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Fusion welding processes are widely used for joining metal structures, such as pipes, ships, and cars. In general, these joining processes offer a very good compromise between reliability, safety, cost and maintenance which are important issues in the current economical context. The negative heat effects of welding, i.e. distortions and residual stresses of the welded parts, are well known and many researches in this field have already been done in the last decades in order to minimize them. On the experimental side, many sophisticated procedures have become state of the art to deal with this problem. On the computational side, the improvement of the simulation algorithms and the computing power enables the simulations of many physical phenomena occurring during the welding process. The implementation of welding simulation techniques is nevertheless not an easy task and often associated with expert knowledge which hinders their global application in an industrial environment. This paper is focused on the industrial requirements of a welding simulation software with special respect to the needs of the automotive industry. The necessary information to run a welding simulation and the expectations of a weld specialist without deep knowledge in numerical methods are investigated. These expectations are tested on an automotive welded assembly with a commercially available welding simulation software designed especially for the needs of the automotive industry. A welding experiment is done and the measured temperature distributions and distortions serve as reference to validate the simulation results. The result quality of the simulations of temperature fields and distortions is in best agreement with experimental data. The workflow is well adapted for the considered industrial requirements and the time-tosolution as well as the computational costs are acceptable, whereas the efficient calibration of the heat input model is still a point which will be further investigated in current and future research works.
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.
The non-uniform heat input during the welding process leads to problematic permanent deformations of welded parts. The control of these welding distortions is, with the absence of the knowledge of the fundamental mechanisms responsible for these deformations, an extremely time and cost consuming iterative “trial-and-error” optimization process. The visualization of the involved physical phenomena, like temperature and distortions, .is an indispensable tool to clearly identify these mechanisms in order to adapt the welding parameters and clamping conditions target-oriented. Both experimental and virtual methods exist to obtain these physical data, however the possibilities to visualize them with experimental methods are laborious, expensive and limited in their application. Welding Simulation using finite element analysis (FEA) offers many benefits and has a great potential to reduce the experimental effort. Nevertheless, the industrial application of welding Simulation is not yet established widely because of reservations regarding the computation costs and the resulting accuracy for instance. In this paper, the results of a case study for a welding Simulation with an industrial background are presented. A welded assembly from the automotive industry has been investigated with numerical and experimental methods. A comparison between both methods demonstrates the Potentials of welding Simulation in terms of visualization. Furthermore, the numerical results reveal the possibilities of current resources. regarding calculation time and result accuracy of an industrial applied welding Simulation.
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.
Fusion welding is widely used in the automotive industry to join metal structures. 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. The implementation of a welding Simulation tool to reduce this very expensive experimental procedures is therefore of high interest. Despite the fact that the automotive industry is a key sector for Simulation procedures, welding Simulation Software is nevertheless not yet widely implemented. This is mainly due to the complexity of the Simulation tools requiring expert users and the resulting high time to Solution.
In this study, a new fast thermo-mechanical Simulation of a complex and large laser beam welded automotive sheet metal assembly with several non linear welds is simulated. Assumptions and simplifications of the complex physical welding phenomenon, which are made to keep the computational cost and the complexity of the Simulation in an industrial frame, are discussed. The calibration time of the phenomenological heat source model has been optimized with a very fast analytical thermal model and the resulting simulated temperature fields match perfectly with the measured ones. Additionally, the user experience and the time-to-solution are kept within a reasonable time frame for arr industrial environment. All Simulation results are validated with experimental results.
In contrast to other simulation fields like forming simulation, welding simulation is still not widely used in industrial environments. A high user expertise, a high time-to-solution and the result accuracy are the most important problems that hinder its extensively application. Different modeling approaches influence these aspects and an analysis of their implementation is of interest especially for the automotive industry as a key user for production Simulation.
Das Ziel der vorliegenden Vorstudie ist es, die grundsätzlichen Anforderungen, Funktionen und Möglichkeiten vorhandener Software zur Simulation schweißbedingter Phänomene (Prozess-, Struktur- und Werkstoffsimulation) zu erarbeiten und gegenüberzustellen. Die notwendigen Eingabedaten, die vorausgesetzte Anwendererfahrung, sowie die Systemanforderungen und der Rechenzeitbedarf werden für sowohl kommerziell erhältliche als auch zur Zeit noch rein in der Forschung angewandte Programme berücksichtigt.
Nach Aufarbeitung des heutigen Kenntnisstandes der Schweißsimulation wird aktuell verfügbare Software diskutiert. Diese Programme lassen sich in Anlehnung an Radaj in drei Teilbereiche (Software für Struktursimulation, Prozesssimulation und Werkstoffsimulation) unterteilen. Schließlich wird auf notwendige Eingabedaten, hier vor Allem auf die Werkstoffkennwerte, eingegangen. Da die quantitative Aussagekraft der Simulationsergebnisse gewährleistet werden muss, ist eine umfassende Prüfung der Plausibilität und der Genauigkeit der experimentell bestimmten Werkstoffkennwerte notwendig.