PSI - Issue 68

Soran Hassanifard et al. / Procedia Structural Integrity 68 (2025) 77–83 S. Hassanifard and K. Behdinan / Structural Integrity Procedia 00 (2025) 000–000

80 4

When the value of fatigue strength reduction factor is known, the required parameters for fatigue life predictions can be obtained by solving Eqs. 4 and 5 at each load level. 2.3. Proposed model The proposed novel technique is based on the observation that the fatigue life of 3D-printed samples at all raster angles is significantly lower than that of the raw filament materials. Since the raw filament material is homogeneous and isotropic, the 3D-printed samples can be treated as specimens with similar behavior to the filaments but containing an imaginary notch, characterized by specific notch strength reduction factors ( " ! ). The notch strength reduction factor values have been calculated for samples with 0º and 90º raster orientations, as shown in Fig. 1.

!" !# !$ %% %& D" D# D$

!" !# !A BB B& D" D# DA !" !# !$ %% %& D" D# D$

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"=!>.?64/.P9+<),2@M5 DABCN+@M.P".a2bN22.N)/M2N5 DABCN+@M.Pc".a2bN22.N)/M2N5

P)5

P75

()G+,-,./MN2//.P(4)5

()*+,-,./MN2//.P(4)5

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6-,72N.89.:;:<2/.M8.9)+<-N2

S-,72N.89.:;:<2/.M8.9)+<-N2

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"=>?.@64/.P9+<),2AM5 DBCaN+AM.P".b2cN22.N)/M2N5 DBCaN+AM.Pd".b2cN22.N)/M2N5

!=.>64/.P9+<),2?M5 D@ABN+?M.P".C2aN22.N)/M2N5 D@ABN+?M.Pb".C2aN22.N)/M2N5

PC5

P:5

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6-,72N.89.:;:<2/.M8.9)+<-N2

6-,72N.89.:;:<2/.M8.9)+<-N2

Fig. 1. Fatigue test data of raw filament materials and 3D-printed samples to obtain " ! values. The calculated " ! values, defined as the ratio of the strength of the raw filament material to the strength of the 3D printed sample at various load levels, are summarized in Table 2. If the values from Table 2 are plotted against the normalized applied stress ( ⁄ ) for all samples at both raster angles, it seems that the data can be accurately represented by the equation " ! = ( ) ( ⁄ , demonstrating a high level of precision. Therefore, notch strength reduction factor values for other raster orientations can be estimated through a linear interpolation between the data obtained for 0º and 90º raster orientations. For example, the relation " ! = 1.46( ) 47.,, ⁄ can be applied with a high degree of precision for samples with a 45º raster orientation.