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<p>Computationally efficient models are required to understand the relationships between additive manufacturing (AM) process variables and the full envelope of design capabilities that AM processes provide. The intentional formation of lack-of-fusion (LOF) porosity within AM parts is a relatively unexplored design space, where most research efforts focus on its mitigation. To enable the use of LOF as a design consideration, process-structure models are needed that predict its formation as a function of physical principles at the part scale. The current work presents a meso-scale thermal history model that predicts the size, shape, and trajectory of the melt pool formed during the directed energy deposition (DED) process. The model simulates melt pool geometry purely as a function of heat conduction to retain the computational efficiency needed to study part-scale LOF structures and their dependence on process variables. A sufficiently accurate representation of melt pool geometry enables the prediction of LOF voids that form as a function of scan strategy throughout the part. Current model predictions of melt pool geometry are validated using both in-situ and ex-situ methods. A simple maximum temperature threshold is used to define regions of the model where LOF voids are most likely to form. Model results compare very well to LOF structures observed experimentally via CT imaging. The model’s computational efficiency enables part-scale optimization of process variables for control of LOF formation. Future applications will allow for tailored LOF structures to control various aspects of AM part performance.</p>

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Thermal history calculation as a predictor of lack-of-fusion void geometry in a directed energy deposition processed high-strength steel

  • 期刊论文

  • 发表日期：

    2025年6月12日

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  • Stephen Cluff,
  • Clara Mock

摘要

Computationally efficient models are required to understand the relationships between additive manufacturing (AM) process variables and the full envelope of design capabilities that AM processes provide. The intentional formation of lack-of-fusion (LOF) porosity within AM parts is a relatively unexplored design space, where most research efforts focus on its mitigation. To enable the use of LOF as a design consideration, process-structure models are needed that predict its formation as a function of physical principles at the part scale. The current work presents a meso-scale thermal history model that predicts the size, shape, and trajectory of the melt pool formed during the directed energy deposition (DED) process. The model simulates melt pool geometry purely as a function of heat conduction to retain the computational efficiency needed to study part-scale LOF structures and their dependence on process variables. A sufficiently accurate representation of melt pool geometry enables the prediction of LOF voids that form as a function of scan strategy throughout the part. Current model predictions of melt pool geometry are validated using both in-situ and ex-situ methods. A simple maximum temperature threshold is used to define regions of the model where LOF voids are most likely to form. Model results compare very well to LOF structures observed experimentally via CT imaging. The model’s computational efficiency enables part-scale optimization of process variables for control of LOF formation. Future applications will allow for tailored LOF structures to control various aspects of AM part performance.