Additive manufacturing (AM) of metals have become a promising fabrication method, due to the decreased waste from conventional manufacturing and the ability to create complex geometries [1]. However, the surface roughness of powder based additively manufactured structures appears porous, with complicated geometries that are a concern for localized corrosion. Knowing which defects are more susceptible than others, from a geometry perspective, will greatly aid mitigation strategies either in terms of AM process parameters or through post-build surface treatments. This study will explore how surface defects created on AM stainless steel parts impact local corrosion stability under atmospheric conditions.The stochastic nature of the pits initiating and repassivating, combined with the complexities of the AM defects and those of thin water layers, make for a very large parameter space to explore. In effect, the most important aspect of localized corrosion under these conditions is the determination of whether a pit will repassivate or grow, and if it grows, how large can it become. Many different parameters affect the pit stability, including the geometry of the cathode size, the anode (pit) size, details of the environment (solution composition, electrochemical potential), and the water layer thickness.It is known that the potential at a pit mouth must be more positive than in order to grow stably [2]. The repassivation potential therefore serves as one way to measure pit stability, while other parameters in the system are held constant. An additional pit stability criteria is the pit stability product, (i ⋅ x), from Galvele’s seminal work [3]. The maximum pit model [4] uses these criteria, parameters that define the thin electrolyte, and the current-potential relationship for the cathodic reaction(s) on the external surface to define the largest hemispherical pit for which the Conservation of Charge is met.Finite element modeling is used here to determine what combinations of geometric parameters associated with surface defects due to AM processing of SS316 lead to the stabilization of a pit or not. Pits of different dimensions, including hemispherical, rectangle, and disk shaped, are assessed as isolated pits. The model’s geometric complexity is then increased to better represent an additively manufactured surface with many pits of different shapes and sizes based on cross-sectional data from actual surfaces. A range of atmospheric conditions are investigated, including a range of relative humidity and salt loading density. The boundary conditions within the model represent the solution kinetics of both scenarios. The water layer and loading densities were varied, according to the equation proposed by Chen et al. [5].SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525. SAND2020-5408 A.[1] B. AlMangour and J. M. Yang, “Improving the surface quality and mechanical properties by shot-peening of 17-4 stainless steel fabricated by additive manufacturing,” Mater. Des., vol. 110, pp. 914–924, 2016.[2] J. Srinivasan, M. J. McGrath, and R. G. Kelly, “A High-Throughput Artificial Pit Technique to Measure Kinetic Parameters for Pitting Stability,” J. Electrochem. Soc., vol. 162, no. 14, pp. C725–C731, 2015.[3] J. R. Galvele, “Transport Processes and the Mechanism of Pitting of Metals,” J. Electrochem. Soc., vol. 123, no. 4, p. 464, 1976.[4] R. M. Katona, J. Carpenter, E. J. Schindelholz, and R. G. Kelly, “Prediction of Maximum Pit Sizes in Elevated Chloride Concentrations and Temperatures,” J. Electrochem. Soc., vol. 166, no. 11, pp. C3364–C3375, 2019.[5] Z. Y. Chen, F. Cui, and R. G. Kelly, “Calculations of the Cathodic Current Delivery Capacity and Stability of Crevice Corrosion under Atmospheric Environments,” J. Electrochem. Soc., pp. 360–368, 2008.