Computational Techniques for Multi-Scale Modeling in Advanced Manufacturing: Multiscale Solidification Models
Sponsored by: TMS Materials Processing and Manufacturing Division, TMS Extraction and Processing Division, TMS: Computational Materials Science and Engineering Committee, TMS: Process Technology and Modeling Committee
Program Organizers: Adrian Sabau, Oak Ridge National Laboratory; Anthony Rollett, Carnegie Mellon University; Laurentiu Nastac, University of Alabama; Mei Li, Ford Motor Company; Alexandra Anderson, Gopher Resource; Srujan Rokkam, Advanced Cooling Technologies, Inc.
Thursday 8:30 AM
March 18, 2021
Room: RM 1
Location: TMS2021 Virtual
Session Chair: Anthony Rollett, Carnegie Mellon
8:30 AM
Computational Multi-Scale Modeling of Segregation and Microstructure Evolution during the Solidification of A356 Ingots Processed via a 2-Zone Induction Melting Furnace: Aqi Dong1; Laurentiu Nastac1; 1University of Alabama
In the current study, a stochastic mesoscopic model was applied to predict the evolution of the A356 microstructure (e.g., dendritic morphologies and columnar-to-equiaxed transition formation) in a 2-Zone induction melting and solidification furnace. The influence of process and material parameters on microstructure, such as initial melting temperature, ultrasonic stirring and cavitation, fluid flow conditions, cooling rate, temperature gradient, and nucleation and growth kinetics parameters for both equiaxed and columnar phases are studied. In addition, the macro-segregation of silicon during solidification of A356 in the crucible is also simulated. The results will be helpful for determining the solidification structure, mushy zone evolution in the crucible and assist in developing of comprehensive solidification maps of various Al-based alloys including those used in additive manufacturing.
8:55 AM
Microstructural Evolution and Defect Formation During Pulsed and Continuous Selective Laser Melting: Ian Mccue1; Steven Storck1; James Mastandrea1; Morgana Trexler1; 1Johns Hopkins Applied Physics Laboratory
Laser powder bed fusion additive manufacturing (AM) is a growing technology to produce unique components with complex geometries. However, an obstacle to its wide-spread use is understanding defect formation and microstructural evolution during AM. High energy densities, fast laser-scan speeds, and rapid cooling introduce a variety of defects and grain morphologies within a single melt pool. It is experimentally challenging to capture and assess these details, but insights have been garnered from continuum modeling techniques. Here, we use a high fidelity fluid dynamics model (CFD) – that includes laser ray tracing, recoil pressure, surface tension, and evaporative cooling – to compare and contrast melt pool dynamics during continuous and pulsed selective laser melting. Using a customized post-processing tool and statistical methods, we find that pulsed lasers systems produce higher pore fractions than continuous lasers, with a much smaller “fully dense” regime, but lead to smaller G/R values and refined microstructures.
9:20 AM
Computational Modeling of Nanoparticles Dispersion in Hybrid Process of Ink Jetting and Laser Powder Bed Fusion: Milad Ghayoor1; Bryce Cox1; Joshua Gess1; Somayeh Pasebani1; 1Oregon State University
Oxide dispersion strengthened alloys are metal-matrix composites in which nano-scale oxides inhibit grain growth at high temperatures providing improved mechanical properties and creep resistance. This study investigates the microstructure of 316L ODS alloy developed via hybrid of laser powder bed fusion and jetting approach. A laser powder bed fusion equipment was modified to enable ink jetting. The ink, containing nanoparticles of Al2O3, was selectively placed into the stainless steel powder bed. The laser consolidated the metal powder and nanoparticles into nanocomposite. A transient finite-difference heat transfer and fluid flow model was created to predict the motion of the nanoparticles throughout the hybrid process, with the goal of correlating nanoparticles placement to achieve a uniform dispersion and optimal thermal and mechanical properties. Model results are compared to experimental data and microstructural evolutions after laser powder bed fusion and post heat treatment.
9:45 AM Cancelled
Multi-scale, Multi-physics Modeling of Additive Manufacturing: Challenges and Potential Solutions: Dayalan Gunasegaram1; Anthony Murphy1; 1CSIRO
The metal additive manufacturing (AM) process is a sum of several sub-processes. These include the coating (raking) of alloy powders, their melting using a heat source, rapid solidification resulting in the formation of unique microstructures, and the development of residual stresses. The AM process starts with near-spherical powders that are tens of micrometers in diameter and ends with built parts that are tens of centimetres in dimension. The broad range of length and time scales, as well as the diverse physics influencing these sub-processes, make modeling AM a multi-scale, multi-physics problem. In this talk, we will take an in-depth look into the distinct challenges that are involved in such an endeavor and discuss potential solutions. We will also discuss the possibility of commencing a coordinated global effort towards developing open-source models that can be progressively updated. Some material for this talk is gleaned from an international Symposium organized by CSIRO.
10:10 AM
Multiphysics Simulation of Microstructure Evolution in Selective Laser Melting of AlSi10Mg: Dehao Liu1; Yan Wang1; 1Georgia Institute of Technology
Selective laser melting (SLM) builds parts by selectively melting metallic powders with a high-energy laser beam. Nevertheless, the lack of fundamental understanding of the process-structure-property relationship for better quality control inhibits wider applications of SLM. Recently, a mesoscale simulation approach, called phase-field and thermal lattice Boltzmann method (PF-TLBM), was developed to simulate microstructure evolution of alloys in SLM melt pool with simultaneous consideration of solute transport, heat transfer, phase transition, and latent heat effect. In this work, a nucleation model is introduced to simulate heterogeneous nucleation at the boundary of the melt pool. The effects of latent heat and cooling rate on dendritic morphology and solute distribution are studied. The simulation results of AlSi10Mg alloy suggest that the inclusion of latent heat is necessary because it reveals the details of the formation of secondary arms, reduces the overestimation of microsegregation, and provides more accurate kinetics of dendritic growth.