PSI - Issue 34

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Harry O. Psihoyos et al. / Procedia Structural Integrity 34 (2021) 253–258 Harry O.Psihoyos et al. / Structural Integrity Procedia 00 (2021) 000 – 000

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Table 1: Process parameters of Group 4 of SLM Ti-6Al-4V fatigue specimens (Du et al. ,2021) Process Parameters Laser power (P) 160 W Layer thickness (t) 30 μ m Scan speed (v) 1000 mm/s Hatch spacing (h) 0.13 mm

Monotonic tensile tests for the nine groups of specimens were conducted to determine their tensile properties and ultrasonic fatigue tests were performed at room temperature for stress ratio R of -1. The fatigue specimens had hourglass shape with tota l length of 51.30 mm, gage length of 32.64 mm, varied diameter within the gage length with nominalminimal diameter of 3.5mm in the middle andedge diameter of 14 mm. 3. Modellingprocedures The present modelling framework consists of two parts. In the first part, the susceptible areas for defect formation in the examined SLM Ti-6Al-4V fatigue specimen are predicted. The prediction of these areas is based on the processing of the therma l history simula tion results of SLM specimen. After the defect characteriza tion of the SLM specimen, the location of the most critica l defect from which crack will initiate and propagate is determined. The ma in assumption in the present fatigue life estimation model is that the fa ilure of the part will initia te and propagate from only one defect. Thus, the most critica l defect has to be considered in the model from which crack will propagate until the fina l fa ilure. In the second part, based on the location of the critica l defect on the perpendicular to loadingdirectioncross-sectionof theSLM part, thestress intensity factor for fatigue life prediction is selected. 3.1. Predictionof defects or susceptibleareas for defect formation in the SLMTi-6Al-4V specimen The prediction of defects or to be better expressed, the susceptible areas for defect formation in the SLM Ti-6Al 4V fatigue specimen was performed by process therma l history simulation in ANSYS 2020R2 Additive Suite. The ma in outputs of thermal history simula tion in ANSYS Additive Suite are the melt pool characteristics (depth, width, length) and the temperatures of the imported part in a layer-by-layermanner. The ma in indicator of defect formation in a location are the melt pool characteristics. If the melt pool characteristics in a location do not fulfill certa in criteria , this location is susceptible for defect formation. These well-known criteria have been developed in the literature and they can serve to ensure the qua lity of melt pool and of the part in whole. The current criteria concerns the ma in defects that canbe generatedduring the SLM process, which are the lack-of-fusionandkeyhole defects. The criterion for lack-of-fusion porosity used in this work was developed by Tang et a l. (2017). As the fundamenta l origin of lack-of-fusion porosity is the insufficient overlap of successive melt pools, the melt pool overlap can be ca lculated to predict lack-of-fusion defect. The process parameters used in this criterion are the hatch spacing (h) and layer thickness (t) . The lack-of-fusioncriterion is expresses as:

2

2

h t W D   +           

(1)

1

where D and is the tota l melt pool depth and W the melt pool width. Although, the assumption of dua l ha lf - ellipse of shape of the melt pool, this criterion can be applied in melt pool of any shape. Keyhole defect formation has been identified usingdepth-to-width ra tio (melt pool cross-sectional aspect ra tio) by the criterion:

D W

0.5

(2)

