## 3 Results
### Fatigue Properties  
According to the literature (Figure 7), HCF fatigue research published a maximum of 26 papers in the preceding year. Low cycle fatigue research has also improved compared to the previous years, a maximum of 6 papers were published. Some investigations with both HCF and LCF also demonstrate the depth of research in ortho implants. Therefore, conclusions based on the findings of the relevant literature suggest that HCF is the most significant research in industrial 4.0 [65]. A high degree of reliability and a large number of loading cycles make it important to comprehend and analyze the fatigue behavior of different materials in distinct fatigue regimes. This is exacerbated by the fact that 90% of component failure incidents in engineering applications are fatigue-related. For fatigue assessments, accelerated fatigue test techniques based on the premise of enhanced severity and decreased test duration have been widely utilized [66]. To find out how different SLM build orientations affect the fatigue properties of Ti6 Al4V alloys, samples of in-situ fatigue and Rotating Bending Fatigue (RBF) bars were made using SLM methods with building orientations of 0\({}^{\circ}\), 45\({}^{\circ}\), and 90\({}^{\circ}\), as shown in Figure 8. The S-N diagrams produced for each structure at various relative densities are depicted in Figure 8. It should be emphasized while evaluating the findings, that relative densities employed in the simulation are not identical to experimental densities. Considering this, there is a high level of concordance between simulation and experiment findings. In accordance with experimental findings, the predicted fatigue life of scaffolds reduced dramatically as the degree of stress increased. Similar to typical solid materials, the S-N curves derived by numerical simulations and their experimental counterparts were linear on a logarithmic scale, as depicted in Figure 9.  
[PERSON]'s model for crack closing was utilized to correlate \(\Delta\)K rate data from various stress ratios (i.e., R = 0.1 and 0.7). Figure 10 depicts the large-crack findings and the effective stress intensity factor for LPBF Inconel 718. These data are compressed into a narrow band with a restriction factor of \(\alpha\) = 2.2 in the mid-rate regime. In the high-rate regime, some discrepancies are found between these two stress ratios, but these variances are predicted since the \(\Delta\)K value at fracture is a function of R as the crack in the specimen expands toward failure. Figure 7: Fatigue Properties. The FASTRAN model accounts for these discrepancies using the two-parameter fraction criteria. The plasticity-induced closure approach under constant amplitude load capacity does not collapse the large-crack growth threshold data onto a unique effective stress intensity factor rate relation in the threshold regime when loading reduction methods are employed and the initial crack growth rate at the start of load reduction is excessively high [68]. This behavior is likely due to the relevance of fracture closure processes other than plasticity-induced closure during cyclic loading with load decrease. As a result, the high-stress (R = 0.7) data were used cautiously to assess the effective stress intensity factor rate in this regime. In the threshold regime, it was discovered that the real effective stress intensity factor data would lie at lower levels than those calculated using large-crack data. Based on the size of the flaw, the crack closure model and baseline effective stress intensity factor rate curve were used to estimate how the crack would grow from the size of the flaw when it first appeared until its failure. The defect size is a significant geometrical characteristic that might influence fatigue life. Several investigations have found a reduced fatigue life for AM specimens with larger voids under the same testing conditions. Consequently, it is essential to investigate the variance in fatigue life of AM specimens based on void size [69].