The main target of the current study is the assessment of API 5L X52 pipe line containing lack of penetration and undercut welding defects and to study the influence of the defect length and depth on the failure pressure of the pipeline. The failure pressure is calculated by using Finite element software ANSYS ver19. The results from finite element analysis are used to train an artificial neural network for easily predicting the failure pressure with a wide range of defect depths and lengths. Also the results obtained were also used in the regression analysis to find equations linking the maximum pressure to the defects dimensions. The results revealed a Good agreement between finite element modeling and the experimental tests, theoretical values and available design codes with maximum average error of (13.4%). The failure pressure varied significantly as a function of the defect length and depth.

In this paper friction stir welding process has been studied whereby utilized FEM method (Ansys software ver. 20). The main effective parameter in this process were rotational speed, linear speed, tool shoulder radius, heat transfer coefficient and clamping percentage to study their influence on represent temperature, von misses stress and frictional stress distribution. Because of the difficulty to obtained the number of the simulation cases in order to get the most important results, Taguchi L27 orthogonal array was apply to reduce the total number of the simulation cases. Pure copper (t = 3.18 mm) material type was applied as work plate material. ANOVA statistical tool was utilized to achieved the optimization process after the simulation cases done. Percentage of contribution of each parameter can be obtained by ANOVA table and mean of S/N ratio plot. Validation process was achieved between the Current study and experiment work in the temperature distribution field with percentage of error 2.7 %. From optimization result It is found that the optimum condition in order to obtained good results for temperature was rotational speed of (450 rpm), linear speed (2.75 mm/s), tool shoulder radius (7 mm), heat transfer coefficient (300 w/m2 K), clamping distance percentage (40 %). And for von misses stress was rotational speed of (550 rpm), linear speed (3 mm/s), tool shoulder radius (7 mm), heat transfer coefficient (300 w/m2 K), clamping distance percentage (20 %). While for frictional stress was rotational speed of (450 rpm), linear speed (2.5 mm/s), tool shoulder radius (7 mm), heat transfer coefficient (300 w/m2 K), clamping distance percentage (30 %).

The present work aims to build mathematical models based on experimental data to estimate the mechanical properties of submerged arc weldment. AISI 1020 low carbon steel plates 16mm thickness were welded according to orthogonal array in order to establish the relationship between input parameters (welding current, Arc voltage and welding speed) and output parameters (ultimate tensile stress, yield stress, impact energy and hardness) by submerged arc welding (SAW) process. The relationship between input and output parameters for the welding process are conducted using two suitable mathematical models the first one based on regression analysis, while the second one based on multi input single output ANFIS model for estimation of some mechanical properties of the welded plates. It was found that ANFIS results are closer to the experimental results than regression results. The optimal parameters (which give a maximum value of ultimate tensile strength (UTS), yield stress and impact energy; 446 MPa, 318 MPa and 213 J) are welding current is (380 Amp), Arc voltage is (25 V) and welding speed is (40 cm/min), while the maximum value of hardness number is (228 HV), when current welding is (380 Amp), Arc voltage is (25 V) and welding speed is (25 cm/min).