Theses and Dissertations at Montana State University (MSU)
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/733
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Item Predicting and modeling the material properties of fused deposition modeling elements leading to more efficient structural designs(Montana State University - Bozeman, College of Engineering, 2021) Murray, Flynn Rae; Chairperson, Graduate Committee: Michael BerryThe current construction industry has a significant negative impact on the climate, and this impact is expected to increase as the world's population continues to grow and urbanization expands. This impact may be reduced by implementing more sustainable building materials and practices. The primary objective of this research is to develop a methodology to estimate and model the material/structural response of elements made with fused deposition modeling. This will ultimately lead to an increased use of FDM in structural applications, and open the door to combining FDM with topology optimization to design and build optimized structural elements, resulting in a more sustainable infrastructure. In this research, tensile and flexural specimens printed in a variety of orientations were tested to evaluate/quantify the effects that print orientation have on elastic properties, ultimate stresses, and failure mechanisms of FDM parts. These elastic properties were then implemented into an orthotropic formulation of the Generalized Hooke's Law, and successfully used in finite element models to predict the elastic response of FDM specimens. Based on this analysis, it was determined that, while the Generalized Hooke's Law provided some advantages, the elastic material response of FDM parts could be estimated with a simpler isotropic model with little loss of accuracy. Response Surface Methodology (RSM) was then successfully used to further evaluate/quantify the effects that print orientation and scale have on the behavior of FDM parts, and to develop equations to predict the stiffness and strength of FDM parts given these print parameters. Finally, the feasibility of using topology optimization combined with additive manufacturing is briefly investigated.