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- Welding simulation (5) (entfernen)
Analytical and numerical methods are used to estimate the temperature field due to the heat effects of welding. Numerical techniques are more adapted for industrial complex applications where analytical solutions do not exist yet. However, computational time is much lower with analytical models and a combination of both methods is investigated. Therefore, the two approaches are introduced and confronted in this paper. The finite-element software Ansys has been used for numerical simulations and Scilab for analytical simulations. In order to get a similar result quality, both methods have to be analysed and compared with respect to boundary conditions. These configurations are presented in this paper. Before starting any analysis, the analytical and numerical models have to be comparable. For the numerical simulation, every in- or output is given in discrete form and, for the analytical simulation, in continuous form. Thus, an analysis of the energy input distribution in both models is compulsory to ensure that the same amount of energy is applied. After this first study, a comparison of the analytical and numerical temperature field simulation is done from a fix point source in an infinite volume in steady state to a moving point source in a finite dimension in a transient state. A good agreement between the analytical and the numerical simulation results is found. However, some techniques, like a consideration of an image heat source for the analytical model or the selection of boundary conditions for the numerical model, need to be taken into consideration when the degree of complexity of the study (finite dimension or cooling time) increases. The limit of the comparison is reached when the geometry becomes too complex and when the effect of variable thermal properties with temperature cannot be neglected.
In a previously published model, gas metal arc welding of 1 mm thick DP600 overlap joints is validated for the transient temperature distribution, the welding distortion and longitudinal residual stresses. Tensile tests have been simulated and performed experimentally. Validations were performed for two clamping cases: an immediate release of the clamps after welding and a release of the clamps after cooling to room temperature. There is good agreement between experiments and simulations. It has been found that the temperature distribution, longitudinal stresses and welding distortions are dependent on the clamping conditions. To explain the effect of the clamping time, a bar model is proposed. It is shown that longer clamping times increase plastic deformation and hence reduce residual stresses and buckling distortion. Additionally for an overlap joint, it has been found that the longitudinal residual stresses are affected significantly by the sample's geometry.
Continuous cooling transformation (CCT) behavior affects the transient state of
material properties employed in a numerical welding simulation, having a direct influence
on the developing stress state. Three different CCT diagrams for S355J2 steel
were employed to understand the influence of variations in CCT behavior on the numerical
calculation of welding-induced residual stresses. The CCT diagrams were
constructed from transformation data contained in the Sysweld software database,
measured dilatometric data from Gleeble experiments, and transformation data calculated
from the JMatPro software. The calculated transverse and longitudinal residual
stress distributions provided a qualitative correction only in comparison to experimental
measurements, with the largest deviation occurring near the weld
interface. Overall, the results indicate a weak dependency of the calculated residual
stresses due to anticipated CCT variations. The most significant effect on the calculated
residual stresses was shown to be related to the proportion of formed martensite.
It is suggested that CCT data of approximate accuracy is sufficient for reliable
calculation of welding-induced residual stresses.