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For differentiating the applicability of various numerical welding simulation methods as well as unifying the prerequisites and the steps to be taken in simulation, normative codes are required for the user. Since any standard-like documents are currently still lacking in this field, the DIN German Institute for Standardization in partnership with the Research Association of DVS German Welding Society have set up a standards committee dealing with the preparation of respective documents.
This article focuses on the presentation of the new DIN Spec 32534-1 explaining the major simulation steps and specifying the application fields and the key terms of welding simulation. In addition, a generally valid simulation structure has been established which is intended to serve as a recommendation for customers and suppliers in formulating and handling a service order as well as for persons who start doing welding simulation for the first time. It additionally gives an overview of the other subject areas dealt with in the standards committee as well as of the international activities in this field.
Für die Abgrenzung der Anwendbarkeit verschiedener Methoden der numerischen Schweißsimulation sowie für die Vereinheitlichung der Voraussetzungen und der durchzuführenden Schritte bei der Simulation sind normative Regelwerke für den Anwender erforderlich. Da es derzeit noch keine normähnlichen Dokumente auf diesem Gebiet gibt, wurde vom DIN der Arbeitsausschuss NA 092-00-29-A "Schweißsimulation" gegründet, welcher sich mit der Erarbeitung der entsprechenden Dokumente befasst. Dieses Gremium wurde gemeinsam mit dem Gemeinschaftsausschuss FA 12 "Anwendungsnahe Schweißsimulation" der Forschungsvereinigung des DVS initiiert.
Das Ziel der Normungsarbeit im Bereich der numerischen Schweißsimulation besteht in der Erarbeitung einer DIN SPEC, die die Vorgehensweisen bei der Simulation verschiedener Schweißphänomene und -verfahren langfristig standardisieren soll. In einem durch den genannten Arbeitsausschuss bereits vorbereiteten Entwurf der DIN SPEC 32534-1 wurde die Struktur des Hauptdokuments festgelegt. Im Hauptdokument sind die Anwendungsbereiche und die wesentlichen Begriffe der Schweißsimulation spezifiziert. Des Weiteren wurde die allgemein gültige Simulationsstruktur erarbeitet, welche als Empfehlung für den Auftraggeber und den Auftragnehmer bei der Formulierung und Abwicklung eines Dienstleistungsauftrages sowie für den Neueinstieg in die Schweißsimulation dienen soll.
Den Schwerpunkt stellt die Vorstellung der neuen DIN SPEC mit der Erläuterung der wesentlichen Simulationsschritte dar. Im Weiteren wird auf die Klassifizierung der Unterdokumente in Abhängigkeit des Schweißverfahrens und des angestrebten Simulationsergebnisses eingegangen. Schließlich wird ein Ausblick auf die weiteren Themenfelder des Arbeitsausschusses NA 092-00-29-A "Schweißsimulation" sowie auf die internationalen Aktivitäten auf diesem Gebiet gegeben.
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.
The objective of this paper is to demonstrate a new simulation technique which allows fast and automatic generation of temperature fields as input for subsequent thermomechanical welding simulation. The basic idea is to decompose the process model into an empirical part based on neural networks and a phenomenological part that describes the physical phenomena. The strength of this composite modelling approach is the automatic calibration of mathematical models against experimental data without the need for manual interference by an experienced user. As an example for typical applications in laser beam and GMA-laser hybrid welding, it is shown that even 3D heat conduction models of a low complexity can approximate measured temperature fields with a sufficient accuracy. In general, any derivation of model fitting parameters from the real process adds uncertainties to the simulation independent of the complexity of the underlying phenomenological model. The modelling technique presented hybridises empirical and phenomenological models. It reduces the model uncertainties by exploiting additional information which keeps normally hidden in the data measured when the model calibration is performed against few experimental data sets. In contrast, here the optimal model parameter set corresponding to a given process parameter is computed by means of an empirical submodel based on relatively large set of experimental data. The approach allows making a contribution to an efficient compensation of modelling inaccuracies and lack of knowledge about thermophysical material properties or boundary conditions. Two illustrating examples are provided.
In diesem Artikel wird eine Übersicht über die Methoden zurnumerischen Berechnung schweißbedingter Bauteilverzüge fürindustrielle Anwendungen gegeben. Zunächst werden die Anforderungen der Automobilindustrie an die benötigte Softwaredargestellt. Dabei wird zwischen der industriellen Forschungund der Entwicklung/Produktionsplanung differenziert. Es werden die verschiedenen derzeit verfügbaren Ansätze zur numerischen Schweißsimulation vorgestellt und deren Möglichkeitenzur Erfüllung der dargestellten Bedürfnisse erläutert. Anhand eines aktuellen Bauteils aus der Automobilindustrie (B-SäuleVW Golf) wird beispielhaft die Verzugsoptimierung mit Hilfe einer Berechnungsmethodik aufgezeigt, welche sich durch eine schnelle Modellerstellung, kurze Rechenzeiten und einfache Handhabung auszeichnet. Ein Vergleich der Simulationsergebnisse mit experimentell ermittelten Daten zeigt sehr gute Über-einstimmungen und verdeutlicht das immense Potenzial einer numerisch unterstützten Prozessoptimierung.
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.
Fast temperature field generation for welding simulation and reduction of experimental effort
(2009)
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.