Additive Manufacturing: Advanced Characterization with Synchrotron, Neutron, and In Situ Laboratory-scale Techniques II: On-Demand Oral Presentations
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, Northwestern University

Monday 8:00 AM
March 14, 2022
Room: Additive Technologies
Location: On-Demand Room

Solidification Crack Propagation and Morphology Dependence on Processing Parameters in AA6061 from Ultra-high-speed X-ray Visualization: Nadia Kouraytem1; Po-Ju Chiang2; Runbo Jiang2; Christopher Kantzos2; Joseph Pauza2; Ross Cunningham2; Ziheng Wu2; Guannan Tang2; Niranjan Parab3; Cang Zhao3; Kamel Fezzaa3; Tao Sun3; Anthony Rollett2; 1Utah State University; 2Carnegie Mellon University; 3Argonne National Laboratory
    Solidification or hot cracks are commonly observed defects in a number of metal alloys and may lead to deterioration of additively manufactured parts quality. In this study, ultra-high-speed x-ray radiography experiments enable the observation and characterization of bundles of hot-cracks that form in monobloc AA6061 substrate. The crack bundles are related to meltpool characteristics and pore formation. Crack propagation rate is also presented for the case of a crack that initiates from a pore. Two types of relevant pore formation are also described, namely keyhole porosity and crack-remelting porosity. The results of this study are expected to facilitate the validation of theoretical and numerical models of solidification cracking.

In-situ Characterization of Laser Powder Bed Fusion Processes at the Stanford Synchrotron Light Source: Kevin Stone1; 1SLAC National Accelertor Laboratory
    Laser powder bed fusion (LPBF) is a method of additive manufacturing where a high powered laser is scanned over a thin bed of metallic powder creating a solid layer, this is then repeated to form larger structures. Much of the melting, resolidification, and subsequent cooling take place at much higher rates and with much higher thermal gradients than in traditional metallurgical processes, with much of this occurring below the surface. Using high speed X-ray characterization at SSRL, we nondestructively probe the dynamics of melting and resolidification during LPBF. With high speed X-ray imaging, we observe the vapor depression and potential void formation. Using high speed in-situ X-ray diffraction, we are able to track phase transformations, determine subsurface cooling rates, and distinguish between the melted and nearby heat affected zones on millisecond time scales. These results provide a direct measure of the subsurface thermal history.

Predicting WAAM Material Properties via Machine Learning: Pinelopi Kyvelou1; Leroy Gardner1; Lei Zou2; Stasha Lauria2; Carlos Gonzales3; Filippo Gilardi4; Odysseas Krystalakos4; Amine Ammar5; Victor Champaney5; Mustafa Megahed6; 1Imperial College; 2Brunel University; 3AIMEN; 4MX3D; 5ENSAM; 6ESI Group
    Predicting material quality in metallic additive manufacturing (AM) is challenging due to the large number of parameters controlling the final output. Plates of different steel grades, thicknesses, toolpath trajectories and dwell times are manufactured using Wire-arc additive manufacturing (WAAM). From these plates, coupons are extracted at different orientations and subjected to tensile tests to determine their mechanical properties. The voltage and current signals employed during AM are monitored and analyzed to identify anomalies both manually and via machine learning. The trained neural network predicts the input signals reliably. The specimens are characterized to obtain mechanical properties as functions of the parameters studied. Data analytics identifies the most influential input parameters on mechanical properties and a regression model is developed to predict mechanical properties as a function of input signals. This presentation will discuss the experiments and the predicted mechanical properties arising from WAAM processes using the developed digital platform.

Neutron Imaging Capabilities and Recent Development at High Flux Isotope Reactor: Yuxuan Zhang1; Leslie Butler2; Hassina Bilheux1; Kyungmin Ham2; Jean Bilheux1; Wieslaw Stryjewski2; Erik Stringfellow1; Michael Vincent2; 1Oak Ridge National Laboratory; 2Louisiana State University
     Neutron imaging is a non-destructive technique that investigates internal features/structures of an object. The neutron’s high penetration depth in metals and high sensitivity to light elements (H, Li, etc.) have made neutron imaging a unique tool in many research fields. Neutron grating interferometry (nGI), implemented in the Talbot-Lau interferometer setup, enables simultaneous access to three imaging modalities: attenuation, differential phase contrast, and scattering. In summary, cracks, voids, and porosity are visible in thick metal structures.In this work, current capabilities at the neutron imaging instrument (CG-1D) at High Flux Isotope Reactor (HFIR) will be presented. Additionally, the recent progress in implementing a neutron grating interferometer will be reported.

Controlling Interdependent Meso-nanosecond Dynamics and Defect Generation Using a Digital Twin: Saad Khairallah1; Brian Simonds2; Tao Sun3; Michael Stokes4; Alexey Volkov4; Aiden Martin1; John Lee1; Gabe Guss1; Nicholas Calta1; Joshua Hammons1; Michael Nielsen1; Kevin Chaput5; Edwin Schwalbach5; Megna Shah5; Michael Chapman5; Trevor Willey1; Alexander Rubenchik1; Andrew Anderson1; Y. Morris Wang6; Manyalibo Matthews1; Wayne King7; 1Lawrence Livermore National Laboratory; 2NIST; 3University of Virginia; 4University of Alabama; 5Air Force Research Laboratory; 6University of California, Los Angeles; 7The Barnes Group Advisors
    We used ALE3D high-fidelity multi-physics model, which was verified with in-situ X-ray and other diagnostics experiments, to study laser-powder and laser-melt pool interactions at short time scales. We captured different modes of laser interactions that involve expulsion of spatter, shadowing and oscillations in absorptivity. We report on self-replicating spatter, that once formed, become hard to get rid of due to a self-replication mechanism that involves loose particles in the powder layer. We explain how pre-sintering the powder could be a strategy to mitigate this effect. Spatter beyond a size threshold can cause pores due to laser shadowing. We identified the laser scan strategy as one source of these large spatter sizes and derived a stability criterion to prevent them. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE- AC52-07NA27344. Lawrence Livermore National Security, LLC. LLNL-ABS-799067.

Flexible Simulation Augmentation for DED AM Using In-situ Digital Image Correlation, Multispectral Infrared Imaging, and Neutron Scattering Validation: James Haley1; Stephan DeWitt1; Thomas Feldhausen1; Bruno Turcksin1; 1Oak Ridge National Laboratory
    In Directed Energy Deposition (DED), transient thermal fields induce scan strategy dependent residual stresses and distortion. Previously developed in-situ Digital Image Correlation (DIC) and infrared imaging techniques can directly measure dynamic strains and temperatures; however, such techniques are limited to the surfaces of deposited components. In this talk, we’ll explore how neutron scattering experiments and thermal simulations can augment these inexpensive, scalable imaging techniques. Neutron scattering can be used to validate the DIC-measured surface strains or to provide residual stress data inside the component. Component-scale thermal simulations can provide the thermal fields inside the component. Taking a data assimilation approach, we discuss the use of an ensemble Kalman filter to dynamically correct the simulation to be consistent with in-situ infrared imaging, allowing for a new degree of accuracy in understanding transient behavior in AM.

Keyhole Melting Regimes and Porosity Formation during Laser Powder Bed Fusion Additive Manufacturing: Yuze Huang1; Tristan G. Fleming2; Chu Lun Alex Leung1; Samuel J. Clark1; Sebastian Marussi1; Kamel Fezzaa3; Jakumeit Jürgen4; Jeyan Thiyagalingam5; Peter D. Lee1; 1University College London; 2Queen's University; 3Argonne National Laboratory; 4Access e.V.; 5Science and Technology Facilities Council
    Keyhole porosity is a major concern in laser powder-bed fusion, degrading the fatigue life of fabricated components. However, the keyhole fluctuation and porosity formation mechanism have not been fully understood. We have used synchrotron X-ray imaging to reveal keyhole fluctuation and collapse behaviours, unveiled their underlying mechanisms using quantitative image analysis. It was found that (i) the onset of keyhole porosity starts from a transition keyhole regime, created by high laser power-velocity conditions, showing the fastest radial fluctuations with frequency ~10 kHz; (ii) unlike the keyhole bottom collapse in the unstable keyhole regime, keyholes tend to collapse at rear-wall zone in the transition regime; (iii) The keyhole regimes are found to be well defined by the keyhole front-wall angle, which collapses to a single function of the scaling enthalpy.These findings provide vital guidance for pore suppression via real-time control of keyhole dynamics in LPBF and other high-beam-energy processing techniques.

Material Processing-microstructure-mechanical Property Relationship of Supersolidus Liquid Phase Sintered Binder Jet Additively Manufactured H13 Tool Steel: Jia Liu1; Rangasayee Kannan2; Dalong Zhang1; Tingkun Liu1; Peeyush Nandwana2; Arun Devaraj1; 1Pacific Northwest National Laboratory; 2Oak Ridge National Laboratory
    Additive manufacturing (AM) of H13 tool steels by binder jet 3D printing (BJ3DP) and pressureless supersolidus liquid phase sintering (SLPS) provides a low-cost alternative manufacturing method for components with intricate geometrical features. However, the understanding of processing-microstructure-mechanical property relationships of BJ3DP-SLPS produced H13 tool steel is still in its infancy, which makes it challenging to maximize part performance via printing and post-processing methods. Here, we leverage atom probe tomography and transmission electron microscopy along with thermodynamic calculations to reveal the microstructure-mechanical property relationships in as-sintered H13 tool steel. The in-situ atom probe tomography is used to develop a deep understanding of the comprehensive processing-microstructure relationship at various stages. The morphology and composition of precipitates in the liquid channels are identified and associated with their mechanical property. These results provide direction to modify the microstructure of the AM-produced components by additional heat treatments to enhance their mechanical properties.