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Powder capture efficiency is indicative of the amount of material that is added to the substrate during laser additive manufacturing (AM) processes, and thus, being able to predict capture efficiency provides capability of predictive modeling during such processes. The focus of the work presented in this paper is to create a numerical model to understand particle trajectories and velocities, which in turn allows for the prediction of capture efficiency. To validate the numerical model, particle tracking velocimetry (PTV) experiments at two powder flow rates were conducted on free stream particle spray to track individual particles such that particle concentration and velocity fields could be obtained. Results from the free stream comparison showed good agreement to the trends observed in experimental data and were subsequently used in a direct laser deposition (DLD) simulation to assess capture efficiency and temperature profile at steady-state. The simulation was validated against a single track deposition experiment and showed proper correlation of the free surface geometry, molten pool boundary, heat affected zone boundary, and capture efficiency.

Powder capture efficiency is indicative of the amount of material that is added to the substrate during laser additive manufacturing processes, and thus, being able to predict capture efficiency provides capability of predictive modeling during such processes. The focus of the work presented in this paper is to create a numerical model to understand particle trajectories and velocities, which in turn allows for the prediction of capture efficiency. To validate the numerical model, particle tracking velocimetry experiments at two powder flow rates were conducted on free stream particle spray to track individual particles such that particle concentration and velocity fields could be obtained. Results from the free stream comparison showed good agreement to the trends observed in experimental data and were subsequently used in a direct laser deposition simulation to assess capture efficiency and temperature profile at steady-state. The simulation was validated against a single track deposition experiment and showed proper correlation of the free surface geometry, molten pool boundary, heat affected zone boundary and capture efficiency.

Nearly 45% of the residential site energy in the US is consumed by the gas furnace for space heating. The design practice of next-generation product often refers to CFD-based design tool, in order to reduce the development cost and cycle. In the present study, Particle Image Velocimetry (PIV) is applied to measure the detailed flow field inside a general gas furnace model for establishing a benchmark database and validating CFD predictions. The furnace model is equipped with multiple observation windows and is connected to an air circulation system with seeding particles introduced, simulating different well-controlled operation conditions. The flow field around the four primary heat exchangers and at the outlet of the furnace is measured and analyzed statistically. The mean velocity displays symmetric patterns as the differential pressure between inlet and outlet of the furnace is low. The symmetry is transiently lost as the differential pressure increases. Statistical analysis also shows turbulence in regions with flow separation and vortex shedding. The results provide a clear understanding of the change of flow characteristics under different operation conditions.