# Advances in Machine Learning Techniques Used in Fatigue Life Prediction of Welded Structures
## 3 Results and Discussion
Using a reliable assessment of strain history and critical plane orientation, the FL of a substructure may be forecasted at any site, while estimating the fatigue lifetime at various spots in a bracket and weld also needs more effort. These crucial sites will be used to map the bracket's and the weld's hot spots or essential stresses [109]. The results demonstrated that the constructed surrogate response surface model can accurately forecast the local equivalent stress amplitudes by utilizing RSM and NSGA-II to optimize fatigue structural parameters. However, the deck thickness is the most significant factor affecting the fatigue functioning of the U-rib weld alongside the U-rib to diaphragm weld [120]. The use of GPR can cut the cost of solving the PFCG forecast by 1875 times on average [123]. Equally, a way that aids in reducing the quantity of experiments and the expense of carrying out destructive tests with the necessary dependability is the methodology for fatigue evaluation based on UT results which has a very high accuracy when compared to experimental results as depicted in Figure 14 [69]. In a stochastic evaluation of stainless steel joined components subjected to mixed mode loading, the median rank treatment and the three-parameter Weibull approximations provided the closest approach to the measured values. Hence, under various loading situations, the fatigue strengths, limitations, lifetimes, and failure probability became predictable [34]. Also, for the Base Metal (BM) cracks in fatigue cracks, the most-likely (median) FL from the probabilistic analysis is nearly comparable to the FL from deterministic calculations [55]. Through the three-dimensional finite element method, the RSW specimens in tensile-shear were examined to know their fatigue propagation life. On this account, the experimental data and the cross-sectional pictures of the coupons were in excellent agreement with the FE results and anticipated fatigue fracture trajectory [60]. Meanwhile, the analysis's findings from an ANN set-up to predict C45 forging tool durability is crucial to the operation of the forging system because they help the technologist choose process parameter figures that will prolong the die's lifetime [79]. Contrarily, it was found that the supplemental ice loading on welded plate joints can reduce the FL by half, compared to that under wave loadings only [80]. Moreover, the use of a comprehensive database of damaged and healthy fatigue damage indices for training ANNs showed that the damage identification method can efficiently detect potential fatigue cracks in welded steel bridge structural components [81]. According to the findings, fatigue dependability indices drastically decline as service life lengthens as illustrated in Figure 15a,b [91]. Figure 14: Comparison of the predicted fatigue life of the spot-welded joints with actual values. Utilizing records from SHM, an incremental two-scale model of damage can be updated with new model parameters over time utilizing Bayesian updating of damage variables as well as sensitivity analysis of damage evaluation to material variables [94]. Findings revealed that the susceptible joints to fatigue failure are the butt-welded longitudinal rib joints, the diaphragm of rib-to-diaphrag joints, and the deck plate of RD joints in OSDs. It also became clear that it was impossible to disregard the significant role that the root-to-deck (RTD) and toe-to-deck (TTD) cracking models both play in the fatigue failure of OSDs. More importantly, when mixed failure models were considered, a striking decline in the fatigue dependability of RD joints can be shown. Moreover, the U-rib butt junction and the RD joint are most and least susceptible to fatigue failure, respectively, among the three essential welded joints in a coastal thin bridge [99; 106; 121]. On another note, experimental findings demonstrated that the Support Vector Machine (SVM) prototype has a greater anti-noise capability and higher forecast in aluminum welded connections after fatigue [113].