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1. Digital Fringe Projection for Interlayer Print Defect Characterization in Directed Energy Deposition

   https://doi.org/10.1115/ISFA2024-141314  

   Hu, Guanzhong; Zha, Rujing; Wang, Yaoke; Cao, Jian; Guo, Ping (July 2024, American Society of Mechanical Engineers)

   Abstract Directed Energy Deposition (DED) is one of the main additive manufacturing (AM) families, enabling the fabrication of multi-material parts with high material addition rates. However, the incremental nature of DED fabrication makes it prone to local defect formation due to process condition fluctuations. Known for its rapid and precise 3D surface measurement capabilities, digital fringe projection (DFP) was previously demonstrated in process monitoring for powder bed AM. This study brings DFP to the DED process through development of a custom motor stage system and validates its effectiveness in assessing surface topography and build height measurement. Measurements were taken on both correctly deposited builds and builds with off-nominal deposition conditions, where the system was able to detect pitting as small as 0.425 mm in the lateral size and 0.154 mm in depth in the case of reduced laser energy. This work paves the way for future machine learning-enabled interlayer defect identification, classification, and healing via altering subsequent processing settings. 

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2. Harnessing metastability for grain size control in multiprincipal element alloys during additive manufacturing

   https://doi.org/10.1038/s41467-025-56616-0  

   Wakai, Akane; Bustillos, Jenniffer; Sargent, Noah; Stokes, Jamesa_L; Xiong, Wei; Smith, Timothy_M; Moridi, Atieh (February 2025, Nature Communications)

   Abstract Controlling microstructure in fusion-based metal additive manufacturing (AM) remains a significant challenge due to the many parameters that directly impact solidification condition. Multiprincipal element alloys (MPEAs), also known as high entropy alloys, offer a vast compositional space to design for microstructural engineering due to their chemical complexity and exceptional properties. Here, we use the FeMnCoCr system as a model platform for exploring alloy design in MPEAs for AM. By exploiting the decreasing stability of the face-centered cubic phase with increasing Mn content, we achieve notable grain refinement and breakdown of epitaxial columnar grain growth. We employ a multifaceted approach encompassing thermodynamic modeling, operando synchrotron X-ray diffraction, multiscale microstructural characterization, and mechanical testing to gain insight into the solidification physics and its ramifications on the resulting microstructure of FeMnCoCr MPEAs. This work aims toward tailoring desirable grain sizes and morphology through targeted manipulation of phase stability, thereby advancing microstructure control in AM applications. 

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3. Weldability study of alloys 625 and 718 fabricated by laser-based additive manufacturing

   https://doi.org/10.1016/j.jmapro.2025.02.051  

   Guzman, Jhoan; Riffel, Kaue C; Evans, William; Brizes, Eric; Avedissian, Nicholas; Farias, Francisco_Werley Cipriano; Ramirez, Antonio J (May 2025, Journal of Manufacturing Processes)

   Nickel-based alloys, Alloys 625 and 718, are widely used in the aerospace industry due to their excellent corrosion resistance and high strength at elevated temperatures. Recently, these alloys have been utilized to manufacture rocket engine components using additive manufacturing (AM) technologies such as laser powder bed fusion (LPBF) and powder-blown laser-based directed energy deposition (DED). These technologies offer faster and more cost-effective production while enabling the fabrication of near-net-shape parts that are subsequently joined by welding. However, solidification cracking susceptibility varies significantly between AM and conventionally processed materials, and limited weldability characterization has been conducted on AM-fabricated materials. This study assesses the weld solidification cracking susceptibility of Alloys 625 and 718 produced by wrought (mill-rolled), LPBF, and DED using transverse varestraint testing, Scheil-Gulliver simulations, the Crack Susceptibility Index (CSI), and the Flow Resistance Index (FRI). Transverse varestraint testing revealed that AM parts exhibited higher susceptibility due to the presence of larger and elongated grains in the fusion zone, affecting the weld solidification cracking response. In Alloy 625, the LPBF condition exhibited the highest maximum crack distance (MCD) of 2.35 ± 0.16 mm, compared to 1.56 ± 0.06 mm for wrought and 1.72 ± 0.10 mm for DED. Similarly, in Alloy 718, the DED condition showed the highest MCD of 2.93 ± 0.41 mm, while the wrought condition had an MCD of 2.01 ± 0.12 mm, and the LPBF condition reached 3.01 ± 0.33 mm at 5 % strain, without a clearly defined saturation strain. Although wrought materials demonstrated greater resistance to solidification cracking, solidification simulations did not correlate with the experimental testing, as they do not account for microstructural and mechanical factors, relying solely on chemistry. 

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4. Searching for Unknown Material Properties for AM Simulations

   https://doi.org/10.3390/met13111798  

   Flood, Aaron; Boillat, Rachel; Isanaka, Sriram Praneeth; Liou, Frank (November 2023, Metals)

   Additive manufacturing (AM) simulations are effective for materials that are well characterized and published; however, for newer or proprietary materials, they cannot provide accurate results due to the lack of knowledge of the material properties. This work demonstrates the process of the application of mathematical search algorithms to develop an optimized material dataset which results in accurate simulations for the laser directed energy deposition (DED) process. This was performed by first using a well-characterized material, Ti-64, to show the error in the predicted melt pool was accurate, and the error was found to be less than two resolution steps. Then, for 7000-series aluminum using a generic material property dataset from sister alloys, the error was found to be over 600%. The Nelder–Mead search algorithm was then applied to the problem and was able to develop an optimized dataset that had a combined width and depth error of just 9.1%, demonstrating that it is possible to develop an optimized material property dataset that facilitates more accurate simulation of an under-characterized material. 

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5. Temporally continuous thermofluidic–thermomechanical modeling framework for metal additive manufacturing

   https://doi.org/https://doi.org/10.1016/j.ijmecsci.2023.108424  

   Mathews, Ritin; Nagaraja, Kishore Mysore; Zhang, Runyu; Sunny, Sumair; Yu, Haoliang; Marais, Deon; Venter, Andrew; Li, Wei; Lu, Hongbing; Malik, Arif (September 2023, International Journal of Mechanical Sciences)

   M. Wiercigroch, editof-in-chief (Ed.)

   Additive manufacturing (AM) is known to generate large magnitudes of residual stresses (RS) within builds due to steep and localized thermal gradients. In the current state of commercial AM technology, manufacturers generally perform heat treatments in effort to reduce the generated RS and its detrimental effects on part distortion and in-service failure. Computational models that effectively simulate the deposition process can provide valuable insights to improve RS distributions. Accordingly, it is common to employ Computational fluid dynamics (CFD) models or finite element (FE) models. While CFD can predict geometric and thermal fluid behavior, it cannot predict the structural response (e.g., stress–strain) behavior. On the other hand, an FE model can predict mechanical behavior, but it lacks the ability to predict geometric and fluid behavior. Thus, an effectively integrated thermofluidic–thermomechanical modeling framework that exploits the benefits of both techniques while avoiding their respective limitations can offer valuable predictive capability for AM processes. In contrast to previously published efforts, the work herein describes a one-way coupled CFDFEA framework that abandons major simplifying assumptions, such as geometric steady-state conditions, the absence of material plasticity, and the lack of detailed RS evolution/accumulation during deposition, as well as insufficient validation of results. The presented framework is demonstrated for a directed energy deposition (DED) process, and experiments are performed to validate the predicted geometry and RS profile. Both single- and double-layer stainless steel 316L builds are considered. Geometric data is acquired via 3D optical surface scans and X-ray micro-computed tomography, and residual stress is measured using neutron diffraction (ND). Comparisons between the simulations and measurements reveal that the described CFD-FEA framework is effective in capturing the coupled thermomechanical and thermofluidic behaviors of the DED process. The methodology presented is extensible to other metal AM processes, including power bed fusion and wire-feed-based AM. 

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