Additive Manufacturing Modeling and Simulation: Microstructure, Mechanics, and Process: Poster Session
Sponsored by: TMS Computational Materials Science and Engineering Committee
Program Organizers: Jing Zhang, Purdue University in Indianapolis; Brandon McWilliams, US Army Research Laboratory; Li Ma, Johns Hopkins University Applied Physics Laboratory; Yeon-Gil Jung, Korea Institute of Ceramic Engineering & Technology
Tuesday 4:45 PM
October 19, 2021
Room: Exhibit Hall B
Location: Greater Columbus Convention Center
Session Chair: Jing Zhang, Indiana University - Purdue University Indianpolis
P3-1: Creep Modeling of 3D Printed Nickel Based Superalloy: Harshal Dhamade1; Abhilash Gulhane1; Tejesh Dube1; Jing Zhang1; 1Indiana University – Purdue University Indianapolis
The objective of this research is to model the creep behavior of nickel alloy 718 manufactured via the selective laser melting process. A finite element (FE) model with a subroutine is created for simulating the creep mechanism for 3D printed nickel alloy 718 components. Using a multi-regime Kachanov-Rabotnov creep model, the FE model is capable to simulate both the secondary and tertiary creep behaviors. A continuum damage mechanics (CDM) approach is employed by implementing a user-defined subroutine formulated to accurately capture the creep mechanisms. Using a calibration code, the material constants are calculated. Through validation study, the model developed in this work can reliably predict the creep behavior for 3D printed metals under uniaxial conditions.
P3-2: Design A Syringe Pump Extruder Type 3D Bioprinter: Haoyee Yeong1; Eli Kindomba1; Bavly Shehata1; Alyaa Idris1; Jing Zhang1; 1Indiana University – Purdue University Indianapolis
In this work, we demonstrated building a low-cost bio 3D printer by adapting a syringe pump extruder to a regular Fused Deposition Modeling (FDM) plastic 3D printer. The relationship between the ink composition, viscosity, and extruder size, were investigated. In parallel with the experimental tests, we developed a CAD model that helps visualize the motion mechanisms. The printer has the potential to fabricate biomaterials that maximally imitate biological tissues and cells.
Poster
P3-3: Finite Element Modeling of Coating Thickness Prediction in Electron Beam Physical Vapor Deposition Process: Anvesh Dhulipalla1; Yafeng Li2; Sugrim Sagar1; Jian Zhang1; Xuehui Yang1; Dan Koo1; Hye-Yeong Park3; Yeon-Gil Jung3; Jing Zhang1; 1Indiana University – Purdue University Indianapolis; 2Tiangong University; 3Changwon National University
The electron beam physical vapor deposition (EB-PVD) process is often used to produce thermal barrier coatings (TBCs). This method has a wide application in the aerospace industry. The computational model can contribute to enhanced control of the coating process by improving efficiency. In this work, a ray tracing based finite element model has been developed. Assuming a line-of-sight coating process and considering the shadow effects. The model is successfully validated by coating prediction on regular shaped components, and modeling results are in good agreement with either the raytracing-based analytical solution or experimental data. Then a coating thickness prediction in a rotary gas turbine blade is demonstrated.
P3-4: Modeling Charpy Impact Property of 3D Printed 718 Nickel Alloys Using the Smoothed Particle Hydrodynamics Method: Sugrim Sagar1; Jian Zhang1; Jing Zhang1; 1Indiana University – Purdue University Indianapolis
In this work, a smoothed particle hydrodynamics (SPH) based model is developed to simulate the Charpy impact behavior of additively manufactured nickel-based alloy 718. The Johnson-Cook (J-C) constitutive material and damage models that describe the strain rate, temperature softening, and damage effects are used in this study. The SPH model is validated using the tensile test at a range of temperatures and strain rates. Then the SPH model is applied to simulate the Charpy impact test at various testing temperatures. The modeling results are compared against the experimental data.
P3-5: Reinforcement Learning Aided Simulations for Determining Process Parameters for Optimizing Microstructure in LPBF Additive Manufacturing Parts: Junwon Seo1; Joseph Pauza1; Anthony Rollett1; 1Carnegie Mellon University
3D-printing of alloys via laser powder bed fusion (LPBF) additive manufacturing has led us to a new possibility of manufacturing complex parts for various applications. However, current printing technique generally relies on a set of predefined process parameters for the entire process. In this research, the optimal process parameter function for 3D-printing an optimized microstructure in IN718 is obtained by applying reinforcement learning technique to mesoscale Monte-Carlo grain growth simulation data. The melt pool morphology and scan strategy in the microstructure simulations is varied with respect to time to generate the data to train the algorithm. The algorithm chooses its optimal process parameter for each time step, which in turn leads us to an adequate parameter selection for achieving optimized microstructure in parts. This research suggests a new opportunity for controlling the process parameter during the printing process to obtain desirable microstructural features and properties in printed parts.
P3-6: Student Design Project of Design a Mechanical Ventilator Prototype during the Pandemic: Francis Iloeje1; Sunday Folorunso1; Haoyee Yeong1; Eli Kindomba1; Yafeng Li2; Jing Zhang1; 1Indiana University – Purdue University Indianapolis; 2Tiangong University
The Covid pandemic poses a challenge for student education. However, it may also provide a unique opportunity for students to tackle some real-world issues. In this work, we demonstrated building a low-cost open-source mechanical ventilator prototype. The process of the design and assembly of the system were demonstrated. In parallel with the experimental tests, we developed a CAD model that helps visualize the motion mechanisms. The ventilator prototype has the potential to help the Covid patients with assisted breath needs.
P3-7: Virtual Reality Modules of 3D Printing Laboratories for Additive Manufacturing Education: Cooper Zuranski1; Shambhuraj Wadghule1; Jing Zhang1; 1Indiana University – Purdue University Indianapolis
In this work, we developed modules aiming to educate the students on variables and general function of the 3D printers through Virtual Reality (VR) simulation and interaction, with the goal of improving students’ learning experience on additive manufacturing (AM).We demonstrated two VR modules, both plastic and metal AM laboratories. The procedure of programming the modules was introduced. The functionalities of the modules were presented in the videos. We showed that how the VR modules can be used as an innovative tool for AM education.