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<p>Directed energy deposition (DED) is a novel additive manufacturing (AM) process which is revolutionizing the rapid production of large metal parts. Metal additive manufacturing methods feature extremely large cooling rates and smaller melt pools compared to traditional manufacturing methods, which results in smaller grain sizes and variance in material properties. While it can be difficult or expensive to experimentally measure melt pool data during the process, numerical simulations can offer a method to predict the effects of process parameters on the resultant melt pool geometry and microstructure. In this work, a computational fluid dynamics model was developed and validated against experimental single-track samples for melt pool geometry of 316L stainless steel wire deposited on a 304L stainless steel substrate. Thermal history data are then used to estimate the resultant primary dendrite arm spacing (PDAS), and semi-empirical correlations are used to approximate hardness, yield strength, and ultimate tensile strength (UTS). For processing parameters of feed rate = 1200&#xa0;mm/min, scan speed = 800&#xa0;mm/min, and nominal laser powers of 800–1200&#xa0;W, the model estimates PDAS on the order of 4–6&#xa0;µm, Vickers microhardness on the range of 195–200&#xa0;HV, yield strength of 365–420&#xa0;MPa and ultimate tensile strength (UTS) of 490–530&#xa0;MPa for 316&#xa0;L parts produced using this process.</p>

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Numerical modeling of a wire-laser directed energy deposition process

  • 期刊论文

  • 发表日期：

    2026年8月3日

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  • Nathan Stoetzel,
  • Aye Thiri Khaing,
  • Amir Shakibi,
  • Mohsen Eshraghi

摘要

Directed energy deposition (DED) is a novel additive manufacturing (AM) process which is revolutionizing the rapid production of large metal parts. Metal additive manufacturing methods feature extremely large cooling rates and smaller melt pools compared to traditional manufacturing methods, which results in smaller grain sizes and variance in material properties. While it can be difficult or expensive to experimentally measure melt pool data during the process, numerical simulations can offer a method to predict the effects of process parameters on the resultant melt pool geometry and microstructure. In this work, a computational fluid dynamics model was developed and validated against experimental single-track samples for melt pool geometry of 316L stainless steel wire deposited on a 304L stainless steel substrate. Thermal history data are then used to estimate the resultant primary dendrite arm spacing (PDAS), and semi-empirical correlations are used to approximate hardness, yield strength, and ultimate tensile strength (UTS). For processing parameters of feed rate = 1200 mm/min, scan speed = 800 mm/min, and nominal laser powers of 800–1200 W, the model estimates PDAS on the order of 4–6 µm, Vickers microhardness on the range of 195–200 HV, yield strength of 365–420 MPa and ultimate tensile strength (UTS) of 490–530 MPa for 316 L parts produced using this process.