Adan Vega

Effect of low transformation temperature weld filler metal on welding residual stress

Abstract The effect of weld filler metal austenite to acicular ferrite transformation temperature on the residual stresses that arise during the gas metal arc welding of a low carbon steel has been examined using a finite element model. It was found that the stress levels in the weld can be tailored by the appropriate selection of the filler metal and compressive, near zero or tensile residual stresses produced. Reasonable agreement was obtained between the model and the stresses measured using neutron diffraction both in welds using conventional and low transformation temperature filler metal.

Reenactment of a bollard pull test for a double propeller tugboat using computational fluid dynamics

Use of CFD simulations is an affordable and trustworthy way of determining a vessel’s capacity before its construction. This study focuses in simulating a bollard pull of a specific tugboat and comparing the results with those of the real test to which it was subjected after construction. In compliance with the regulations of the classification societies regarding these types of tests, simulations will be carried out to study the bollard pull tests of a double propeller two boat. The results showed that the mathematical model is suitable for a numerical calculation of the bollard pull tests.

Development of a neural network model to predict distortion during the metal forming process by line heating

In order to achieve automation of the plate forming process by line heating, it is necessary to know in advance the deformation to be obtained under specific heating conditions. Currently, different methods exist to predict deformation, but these are limited to specific applications and most of them depend on the computational capacity so that only simple structures can be analyzed. In this paper, a neural network model that can accurately predict distortions produced during the plate forming process by line heating, for a wide range of initial conditions including large structures, is presented. Results were compared with data existing in the literature showing excellent performance. Excellent results were obtained for those cases out of the range of the training data.