Filtern
Erscheinungsjahr
- 2011 (2) (entfernen)
Dokumenttyp
Sprache
- Englisch (2)
Referierte Publikation
- ja (2)
Schlagworte
- Simulating (2) (entfernen)
Welding is one of the most widely used joining processes in structural applications, like in car body production in the automotive industry. It is well-known that distortions and residual stresses occur during and after the welding process. Many procedures exist to decrease these negative heat effects of welding, but are often coupled with highly cost intensive experiments. For several decades, simulation models have been developed to understand and predict the heat effects of welding and to reduce experimental effort. In the production planning of various Original Equipment Manufacturers (OEM), some simulation tools are already well established, e.g. for crash test, forming or casting simulations. For welding, the demand is high but the implementation of welding simulation software is still not established yet. Welding is a complex process and the development of a flexible simulation tool, which produces good simulation results without expert knowledge in simulation, is not an easy task. In this paper, a welded assembly from the automotive industry has been simulated and compared to experimental data. Temperature fields and transient distortion distributions have been measured with thermocouples and with an optical 3D deformations analysis tool, respectively. The simulation has been run with a commercially available welding simulation software. The simulated temperature fields match the numerical ones perfectly. The simulated distortions are also qualitatively in best agreement with the experimental ones. Quantitatively, a difference of approximately 20 % between the simulated and the measured distortions is visible; this is acceptable considering the simplifications and assumptions of the simulation model. The global time to solution to get these results without expert knowledge in welding simulation was between 4 and 6 weeks, which is a reasonable time frame for an industrial application of welding simulation.
Fast temperature field generation for welding simulation and reduction of experimental effort
(2011)
The quality of welding processes is governed by the occurring induced distortions yielding an increase in production costs due to necessary reworking. Especially for more complex specimens, it is difficult to evaluate the optimal configuration of welding sequences in order to minimize the distortion. Even experienced welding operators can solve this task only by trial and error which is time and cost consuming. In modern engineering the application of welding simulation is already known to be able to analyse the heat effects of welding virtually. However, the welding process is governed by complex physical interactions. Thus, recent weld thermal models are based on many simplifications. The state of the art is to apply numerical methods in order to solve the transient heat conduction equation. Therefore, it is not possible to use the real process parameters as input for the mathematical model. The model parameters which allow calculating a temperature field that is in best agreement with the experiments cannot be defined directly but inversely by multiple simulations runs. In case of numerical simulation software based on finite discretization schemes this approach is very time consuming and requires expert users. The weld thermal model contains an initial weakness which has to be adapted by finding an optimal set of model parameters. This process of calibration is often done against few experiments. The range of model validity is limited. An extension can be obtained by performing a calibration against multiple experiments. The focus of the paper is to show a combined modelling technique which provides an efficient solution of the inverse heat conduction problem mentioned above. On the one hand the inverse problem is solved by application of fast weld thermal models which are closed form solutions of the heat conduction equation. In addition, a global optimization algorithm allows an automated calibration of the weld thermal model. This technique is able to provide a temperature field automatically that fits the experimental one with high accuracy within minutes on ordinary office computers. This fast paradigm permits confirming the application of welding simulation in an industrial environment as automotive industry. On the other hand, the initial model weakness is compensated by calibrating the model against multiple experiments. The unknown relationship between model and process parameters is approximated by a neural network. The validity of the model is increased successively and enables to decrease experimental effort, For a test case, it is shown that this approach yields accurate temperature fields within very short amount of time for unknown process parameters as input data to the model contributing to the requirement to construct a substitute system of the real welding process.