Laser-based powder directed energy deposition (DED-LB/P) relies on powder delivery dynamics, which affect process efficiency and part quality through material catchment at the melt pool. This study investigates powder flow behavior and particle catchment using a combined computational and experimental approach. Computational fluid dynamics (CFD) models were developed to simulate material-laser interaction, and powder flow, including particle impact frequency. Model predictions were validated through single-bead deposition of stainless steel 316L powder, monitored using acoustic emission (AE). Simulations provided insight into the frequency of free-powder particle impacts, supporting analysis of powder-substrate interactions. Results show that structure-borne AE signals are sensitive to variations in powder mass flow rate, enabling reliable detection of flow fluctuations. However, direct quantification of powder catchment efficiency from AE remains challenging. The integration of AE monitoring with computational modeling offers a promising pathway for improved understanding and real-time evaluation of powder delivery efficiency and process stability in DED-LB/P.