Additive Manufacturing Modeling and Simulation: AM Materials, Processes, and Mechanics: Additive Manufacturing Modeling and Simulation - Residual Stress, Fatigue Property, and Thermal Property
Sponsored by: TMS Additive Manufacturing 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
Monday 2:00 PM
November 2, 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
2:00 PM
Development of Temperature History Profiles for Production of Ti-6Al-4V Using a Semi-Analytical Model: Lonnie Smith1; Amit K Verma1; Andrew (Drew) Huck1; P. Chris Pistorius1; Anthony (Tony) Rollett1; 1Carnegie Mellon University
Directed energy deposition (DED) is an additive process that uses a laser beam to melt a feed of hot wire, which creates a melt pool on the surface of a metallic substrate. The work here seeks to generate temperature history profiles for layer-wise development of parts built using Ti-6Al-4V (Ti64). By utilizing a modified version of the Rosenthal solution to the moving heat source problem, a simple, semi-analytical model that incorporates system parameters and multiple modes of heat transfer, including convective heat loss, is used to produce plausible temperature history profiles. The results achieved with this model are obtained quickly (in comparison to ANSYS based solutions) and will be used to develop predictions of the fraction of phases that form in the creation of Ti64 parts via DED. Validation of the simulations is achieved by calibrating the model against metallographic information obtained from etching the cross sections of fabricated samples.
2:20 PM Invited
A System Dynamics approach to submodels for Residual Stress Predictions of SLM Parts: Jose Mayi-Rivas1; Seetha Raghavan1; 1University of Central Florida
Accurate predictions of residual stress distributions within Additive Manufacturing parts typically require complex thermomechanical finite element models (FEM). One of the main methods to reduce model complexity involves the use of a micro or mesoscale submodel, results of which are then applied to a macroscale simulation to obtain complete displacement and stress fields. This work proposes an innovative approach by replacing the micro level FEM with energy-based system dynamic equations that can be explicitly correlated to the sum of all contributions to the residual stress. Results are validated with existing FEM submodels in literature and eventually with X-ray diffraction measurements.
2:40 PM
Stress State Dependent Plasticity and Fracture Properties of Additively Manufactured Stainless Steel 316L: Alexander Wilson-Heid1; Allison Beese1; 1Pennsylvania State University
A stress state dependent plasticity and fracture description for laser powder bed fusion (L-PBF) additively manufactured 316L has been developed. Experimental tests under five dissimilar stress states were used to probe the elastoplastic behavior and fracture strain to failure was evaluated under six different stress states. Both plasticity and fracture behavior were characterized in two orientations with respect to the build direction. Using a combined experimental and computational modeling/simulation approach, an anisotropic plasticity model (Hill 1948 anisotropic yield criterion, associated flow rule, and an isotropic hardening law) and ductile fracture model (modified Mohr-Coulomb) were calibrated and validated. The L-PBF material was found to be more ductile for samples whose tensile axis was parallel to the vertical build direction for all stress states, while the strength of the material was found to be isotropic for pure shear and shear dominated stress states, and anisotropic only under tension dominated loading.
3:00 PM
Defect-based Fatigue Model for AlSi10Mg Produced by Laser Powder Bed Fusion Process: Avinesh Ojha1; Wei-Jen Lai1; Ziang Li1; 1Ford Motor Company
Defect is inevitable in metal parts built by laser powder bed fusion (L-PBF) process. The size, shape, and location of the defect play critical roles in determining material’s fatigue strength. Due to the random nature of defect in the part, statistical method must be employed for fatigue strength estimation. A defect-based statistical fatigue strength model has been developed and validated for L-PBF AlSi10Mg containing keyhole defects with different size distributions. Artificial defects were also introduced for model validation. The model modified Murakami’s formulation to address material dependence and followed Romano’s approach to consider the statistical behavior of fatigue strength. However, the proposed model is unable to predict fatigue strength of material containing lack-of-fusion defect possibly due to higher stress concentration induced by its morphology.