Additive Manufacturing Fatigue and Fracture V: Processing-Structure-Property Investigations and Application to Qualification: Poster Session
Sponsored by: TMS Structural Materials Division, TMS: Additive Manufacturing Committee, TMS: Mechanical Behavior of Materials Committee
Program Organizers: Nik Hrabe, National Institute of Standards and Technology; John Lewandowski, Case Western Reserve University; Nima Shamsaei, Auburn University; Mohsen Seifi, ASTM International/Case Western Reserve University; Steve Daniewicz, University of Alabama
Tuesday 5:30 PM
March 16, 2021
Room: RM 2
Location: TMS2021 Virtual
Session Chair: Nik Hrabe, National Institute of Standards and Technology (NIST)
Effect of Laser Power, Laser Spot Size and Hatch Spacing on Mechanical and Microstructural Properties of 316L Stainless Steel Processed via Selective Laser Melting: Taban Larimian; Tushar Borkar1; Manigandan Kannan2; Dariusz Grzesiak3; Bandar AlMangour4; 1Cleveland State University; 2University of Akron; 3West Pomeranian University of Technology; 4Saudi Arabia Basic Industries Corporation
At the present time selective laser melting is among the most popular metal additive manufacturing processes. For this research work, selective laser melting was used to fabricate 18 blocks made of 316L stainless steel. Each block was fabricated under different processing parameters. The effect of processing parameters such as scanning speed, energy density, hatch spacing, laser spot size, etc. on microstructure and mechanical properties of these samples were studied. Scanning electron microscopy analysis was done on vertical and horizontal cross sections of each block to study the shape and size of melt pools under different building parameters. Additionally, microhardness and the microstructure of the samples were studied for vertical and horizontal cross sections individually for each of the samples. Moreover, ultimate tensile strength, yield strength, elongation and relative density of each sample was measured in order to investigate the role of each processing parameter on each of the mechanical properties.
Effect of Thickness on Ultrasonic Fatigue Behavior of 316L Stainless Steel Made by Powder Bed Fusion Additive Manufacturing: Megan Trombley1; Qianying Shi1; John Allison1; 1University of Michigan
In additive manufacturing (AM) of metallic materials, porosity is an inherent feature which can result in critical defects that impact fatigue behavior. This study explores the effect of AM sample thickness (diameter) on the ultrasonic fatigue behavior of 316L stainless steel. Cylindrical dog-bone specimens of 1.5mm, 2.5mm, and 5.0mm gauge were manufactured by Naval Research Laboratory using a Concept Laser M2 AM machine. The use of ultrasonic fatigue allows for the gathering of larger datasets than feasible using a traditional fatigue testing apparatus. These large datasets enable improvements in statistical treatments in determination of manufacturing process effects such as thickness on fatigue performance of these AM samples. This presentation will review findings on the influence of sample thickness on fatigue behavior including fatigue strength and nature and size of defects present at the site of fatigue crack initiation.
Quantifying Surface Roughness in Additive Manufactured Ti-6AI-4V Using In-situ X-ray Imaging: Alisha Bhatt1; Chu Lun Alex Leung1; Gowtham Soundarapandivan2; Sebastian Marussi1; Saurabh Shah1; Robert Atwood3; Manish Tiwari1; Peter Lee1; 1University College of London; 2TWI Ltd; 3Diamond Light Source Ltd
Smart implants are devices with therapeutic and diagnostic capabilities which employ nanosensors that are small, robust, and easy to integrate into the body. This project aims to imbed these nanosensors directly onto additive manufactured (AM) titanium biomedical implants. The surface finish of the AM component will have a significant effect on the adhesion of the sensors to the substrate, an optimum surface profile is required. Here, we designed a series of experiments to analyse the correlations between powder oxygen level, process parameters, and the resultant surface roughness of additive manufactured Ti-6AI-4V parts via high-speed synchrotron radiography. Results revealed positive skewness and kurtosis in roughness with an increase in layers, while the Ra (arithmetical mean) decreases with an increase in heat input, indicating a rougher profile with lower energy density. The work reveals how the roughness profile varies as a function of processing conditions, highlighting key trends for parameter optimization.
Ultrasonic Nondestructive Characterization of Hybrid Additively Manufactured 420 Stainless Steel: Luz Sotelo1; Cody Pratt1; Haitham Hadidi1; Michael Sealy1; Joseph Turner1; 1University of Nebraska Lincoln
Hybrid additive manufacturing (AM) processes enable the creation of functionally graded components for which the variation in material properties is achieved through the synergized combination of manufacturing processes and/or energy sources. To date, examples of nondestructive evaluation (NDE) in hybrid AM are limited, and their sensitivity to these functional gradients is currently unclear. Here, 420 stainless steel samples are considered. A comparison is made between a sample manufactured using a hybrid AM process that incorporated directed energy deposition (DED) and laser peening with a sample created by DED alone and a wrought sample. The hardness profile and ultrasonic phase velocity, attenuation, and diffuse backscatter responses were measured across the axial (build) direction of the samples. Laser, optical and SEM micrographs were obtained for qualitative verification. The results show excellent agreement between destructive and nondestructive measurements, highlighting the potential of ultrasonic methods for the efficient characterization of hybrid AM components.
Variation and Impact of Surface Roughness on Fatigue in Laser Powder Bed Fusion: Rachel Tullis1; Joy Gockel1; Luke Sheridan1; 1Wright State University
Although any type of defect can weaken the performance of an additively manufactured part, rough surfaces with deep notches have been shown in prior studies to be a leading cause in decreasing the fatigue life. However, there is a lack of understanding of the surface roughness, the variability, and the appropriate metrics to sufficiently represent the impact of the surface on the mechanical performance. This work investigates the surface roughness of specimens fabricated with laser powder bed fusion through the calculation and comparison of surface measurement metrics. After these metrics are calculated, the variation within each sample and across different surfaces is determined. The calculated metrics and variations are related to the expected impact that the surface will have on the fatigue performance through fracture mechanics methods. Results from this research will provide guidance towards surface roughness metric and sampling specifications to ensure quality parts with consistent mechanical performance.