A major challenge in additive manufacturing of metallic components is identifying and reliably predicting the relationship between chemistry, challenging processing conditions, microstructure evolution, and mechanical properties for a variety of alloys. Mesoscale simulations of discrete defects in metals provide an ideal framework to investigate this relationship by numerically modeling the micro-scale mechanisms governing the plastic deformation under high thermal and mechanical loading conditions. To bridge size and time-scale while limiting computational effort, typically the concept of representative volume elements (RVEs) is employed. However, in settings with complex thermal and mechanical loading histories careful consideration of the impact of modeling constraints in terms of time scale and simulation domain on predicted results is required. We address the representation of cellular dislocation structures formation in mesoscale simulation volumes (few tens of um) using the example of a cool-down process during unidirectional single-track scan of powder-bed fusion (PBF) of AISI 316L stainless steel. This is achieved by a series of large-scale three-dimensional discrete dislocation dynamics (DDD) simulations informed by experimental measurements and thermo-mechanical finite element modeling of the PBF process. We demonstrate the transient cellular dislocation structure evolution in response to chemical and processing conditions, enabling direct comparisons to experimental characterization. Our results show that the interruption of dislocation slip at solidification cell walls is responsible for the formation of cellular dislocation structures, highlighting the significance of considering chemical heterogeneity for a physics-based modeling of plastic deformation during additive manufacturing. This work will support microstructure-informed process optimization for tailored mechanical performance of additively manufactured alloys.