Andreas Pittner

Methodology to improve applicability of welding simulation

Abstract 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.

Effect of cooling rate on microstructure and properties of microalloyed HSLA steel weld metals

Abstract Two high strength Nb/Ti microalloyed S690QL steels were welded with identical filler material, varying welding parameters to obtain three cooling rates: slow, medium and fast cooling. As cooling rate increased, the predominantly acicular ferrite in Nb weld metal (WM) is substituted by bainite, with a consequence of obvious hardness increase, but in Ti WM, no great variation of acicular ferrite at all cooling rates contributed to little increment of hardness. The transition between bainite and acicular ferrite has been analysed from the point view of inclusions characteristics, chemical composition and cooling rate. Excellent Charpy toughness at 233 K was obtained with acicular ferrite as predominantly microstructure. Even with bainite weld of high hardness, the toughness was nearly enough to fulfill the minimal requirements. WM for Ti steel showed to be markedly less sensitive to the variations of cooling rate than that for Nb steel.

Influence of Solute Content and Solidification Parameters on Grain Refinement of Aluminum Weld Metal

Grain refinement provides an important possibility to enhance the mechanical properties (e.g., strength and ductility) and the weldability (susceptibility to solidification cracking) of aluminum weld metal. In the current study, a filler metal consisting of aluminum base metal and different amounts of commercial grain refiner Al Ti5B1 was produced. The filler metal was then deposited in the base metal and fused in a GTA welding process. Additions of titanium and boron reduced the weld metal mean grain size considerably and resulted in a transition from columnar to equiaxed grain shape (CET). In commercial pure aluminum (Alloy 1050A), the grain-refining efficiency was higher than that in the Al alloys 6082 and 5083. Different welding and solidification parameters influenced the grain size response only slightly. Furthermore, the observed grain-size reduction was analyzed by means of the undercooling parameter P and the growth restriction parameter Q, which revealed the influence of solute elements and nucleant particles on grain size.

Fast Temperature Field Generation For Welding Simulation and Reduction Of Experimental Effort

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.

Environmental energy efficiency of single wire and tandem gas metal arc welding

This paper investigates gas metal arc welding (GMAW) with respect to energy consumption and its associated environmental impacts. Different material transfer modes and power levels for single wire GMAW (SGMAW) and tandem GMAW (TGMAW) are evaluated by means of the indicator electrical deposition efficiency. Furthermore, the wall-plug efficiency of the equipment is measured in order to describe the total energy consumption from the electricity grid. The results show that the energy efficiency is highly affected by the respective process and can be significantly enhanced by a TGMAW process. The wall-plug efficiency of the equipment shows no significant dependency on the power range or the material transfer mode. Moreover, the method of life cycle assessment (LCA) is adopted in order to investigate the influences of energy efficient welding on the environmental impacts. In the comparative LCA study, the demand of electrical energy is reduced up to 24%. In consequence, the indicator values for global warming potential (100), acidification potential, eutrophication potential, and photochemical ozone creation potential are reduced up to 11%.

Numerical sensitivity analysis of TRIP-parameter K on weld residual stresses for steel S355J2+ N

ABSTRACT A combined experimental numerical approach is applied for sensitivity analysis of the transformation induced plasticity (TRIP)-parameter K on weld residual stresses for welding of structural steel of grade S355J2+ N. K was determined experimentally using the Gleeble 3500 facility. A thermomechanical FE model of the real welding process was experimentally validated against temperature field and X-ray stress measurements. Within sensitivity analyses K was varied by several orders of magnitude and the influence on the calculated residual stresses is evaluated by performing corresponding FEA. The correct order of magnitude is sufficient to reproduce the residual stresses qualitatively and quantitatively.

Reconstruction of 3D transient temperature field for fusion welding processes on basis of discrete experimental data

This paper presents an approach to reconstruct the three-dimensional transient temperature field for fusion welding processes as input data for computational weld mechanics. The methodology to solve this inverse heat conduction problem fast and automatically focuses on analytical temperature field models for volumetric heat sources and application of global optimisation. The important issue addressed here is the question which experimental data is needed to guarantee a unique reconstruction of the experimental temperature field. Different computational-experimental test cases are executed to determine the influence of various sets of discrete experimental data on the solvability of the optimisation problem. The application of energy distributions utilised for laser beam welding allows reconstructing the temperature field efficiently. Furthermore, the heat input into the workpiece determined by the simulation contributes to the evaluation of the thermal efficiency of the welding process.

Design of neural network arc sensor for gap width detection in automated narrow gap GMAW

An approach to develop an arc sensor for gap width estimation during automated NG-GMAW with a weaving electrode motion is introduced by combining arc sensor readings with optical measurements of the groove shape to allow precise analyses of the process. The two test specimen welded for this study were designed to feature a variable groove geometry in order to maximize efficiency of the conducted experimental efforts, resulting in 1696 individual weaving cycle records with associated arc sensor measurements, process parameters and groove shape information. Gap width was varied from 18 mm to 25 mm and wire feed rates in the range of 9 m/min to 13 m/min were used in the course of this study. Artificial neural networks were applied as a modelling tool to derive an arc sensor for estimation of gap width suitable for online process control that can adapt to changes in process parameters as well as changes in the weaving motion of the electrode. Wire feed rate, weaving current, sidewall dwell currents and angles were defined as inputs to calculate the gap width. The evaluation of the proposed arc sensor model shows very good estimation capabilities for parameters sufficiently covered during the experiments.

Strain-rate controlled Gleeble experiments to determine the stress-strain behavior of HSLA steel S960QL

Abstract In order to generate a material data base for computational welding mechanics, temperature and strain-rate dependent stress-strain experiments were performed by using a Gleeble® 3500 testing system. The object of the investigation was HSLA transformable steel S960QL and related solid phases as bainite, martensite and austenite. For the production of these solid phases, the base material was heat treated according to an average weld temperature cycle which was extracted within the heat affected zone of a thermal numerical weld simulation of a GMA weld. The hot tensile tests were carried out via cost-saving flat specimen geometries. Two experimental series with different strain-rates were conducted, where the longitudinal strain-rate was controlled by specification of the transversal strain-rate applying Poissons-ratio. Subsequently, the resulting stress-strain curves were approximated in accordance with the Ramberg-Osgood-materials law. Consequently, it is shown that the temperature and strain-rate dependent stress-strain behavior of metals can be successfully characterized by means of a Gleeble®-system. However, this requires a control of the longitudinal strain-rate by specification of the transversal strain-rate. The related experimental procedure and the method of evaluation are explained in detail. With regard to all tested solid phases, a significant strain-rate dependency can only be observed upwards from temperatures of 400 °C. Based on experimental results, Ramberg-Osgood-parameters will be presented to describe the stress-strain behavior of steel S960QL and related solid phases for temperatures between 25 °C and 1200 °C. Furthermore, the use of cost-saving flat specimen-geometry appears reasonable.