Date of Graduation

5-2023

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Engineering (PhD)

Degree Level

Graduate

Department

Civil Engineering

Advisor/Mentor

Gary Prinz

Committee Member

Cameron Murray

Second Committee Member

Robert D. Moser

Third Committee Member

Micah Hale

Fourth Committee Member

Pedro Quintero

Keywords

Additive Manufacturing, Low-Cycle Fatigue, Micro-mechanical testing, Selective Laser Melting

Abstract

Selective laser melting is an additive manufacturing technology that opens the possibility to manufacture components with complex geometries that are difficult with traditional manufacturing techniques which could benefit engineering applications such as aviation or structural engineering. However, the lack of a reliable universal predictive model for selective laser melting components could impede the full implementation in industrial applications. Therefore, this dissertation investigates the mechanical behavior of selective laser melting 17-4 PH stainless steel under ultra-low cycle fatigue regime and propose a novel micro-mechanical based modeling using statistical and representative volume element. The first phase of this project examined the mechanical behavior of selective laser melting 17-4 PH stainless steel at macro-scale by tensile test and ultra-low cycle fatigue testing (Δ��/2 = 2%, 3% and 4%), and were compared to its wrought counterpart. Results showed that selective laser melting components underperform by 62% and 65%, compared to its wrought counterpart, when subjected to cyclic load with amplitudes of (Δ��/2 = 3% and 4%) respectively. Further examination in the fracture surface revealed the presence of voids within selective laser melting samples. This shows the detrimental effect that fabrication induced defects have over the fatigue life in selective laser melting. Also, Coffin-mason universal slope over predicts the performance of additively manufactured steel by 119% and 213% on strain amplitudes of 3% and 4%. Thus, a predictive model based on micro-mechanical testing is studied. The second part of this project describes a methodology to improve the micro-tensile sample fabrication throughput. This methodology consists in the pre-fabrication of micro-columns by photolithography and wet-etching. During wet-etching, excess of bulk material is removed, reducing the material re-deposition during the focused ion beam milling and easing the maneuverability of the grip by fabricating samples above bulk surface. Possible challenges during testing were commented on along recommendation on how to perform micro-tensile tests. Once the methodology was developed, selective laser melting 17-4 PH stainless steel was characterized via small scale mechanical testing such as nanoindentation, micro-compression and micro-tensile. An elastic modulus of 187.6 GPa was measured using nanoindendation with a Berkovich indenter. From the micro-compression, a yield stress of 759 MPa ± 207 MPa was measured. Also, a strain-hardening behavior was seen. An increase of 47% in the yield stress (1115 MPa) in micro-tensile test was seen, when compared to micro-compression. When micro- and macro- tensile test are compared, micro-tensile specimen shows an ultimate tensile strength of 1359 MPa, ~21% higher than the bulk specimen (1115 MPa). Also, the pronounced strain hardening behavior in macro-specimen was not shown during micro-specimen, suggesting different failure mechanisms. Lastly, this project proposes a framework for a predictive model based on micro-mechanical testing using statistical and representative volume elements. For this, a methodology was suggested, using representative volume element, to up-scale micro-mechanical properties. Then, using statistical volume elements, the effects of voids were studied. Although the model predicts mechanical behavior with low accuracy, suggestions as performing mechanical testing at the meso-scale and combining characterization techniques with micro-mechanical testing were done.

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