Investigation of Stress Concentrations in Fused Deposition Modeled Parts
Faculty Mentor Name
David Lanning
Format Preference
Poster
Abstract
Rapid prototyping using additive manufacturing has an ever-increasing presence in industry. Fused Deposition Modeling (FDM) is a common type of additive manufacturing and has experienced significant growth in recent years. There are many process parameters that affect the quality and mechanical properties of FDM parts, which makes it a highly desirable manufacturing process but also creates a barrier due to the lack of knowledge of their effects. There exists a large gap in knowledge about how specimen geometry coupled with infill parameters affects mechanical properties, which this study aims to address. To investigate these effects, infill pattern is constrained to a ‘gyroid’ pattern, and the infill density is varied at 20%, 40%, and 60%. Previously, work was conducted to demonstrate how stress concentrations, in the form of notches and holes, affect the strength of FDM-printed specimens. These studies resulted in nonintuitive results that contradict traditional solid mechanic theories to predict failure and crack propagation. Specimen geometry is now constrained to stress inducing "v" notches and elliptical holes. The new geometry can be correlated to previously tested specimens with stress concentrations in the form of circular holes and semi-circle notches. While the theoretical stress concentration factor can be designed the same between a "v" and semi-circular notch, the stress field around the notch varies with a higher maximum stress at the "v" notch due to the sharp curve compared to the semi-circle. This leads to a higher probability of crack initiation and propagation than traditionally expected, which will be influential in creating failure theories for 3D-printed products. Initial results have lead to continued belief from prior work, in that the shell in 3D printed parts makes the edges solid. The added material reinforces the part at that location, which decreases the stress concentration factor.
Investigation of Stress Concentrations in Fused Deposition Modeled Parts
Rapid prototyping using additive manufacturing has an ever-increasing presence in industry. Fused Deposition Modeling (FDM) is a common type of additive manufacturing and has experienced significant growth in recent years. There are many process parameters that affect the quality and mechanical properties of FDM parts, which makes it a highly desirable manufacturing process but also creates a barrier due to the lack of knowledge of their effects. There exists a large gap in knowledge about how specimen geometry coupled with infill parameters affects mechanical properties, which this study aims to address. To investigate these effects, infill pattern is constrained to a ‘gyroid’ pattern, and the infill density is varied at 20%, 40%, and 60%. Previously, work was conducted to demonstrate how stress concentrations, in the form of notches and holes, affect the strength of FDM-printed specimens. These studies resulted in nonintuitive results that contradict traditional solid mechanic theories to predict failure and crack propagation. Specimen geometry is now constrained to stress inducing "v" notches and elliptical holes. The new geometry can be correlated to previously tested specimens with stress concentrations in the form of circular holes and semi-circle notches. While the theoretical stress concentration factor can be designed the same between a "v" and semi-circular notch, the stress field around the notch varies with a higher maximum stress at the "v" notch due to the sharp curve compared to the semi-circle. This leads to a higher probability of crack initiation and propagation than traditionally expected, which will be influential in creating failure theories for 3D-printed products. Initial results have lead to continued belief from prior work, in that the shell in 3D printed parts makes the edges solid. The added material reinforces the part at that location, which decreases the stress concentration factor.