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Go to Editorial ManagerWelding residual stress has influences on fatigue, fracture, and corrosion. It is therefore important to explore the welding factors effect on the residual stresses. In this work, four welding factors (current, arc voltage, welding travel speed and included angle) were used to weld low carbon steel (ASTM A516 Grade 60).The experiments included welding of (60) pieces with dimensions of (300 x 150) mm and 10 mm thickness that were conducted based on the design matrix founded by using design of experiment (DOE) software (DESIGN EXPERT 10) with response surface methodology (RSM) technique. The X-Ray diffraction (XRD) method was used to measure the residual stress, which was then modeled and optimized in terms of the welding factors using (RSM) technique. The data showed that the welding travel speed and arc voltage have a significant influence on the residual stress. It was found that the optimum solution for minimum residual stress was at 450 Amp welding current, 34 volt arc voltage, 38 cpm welding speed, and 60? included angle. Where, the optimum value of residual stress was (-88.4 MPa). Finally, the predicted and experimental results of residual stress were in agreement with a maximum error of 1.8%.
Accurate measurement of residual stress is crucial for assessing structural integrity and predicting fatigue life. Although significant work has been documented on applying two-dimensional (2D) and three-dimensional (3D) digital image correlation (DIC) independently to the hole drilling process, a direct comparison of their accuracy and performance under the same conditions (most importantly, with plastic deformation) has not yet been published. This work conducted the first explicit comparison between 2D and 3D-DIC combined with the hole drilling method for residual stress measurement using finite element (FE) analysis as a validation standard. Residual stresses were induced through plastic bending of a square beam made of aluminum alloy 7075-T651. The findings indicate that the 3D-DIC is more accurate (93%) compared to the 2D-DIC (88%), objectively tested against FE solutions, even on a flat surface, which is theoretically ideal for 2D-DIC.This difference in accuracy is attributed to the higher sensitivity of the 2D-DIC to out-of-plane deformation and camera misalignment. These results support the effectiveness of 3D-DIC in measuring residual stress and explain that there is a trade-off between the practical accuracy of 2D and 3D versions of the hole-drilling technique.
Orthoses and prostheses were Chosen and laminated based on their high Yield, ultimate stresses, bending stresses, and fatigue limit. Response Surface Methodology (RSM) was utilized to find the best values for two parameters reinforcement perlon fiber and percent of Titanium Nanoparticle coupled with the matrix resin during optimization. The response surface methodology combined the expertise of mathematicians and statisticians to construct and analyze experimental models. Using this method, we identified 13 different lamination samples comprising a wide range of perlon number and Ti nano Wt% in their Perlon layer composition. All lamination materials defined by RSM methods and produced by a vacuum system were subjected to a battery of tests, with fatigue tests performed on the ideal laminating material in contrast to laminations created in the first study (Tensile test, Bending test, and Fatigue tests according to the ASTM D638 and D790 respectively). In comparison to the other 12 laminations tested using Design Expert version 10.0.2, the lamination with ten perlon layers and 0.75 percent Ti nano proved to be the strongest overall in terms of Yield, ultimate, and bending loads. This study used composite materials and titanium nanoparticles to characterize and fabricate ankle foot orthoses. Strength in bending should amount to about 70 MPa, around 85 MPa in tensile tension. Two empirical quadratic equations for the models of peak bending strength and maximum tensile stress with 95% confidence were created using the response surface approach and analysis of variance within the design of experiments software.