## 3 Results
### Numerical Simulation Validation with Experimental Results
As shown in Figure 29b, the experimentally determined elastic modulus of the specimens is relatively similar to the value expected by FE calculations based on CAD models. Most likely, the differences between the experimental and FE results are due to flaws in the geometry of the specimens, such as strut oversizing due to the way they were made, strut cross-section variation along the strut-axis, and strut dislocation. Comparing experimental and numerical findings Figure 30. Consequently, owing to the negative value of the stress exponent (b), the fatigue life reduced as the cyclic load increased. In contrast to the actual findings, all computational models predicted a longer lifespan for the lattice abutment. In comparison to the actual findings, the Soderberg model produced the most accurate forecast of fatigue life among the three techniques of mean stress correction. Although the majority of experimental data received from fatigue testing of metals fall between the Goodman and Gerber curves, the adoption of the Soderberg adjustment as the most accurate correction does not necessarily contradict the aforementioned tendency. As the most accurate adjustment, the Soderberg correction does not necessarily contradict the stated trend. It must be mentioned that the bulk of experimental fatigue testing is performed in a laboratory. Multiple investigations have shown that the presence of stress raisers may significantly reduce the fatigue characteristics of a component. This impact will be considerably more evident in EBM-produced lattice structures. EBM-manufactured products have a greater amount of surface roughness as one of their distinguishing qualities [87]. Low-thickness struts are the weakest connections in the porous structure and are susceptible to significant plastic deformation. A tight match between experimental data and numerical findings of a more cautious Soderberg adjustment reveals the effects of the aforementioned parameters on fatigue life. When designing a component based on its yield strength, the Soderberg relationship is applied. It indicates that, under cyclic stresses, the specified lattice structure seldom undergoes plastic deformation. Under torsion and multiaxial stresses (Figure 31), horizontal specimens have more fatigue strength at 2 million cycles (run-out limit) than vertical specimens, however, under uniaxial loads, vertical orientation demonstrates greater fatigue strength than horizontal orientation. There is a significant difference between the projected outcomes and the actual data, as seen in Figure 32. Moreover, just one set of data falls inside the 1.5 error zone. The predicted outcomes exhibit significant dispersion. An ML framework based on sensitive features and CDM is suggested to forecast the fatigue life of L-PBF-built AISi10 Mg samples to achieve high-precision and high-reliability fatigue life prediction of AM components. The extraction of sensitive features reduces the effect of feature causality on the prediction  
Figure 30: The results of the load-lifetime plotted for the four levels of cyclic loads. Reprinted with permission from ref. [86]. 2021, Elsevier. performance of the ML model. Also, the CDM-based life is used as physical information to describe how AM components break down under different levels of stress.