Additive Manufacturing Modeling and Simulation: AM Materials, Processes, and Mechanics: Additive Manufacturing Modeling and Simulation - Online Process Monitoring, Non-mechanical Property Characterization
Sponsored by: TMS Additive Manufacturing Committee
Program Organizers: Jing Zhang, Indiana University – Purdue University Indianapolis; Brandon McWilliams, US Army Research Laboratory; Li Ma, Johns Hopkins University Applied Physics Laboratory; Yeon-Gil Jung, Korea Institute of Ceramic Engineering & Technology

Wednesday 8:00 AM
November 4, 2020
Room: Virtual Meeting Room 2
Location: MS&T Virtual

Session Chair: Jing Zhang, Indiana University – Purdue University Indianapolis; Brandon McWilliams, CCDC Army Research Laboratory; Li Ma, Johns Hopkins University Applied Physics Laboratory; Yeon-Gil Jung, Changwon National University


8:00 AM  
In-situ Monitoring of Powder Flow in Direct Energy Deposition Additive Manufacturing: Baily Thomas1; Abdalla Nassar1; Steve Brown1; Matthew Milanek1; Jason Scherer1; 1Penn State University
    In the Direct Energy Deposition (DED) additive manufacturing (AM), one of the primary parameters varied is powder flow. Systematic and anomalous variations in powder flow rate influence deposition geometry and build quality. Here, we present an in-situ laser and camera based monitoring method to record and analyze powder flow on an Optomec LENS MR-7 DED system. Via calibration of the developed methods, we demonstrate the ability to measure overall mass flow rate and individual-nozzle mass flow rates from a multi-nozzle DED system. The developed methods allow for in-situ monitoring of flow rate and detection of powder flow anomalies.

8:20 AM  
Property Measurements for Modeling the Process-structure-property Relationships in Additive Manufacturing: Gwendolyn Bracker1; Madeline Scott1; Elizabeth Hodges1; Michael SanSoucie1; Robert Hyers1; 1University of Massachusetts
    Current work in additive manufacturing seeks to apply a wide variety of modeling techniques to the process, structure, properties, and behavior of both additive manufacturing processes and components. However, these models all require accurate input data for the simulated conditions to predict the process and performance of the resulting parts. In processing simulations, modeling the melt behavior requires accurate data on the viscosity and surface tension to predict heat transfer, fluid flow, and their interactions with the developing microstructure. The necessary precision is difficult to achieve using conventional processing techniques due to the high temperature and reactive behavior of molten metals. Containerless processing provides a unique opportunity to measure the surface tension and viscosity of a melt without the influence of an interface between the melt and a container. This technique has been applied to numerous alloys, including Inconel 625.

8:40 AM  
Control of High-temperature Drop-on-demand Metal Jetting through Numerical Modelling and Experimentation: Negar Gilani1; Nesma Aboulkhair1; Marco Simonelli1; Ian Ashcroft1; Richard Hague1; 1University of Nottingham
    Metal jetting entails dispensing and depositing molten metal droplets at precise locations. This opens opportunities for additive manufacturing of intricate metallic components. Numerous applications such as flexible circuits, advanced electronic components and biotechnologies are considered using the novel technique introduced here, MetalJet. It has the capability of producing metallic micro-droplets (~70 µm in diameter) with melting points up to 2000 °C at frequencies up to 2 kHz. Here we study the deposition of Tin droplets on various substrates through computational modelling and experimentation. Tin is chosen since it provides the opportunity of investigating wide droplet temperature ranges. The experimentation consists of printing and characterizing 3D objects while a 3D sequentially coupled thermomechanical finite element model is developed for the modelling. These provide insights into the fundamental physical phenomena of the MetalJet process which are unknown to date, including inter-droplets bonding and adhesion to the substrate, residual stress build-up and deformations.