Mechanical strength of polylactic acid (PLA) is increasingly relevant with time because of its attractive mechanical properties and 3D printability. Additive manufacturing (AM) methods, such as fused deposition modeling (FDM), stereolithography (SLA), and selective laser sintering (SLS), serve a vital role in assisting designers with cheap and efficient generation of the desired components. This document presents research to investigate the anisotropic response of multi-oriented PLA subjected to multiple monotonic loading conditions. Although empirical data has previously been captured for multi-oriented PLA under tensile and compressive loading conditions, the data has yet to be applied with regard to a representative component geometry. The tensile and compressive empirical data were ultimately used to develop elastic and yield constitutive models which aided in the characterization of PLA under torsion and bending. This representative component geometry is expected to experience a combined torsion and bending load condition in an effort to address this integral gap in the mechanical properties of multi-oriented PLA. In addition to the acquired empirical data, finite element analysis (FEA) and analytical modeling are employed to supplement the accurate modeling of future component analysis. As a result of the proposed array of experiments, the torsional and bending capabilities of PLA are forecasted to vary based on the print orientation. Lastly, the broader impact of this work is dedicated to addressing the material's capability to operate in environments which possess significant torsion and bending such as model aircraft wings and shafts for remote controlled cars.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:honorstheses-1493 |
| Date | 01 January 2019 |
| Creators | Santomauro, Aaron T |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Honors Undergraduate Theses |
Page generated in 0.0025 seconds