The technologies of Additive Manufacturing are gaining in popularity within the aerospace industry. Among them, Directed Energy Deposition (DED) presents several advantages, such as localized deposition and printing of large parts [1], which makes it an excellent candidate to replace traditional manufacturing methods. Aircraft engine components produced using casting or forging sometimes have up to 80% of the raw material machined away to produce the final geometry [2]. Layer-by-layer near net-shape deposition using metal wire or powder can be used to decrease the waste material and energy use during production. This significantly cuts emissions and mineral resources consumption and reduces the environmental footprint of the component. To be able to ensure the high quality required for components in the aerospace industry and to decrease the amount of material used in the manufacturing process of DED parts it is of high important to have control over the process. There are several challenges of implementing the DED process including the selection of process parameters and the final distortion of the manufactured parts. These are areas where different modelling and simulation methods can provide a great benefit and be used to better understand the process of DED by predicting data that cannot be measured experimentally and by studying the effect of process parameters virtually. The understanding that has previously been gathered from simulating smaller scale transient thermo-mechanical simulations can be implemented on large scale DED simulations of full scale industrial components. These large scale transient thermo-mechanical simulations are contrasted to the previously developed method using inherent strain. In this method, the distortions predicted using the transient thermo-mechanical analysis on a subscale geometry are used to calibrate inherent strains. These different modelling methods enable simulation-driven design of the DED process from idea to final component.