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Meeting MS&T23: Materials Science & Technology
Symposium Additive Manufacturing Modeling, Simulation, and Machine Learning: Microstructure, Mechanics, and Process
Presentation Title Computational and Experimental Study of Up-/Down-surface Characteristics of Sloped Samples in L-PBF Process
Author(s) Nismath Valiyakath Vadakkan Habeeb, Santosh Rauniyar, Kevin Chou
On-Site Speaker (Planned) Nismath Valiyakath Vadakkan Habeeb
Abstract Scope Laser Powder Bed Fusion (L-PBF) is utilized in various industries, but its full potential is hindered by inconsistent quality of the built parts. For features with inclined surfaces, surface finishes are particularly poor, as one of the most unfavorable defects for load-bearing surfaces of L-PBF components. The surface roughness is strongly affected by the contouring parameters. This study proposes a multi-layer, multi-physics simulation framework to understand the factors exacerbating the inclined surface finishes. Simulation results indicate that porosities formed due to insufficient melting in low-energy contouring scans increase the surface roughness for up-skin regions. While the visualization of the attached particles remains challenging for the down-skin surface, the simulation results show a lower and abnormal thermal gradient at the melt boundary due to the poorly supported melt region. The simulated trend was compared through a comprehensive Design of Experiment, and the simulation results qualitatively agree well with the experimental data.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

3-Dimensional Microstructure Characterization of Laser Powder Bed Fusion IN625 and IN718
3D Deep Learning for Porosity Analysis in Additive Manufacturing
A-1: 3D Printed Ceramics for Solid-state Battery Components
A-22: Enhancing Material Properties in Multi-Material 3D Printing: Exploring In-Situ Mixing and Material Gradation
A-23: Mechanical Ventilator Prototype Using 3D Printed Components
A-2: Deep Learning Assisted Material Structure Property Linkage of 3D Printed AlSi10Mg Alloy
A-3: Density Functional Theory Based Methods for Predicting Interfacial Strengths in Thermal Barrier Coatings with MXene Using Spark Plasma Sintering
A-4: Developing Virtual Reality Models to Simulate Additive Manufacturing Process
A-5: Extrusion Based 3D Printing of Silicon Carbide
A-6: Inkjet 3D Printing of Biodegradable Materials
A-7: Modeling Laser Heating Phenomenon in Refractory Metal Powder Bed Fusion Process
A-8: Simulation of Shell Thickness and Inclusions Trajectory in Casting Mold of Round Steel Billet Continuous Casting
A Molecular Dynamics Study on the Micro Cold Spray of Zinc Oxide Films
A Unified Treatment of Alloy Dependent Material Properties and Process Parameters for Accurate Solidification Simulations for AM Based on CALPHAD
Analyzing and Predicting Surface Roughness in Laser Powder Bend Fusion
Better Understanding of Cracking Phenomena in High-Strength Superalloys through Multiphysics Modeling in Additive Manufacturing
Computational and Experimental Study of Up-/Down-surface Characteristics of Sloped Samples in L-PBF Process
Effect of Size, Location, and Aspect Ratio of Pores on Ductility of PBF-LB Ti-6Al-4V: Experiments and Simulations
Examining the Effect of an Oxide Layer on the Deposition of Tantalum Films via Micro-Cold Spray
Finite Element Simulation Based on Constitutive Model of Cellular-structured Metals Produced by Additive Manufacturing
Gas Atomization of Mg-Zn-Ca-Mn Alloy Powder for Additive Manufacturing
Mechanical Properties of Truss-based Nanolattices: A Molecular Dynamics Study
Microstructure Evolution Simulation of Inconel 718 Superalloy during Laser Powder Bed Fusion (LPBF) Process
Modeling In-Situ Phase Transformation in Inconel 718 and EH36: A Study Using Phase Field and Phase Fraction Models
Multi-Model Monte Carlo Simulations of Mechanical Behavior of Additively Manufactured Metals
Open-source Numerical Simulations of Melt Pool Physics in Laser Powder Bed Fusion Processes
Physics-constrained, Inverse Design of High-temperature Strength Printable Aluminum Alloys with Low Cost and CO2 Emissions for High Demand Industries
Physics Informed Reduced Order Model for Directed Energy Deposition Simulations in MALAMUTE
Predicting Material Properties in Additive Manufacturing Using Acoustic Signatures and Machine Learning
Quantification of Carbide Pickup and Quality Control of SS 316L Manufactured via Binder Jet Printing
Quantification of Spatter Counts and Trajectories in Laser Powder Bed Fusion using Machine Learning Analysis of High Speed Imaging
Simulating the 3D Printing Process of Hydroxyapatite Powders
Simulation of Anisotropic Mechanical Behavior of Additively Manufactured Ti-6Al-4V Wall Structures using VPSC
The Effect of Disorder and Constitutive Material on the Mechanical Properties of Bioinspired Honeycombs
Use of Machine Learning to Identify Process-Structure-Property Relationships in PBF-LB AlSi10Mg
Utilizing Cellular Automata to Resolve Process Parameter to Microstructure Correlations in LPBF Additively Manufactured Parts

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