the simulations. AlSi10Mg single-track deposits were performed using a Concept Laser M2 LPBF system, varying laser powers, scan velocities, and spot sizes. Cross-sectional microscopy and porosity analyses revealed transitions from lack-of-fusion to keyhole-induced porosity as a function of volumetric energy density (VED). Numerical results showed good qualitative and quantitative agreement with experimental observations, with relative errors in melt pool dimensions below 12%. Simulations further revealed transient flow patterns and melt pool instabilities difficult to capture experimentally. The findings demonstrate that the combination of experimental observations and simulation tools can be used to construct map process windows, predict defects, and support process optimization in LPBF, understanding the multiphysics phenomena at different building conditions, which is particularly important for high-conductivity aluminum alloys.

This study presents an experimental analysis and computational fluid dynamics (CFD) model for studying single-track formation in the Laser Powder Bed Fusion (LPBF) process, implemented in OpenFOAM. The model incorporates key physical phenomena, including Marangoni convection, recoil pressure, and phase change, to accurately capture melt pool dynamics. A stochastic powder size distribution, statistically characterized from experimental observations, is used as the initial condition to enhance the fidelity of the simulations. AlSi10Mg single-track deposits were performed using a Concept Laser M2 LPBF system, varying laser powers, scan velocities, and spot sizes. Cross-sectional microscopy and porosity analyses revealed transitions from lack-of-fusion to keyhole-induced porosity as a function of volumetric energy density (VED). Numerical results showed good qualitative and quantitative agreement with experimental observations, with relative errors in melt pool dimensions below 12\(\%\). Simulations further revealed transient flow patterns and melt pool instabilities difficult to capture experimentally. The findings demonstrate that the combination of experimental observations and simulation tools can be used to construct map process windows, predict defects, and support process optimization in LPBF, understanding the multiphysics phenomena at different building conditions, which is particularly important for high-conductivity aluminum alloys.