In order to capitalize on the cost-effectiveness of additive manufacturing (AM), it is critical to understand how to build components with consistency and high quality. Directed energy deposition (DED) is an AM method for creating parts layer by layer through the use of a moving heat source and powder material inserted into the melt pool generated on the substrate. DED, like most AM processes, is highly complex due to the rapid thermal gradients experienced during processing. These thermal gradients are determined by a variety of processing parameters, which include laser power, powder feed rate, travel speed, layer height hatch spacing, etc. A lot of effort has been carried out in the additive manufacturing community to understand what these critical parameters are and how they influence the thermal gradients. Despite all these efforts, AM industries rely on a trial-and-error-based approach to find the right set of parameters to produce a quality part. This is time-consuming and not a cost-effective use of AM technology. The aim of our research is to reduce the amount of experimental data in combination with numerical analysis to optimize this relationship. Physics-based two-dimensional melt-pool modeling and experimental results from an OPTOMEC 850M LENS will be utilized to investigate the effects of processing parameters on melt-pool geometry, and the results from this study will provide key processing guidelines to achieve desirable clad geometry and powder efficiency for the DED method.

Continual perturbations to the flow field in the square lid driven cavity can significantly impact both its stability and the dynamic characteristics of the system. In this study, the effect of these perturbations are analyzed via computational fluid dynamics simulations of a square, two-dimensional, lid driven cavity containing varying area fractions of suspended particles. The evolution over time of these particle-particle and particle-fluid interactions generate two-dimensional disturbance velocity changes in the flow field. In order to better understand the characteristics and effects of these changes, proper orthogonal decomposition analysis is performed on the velocity difference flow field to determine the dominant flow structures over the simulation time domain. The resulting eigenvectors and eigenvalues represent the varying dominant flow structures and their respective dominance over the simulation time, respectively. This is carried out at particle suspension area fractions from 10\% - 50\% and for Reynolds numbers of 100, 400, 700, and 1000. Critical flow regimes and particle suspension area fractions are discussed in order to characterize the stability of this particle-in-fluid system.