PSI - Issue 7

Yoichi Yamashita et al. / Procedia Structural Integrity 7 (2017) 11–18 Yoichi Yamashita et Al./ Structural Integrity Procedia 00 (2017) 000–000

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the values σ / σ w close to 0.8 around N f = 10 6 . At present, the reason is not clear. Although the Vickers hardness of Material B is almost the same as Material A, the fatigue strength is lower than Material A. The same trend was observed for additively manufactured Ti-6Al-4V with larger particle (Masuo, H. et al. 2017). These results suggest that more precise estimation of the effective size √ area eff is necessary for the complex configuration of multi-defects as shown in Fig. 9. The values of σ / σ w for A1, B1, B2, and C1 in Fig. 4 and a 1 and b 1 in Fig.6 which ran out are confirmed lower than 1.0 by calculation with the defect sizes obtained by the subsequent tests at higher stress. For example, the values of σ / σ w for the specimens of Material A which ran out longer than N =10 7 were summarized as follows. ① Applied stress σ = 300MPa, N = 2×10 7 , √ area =179 µ m. σ w =352MPa. σ/σ w ＝ 0.85. ② Applied stress σ = 365MPa, N = 10 7 , √ area =19 µ m. σ w =512MPa. σ/σ w ＝ 0.71. ③ Applied stress σ = 350MPa, N = 10 7 , √ area =74 µ m. σ w =408MPa. σ/σ w ＝ 0.86. Thus, it is confirmed that these previous tests were carried out below the fatigue limit of each specimen. Since the fatigue limit of AM specimens is influenced by the size of defects contained in individual specimens, we must understand that we cannot define a constant fatigue limit for a material in question from the usual S - N data. Figure 11 shows the statistics of extreme analysis of the largest defects which appeared on the sections cut from the raw plate materials within the area S 0 = 80.97mm 2 for Material A and S 0 = 116.49mm 2 for Material B. Regarding linear defects, the length of linear defect was also plotted in addition to the √area, because the effective value of √area must be estimated by using the length of defect based on the concept explained in Figs. 8 and 9. Although these analyses are based on 2D measurement, the statistics of extremes analysis such as Fig. 11 will be useful to improve the quality of AM processes. From the viewpoint of the quality control of AM materials based on defect size, A is graded higher than B.

8.0

8.0

7.0

7.0

6.0

6.0

Pore

0.0 Reduced variate ｙ j （ % ） 1.0 2.0 3.0 4.0 5.0

0.0 Reduced variate ｙ j （ % ） 1.0 2.0 3.0 4.0 5.0

Pore

Elliptical defect

Elliptical defect

Linear defect ℓ

Linear Defect ℓ

-1.0

-1.0

S 0 = 80.97mm 2

S 0 = 116.49mm 2

-2.0

-2.0

0

20

40

60

80

100

0

50

100

150

200

√area max （μ m ） or ℓ

√area max （μ m ） or ℓ

(a) Material A

(b) Material B Fig.11 Statistics of extremes of the defects of the raw plate materials.

Figure 12 shows the statistics of extremes analysis of the defects which were observed at fatigue fracture origins. In this analysis, the modification of √area was applied based on the rule of Figs. 8 and 9 and the √ area effmax was estimated. From the above discussion, it is necessary for the fatigue design of AM components to consider the method of the statistics of extremes based on not only Fig. 11 (even with the 3D measurement) but also the concept of Fig.12 (Figs. 8& 9). Considering the volume and number of productions of the components in question, the effective largest defect √ area effmax contained in large or many components can be predicted. The lower bound of the fatigue limit σ wl based on √ area effmax can be determined by the following equation.

σ wl = 1.43( HV +120)/( √ area effmax ） 1/6

(3)