Additive Manufacturing: Advanced Characterization with Synchrotron, Neutron, and In Situ Laboratory-scale Techniques II: In Situ Monitoring of Directed Energy Deposition Processes
Sponsored by: TMS Structural Materials Division, TMS: Additive Manufacturing Committee, TMS: Advanced Characterization, Testing, and Simulation Committee
Program Organizers: Fan Zhang, National Institute of Standards and Technology; Donald Brown, Los Alamos National Laboratory; Andrew Chuang, Argonne National Laboratory; Joy Gockel, Colorado School of Mines; Sneha Prabha Narra, Carnegie Mellon University; Tao Sun, University of Virginia
Wednesday 8:30 AM
March 2, 2022
Location: Anaheim Convention Center
Session Chair: Sneha Narra, Carnegie Mellon University; Jordan Weaver, National Institute of Standards and Technology
8:30 AM Invited
Porosity Formation, Evolution, and Solidification in Powder-blown Directed Energy Deposition Additive Manufacturing Using High-speed Synchrotron X-ray Imaging: Sarah Wolff1; Hui Wang1; Mahsa Valizadeh1; Marwan Haddad1; Benjamin Gould2; 1Texas A&M University; 2Argonne National Laboratory
The laser-based powder-blown directed energy deposition (L-DED) additive manufacturing process is promising for its fabrication of complex, multi-material metallic parts with superior mechanical parts for a wide range of applications. However, porosity in L-DED parts is common due to rapid solidification, and can pose obstacles in deteriorating mechanical properties, and therefore part qualification and certification. This talk will discuss some of the fundamental interactions between in-flight powder particles and the underlying melt pool that lead to porosity in the L-DED process. High-speed synchrotron X-ray imaging (up to 80,000 fps) experiments at the 32-ID beamline at the Advanced Photon Source in Argonne National Laboratory show porosity mechanisms that originate from feedstock powders, laser attenuation during deposition, the interplay between the kinetic and surface energies during deposition, as well as particle characteristics of shape, size, and chemical composition. In addition, preliminary machine learning training methods can identify porosity in X-ray images.
Blown Powder Additive Manufacturing Process Replicator for High Speed Optical, Infra-red and Synchrotron X-ray Imaging: Sebastian Marussi1; Yunhui Chen1; Samuel Clark2; Robert Atwood3; Veijo Honkimaki4; Alexander Rack4; Ben Saunders5; Martyn Jones5; Peter Lee1; 1University College London; 2Argonne National Laboratory; 3Diamond Light Source; 4European Synchrotron Radiation Facility; 5Rolls-Royce plc.
With increasing demand for additive manufactured (AM) complex shaped critical components, a better understanding of the underlying phenomena is required. To achieve this, we developed a second generation blown powder directed energy deposition additive manufacturing process replicator (BAMPR-II) to simulate industrial direct energy deposition (DED) process in a synchrotron beamline. We determined the design based on the build process and experimental constrains, evaluating the trade-offs required. The key design criteria included the capacity to be integrated on a range of beamlines, to enable high-speed X-ray radiography and diffraction to capture melt pool dynamics and microstructural feature evolution. We also incorporated a correlative high-speed infra-red and optical imaging, enabling the synchrotron imaging to be used for calibrating surface-based process responses. We conclude that in situ process replication of DED provides a means to help transform our understanding of AM processing and develop new strategies to improve product quality.
In-situ Synchrotron X-ray Diffraction Experiments to Study the Role of Solid-state Thermal Cycling on Microstructure Formation during Metal AM: Steve Gaudez1; Wolfgang Pantleon2; Manas V. Upadhyay1; 1CNRS UMR7649 Ecole Polytechnique; 2Technical University of Denmark
During Additive Manufacturing (AM) of metals, the material undergoes rapid solidification just after deposition. Then, until the end of the AM process, it is subjected to Solid-State Thermal Cycling (SSTC). It is important to study the role of SSTC on the microstructure evolution during AM, because the microstructural features determining the materials response such as texture, internal strains, etc., are affected by SSTC. Separating the microstructural changes due to SSTC from those occurring during solidification requires time-resolved investigations. To that end, in-situ synchrotron X-ray diffraction (XRD) and radiography experiments can be very useful. We have developed a novel miniature Laser Metal Deposition (mini-LMD) machine to perform such experiments. Preliminary results of in-situ powder XRD and High-Resolution Reciprocal Space Mapping (HRRSM) experiments are presented elucidating the role of SSTC on the evolution of the polycrystalline grain structure as well as the intragranular microstructure for different printing parameters.
Characterizing Void Morphology in Single-track Builds of Directed Energy Deposition Using New Image Processing Techniques for X-ray Computed Tomography Data Sets: Newell Moser1; Edward Garboczi1; Samantha Webster2; Jian Cao2; 1National Institute of Standards and Technology; 2Northwestern University
Single-track builds of Ti-6Al-4V were manufactured via Directed Energy Deposition (DED) at the Advanced Photon Source (Argonne National Laboratory); high-speed X-ray imaging was performed to capture real-time interactions between the melt pool and the metal particles. Afterwards, at the National Institute of Standards and Technology, the DED samples were characterized using micro X-ray Computed Tomography (X-ray CT), which is the focus of this presentation. The resultant (volume-based) image sequences were carefully segmented using a new, open-source suite of Python scripts that strike a balance between computational speed and memory consumption. Moreover, a variety of techniques, including spherical harmonics, were utilized to characterize the shape, size, orientation, and distribution of the internal voids. By linking these void statistics to the chaotic process of DED, critical insights were revealed that relate process parameters to the mechanisms that drive the formation of voids.
10:00 AM Break
Deep Learning for Real-time Non-destructive Inter-layer Quality Control during Additive Manufacturing Process: Steven Hespeler1; Michael Juhasz2; Ehsan Dehghan-Niri1; Jeffrey Riemann2; 1New Mexico State University; 2FormAlloy Technologies, Inc.
Defects are a leading issue for rejection of parts manufactured through Additive Manufacturing (AM). Typically, defect measurements are gathered post-production with computerized tomography (CT) scans which are difficult to implement into real-time monitoring. In-situ monitoring of AM produced parts was employed to collect real-time data during a Directed Energy Deposition (DED) build. Machine Learning (ML) methods were utilized on time sensitive parameters during the build to provide a defect classification system. Statistical analysis performed evaluated feature impacts on inter-layer classification and investigates the relationships between these features. A threshold was applied to detect porosity sizes and quantities that render individual layers as acceptable or unacceptable. We demonstrate the effectiveness of using a Deep Learning (DL) technique for the purpose defect monitoring. The customized DL technique is shown to be highly effective at classifying acceptable/unacceptable layers real-time during build process.
10:35 AM Invited
Overview of Modelling for Deformation Temperature and Stress Prediction for Wire Arc Large Scale Additive Manufacturing: Andrzej Nycz1; Yousub Lee1; Srdjan Simunovic1; Luke Meyer1; Chris Masuo1; William Carter1; Mark Noakes1; 1Oak Ridge National Laboratory
Wire-arc additive manufacturing is a new field of 3D printing with roots in welding, automation, and classic fused deposition modeling. Due to part size potentially reaching 8ft or more, unique challenges are created for thermal management, deformation, and residual stress. While these challenges are known to some degree in welding and metal powder beds, they are greatly magnified in large scale wire-arc metal additive manufacturing. This work presents the results and findings from the development of wire-arc additive manufacturing at Oak Ridge National Laboratory.