TY - GEN A1 - Pittner, Andreas A1 - Weiss, D. A1 - Schwenk, Christopher A1 - Rethmeier, Michael T1 - A methodology for the fast temperature field generation for welding simulation T2 - 17th International Conference "Computer Technology in Welding and Manufacturing" CY - Cranfield, UK DA - 2008-06-18 KW - Welding simulation KW - Temperature field generation KW - Short calculation time KW - Multiple experiments KW - Inverse heat conduction problem KW - Neural networks PY - 2008 SN - 978-1-903761-07-6 SP - 1 EP - 12 PB - TWI CY - Cambridge AN - OPUS4-18290 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pittner, Andreas A1 - Weiss, D. A1 - Schwenk, Christopher A1 - Rethmeier, Michael ED - V.I. Makhnenko, T1 - Fast generation and prediction of welding temperature fields for multiple experiments N2 - The objective of this paper is to demonstrate a new simulation technique which allows the fast and automatic generation to temperature fields based on a combination of empirical and phenomenological modelling techniques. The automatic calibration of the phenomenological model is performed by a multi-variable global optimisation routine which yields the optimal fit between simulated and experimental weld charcteristics without the need for initial model parameters. For exemplary welding processes it is shown that linear 3D heat conduction models can approximate measured temperature fields with a high accuracy. The modelling approach presented comprises the automatic calibration against multiple experiments which permits simulating the temperature field for unknown process parameters. The validation of this composite simulation model is performed for exemplary welding processes and includes the prediction of the fusion line in the cross section and the corresponding thermal cycles. T2 - 4th International Conference - Mathematical modelling and information technologies in welding and related processes CY - Katsiveli, Crimea, Ukraine DA - 2008-05-27 KW - Welding simulation KW - GMA-laser hybrid welding KW - Laser beam welding KW - Neural networks KW - Global optimisation KW - Stochastic search method KW - Inverse heat conduction problem KW - Model prediction PY - 2008 SP - 134 EP - 140 CY - Kiev, Ukraine AN - OPUS4-19639 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - RPRT A1 - Pittner, Andreas A1 - Weiss, D. A1 - Schwenk, Christopher A1 - Rethmeier, Michael T1 - Fast temperature field generation for welding simulation and reduction of experimental effort N2 - 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 minimise 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 discretisation 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 optimisation 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. KW - Welding simulation KW - Temperature field generation KW - Short calculation time KW - Multiple experiments KW - Inverse heat conduction problem KW - Neural networks PY - 2009 IS - SC-Auto-32-09 SP - 1 EP - 11 PB - International Institute of Welding CY - Paris AN - OPUS4-19744 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Pittner, Andreas A1 - Schwenk, Christopher A1 - Rethmeier, Michael A1 - Weiß, D. T1 - Automated generation of temperature fields for numerical welding simulation KW - Welding simulation KW - Temperature field generation KW - Optimization KW - Neural networks PY - 2009 SN - 0288-4771 VL - 27 IS - 2 SP - 219 EP - 224 CY - Tokyo, Japan AN - OPUS4-19826 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Pittner, Andreas A1 - Schwenk, Christopher A1 - Rethmeier, Michael A1 - Weiß, D. ED - Hirata, Yoshinori ED - Manabu Tanaka, T1 - Automated generation of temperature fields for numerical welding simulation T2 - 8th International Welding Symposium - Innovations in Welding and Joining for a New Era in Manufacturing CY - Kyoto, Japan DA - 2008-11-16 KW - Welding simulation KW - Temperature Field Generation KW - Optimization KW - Neural Networks PY - 2008 SP - 158 PB - Japan Welding Society CY - Kyoto AN - OPUS4-18614 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -