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Eingeladener Vortrag
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Effect of cooling rate on microstructure and properties of microalloyed HSLA steel weld metals
(2015)
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.
Despite the advances in hardware and software techniques, standard numerical methods fail in providing real-time simulations, especially for complex processes such as additive manufacturing applications. A real-time simulation enables process control through the combination of process monitoring and automated feedback, which increases the flexibil- ity and quality of a process. Typically, before producing a whole additive manufacturing structure, a simplified experiment in form of a bead-on- plate experiment is performed to get a first insight into the process and to set parameters suitably. In this work, a reduced order model for the transient thermal problem of the bead-on-plate weld simulation is devel- oped, allowing an efficient model calibration and control of the process. The proposed approach applies the proper generalized decomposition (PGD) method, a popular model order reduction technique, to decrease the computational effort of each model evaluation required multiple times in parameter estimation, control and optimization. The welding torch is modeled by a moving heat source, which leads to difficulties separating space and time, a key ingredient in PGD simulations. A novel approach for separating space and time is applied and extended to 3D problems allowing the derivation of an efficient separated representation of the tem- perature. The results are verified against a standard finite element model showing excellent agreement. The reduced order model is also leveraged in a Bayesian model parameter estimation setup, speeding up calibrations and ultimately leading to an optimized real-time simulation approach for welding experiment using synthetic as well as real measurement data.
Welding is the most important joining technology. In the steel construction
industry, e.g. production of windmill sections, welding accounts for a
main part of the manufacturing costs and resource consumption. Moreover, social
issues attached to welding involve working in dangerous environments. This aspect
has unfortunately been neglected so far, in light of a predominant focus on economics
combined with a lack of suitable assessment methods. In this chapter,
exemplary welding processes are presented that reduce the environmental and
social impacts of thick metal plate welding. Social and environmental Life Cycle
Assessments for a thick metal plate joint are conducted for the purpose of
expressing and analysing the social and environmental impacts of welding.
Furthermore, it is shown that state-of-the-art technologies like Gas Metal Arc
Welding with modified spray arcs and Laser Arc-Hybrid Welding serve to increase
social and environmental performance in contrast to common technologies, and
therefore offer great potential for sustainable manufacturing.
The microstructure of a fusion weld has great influences on the susceptibility of the base material to hot cracking and on the mechanical properties of the weld. Small, globulitic grains are necessary for increased strength, ductility and toughness and for a low inclination to hot cracking instead of large, oblong grains. This study reports on the factors which exert the main influences on such grain refinement in the weld. Thus, the influences of the thermal conditions, the chemical composition of the weld metal and the number and type of solidification nuclei on the microstructure were classified for the TIG welding of three different aluminium alloys.
To increase the competitiveness of jacket substructures compared to monopiles a changeover from an individual towards a serial jacket production based on automated manufactured tubular joints combined with standardized pipes has to be achieved. Therefore, this paper addresses fatigue tests of automatically welded tubular X-joints focusing on the location of the technical fatigue crack. The detected location of the technical crack is compared to numerical investigations predicting the most fatigue prone notch considering the structural stress approach as well as the notch stress approach. Besides, the welding process of the automated manufactured tubular X-joints is presented.
To increase the competitiveness of jacket substructures compared to monopiles a changeover from an individual towards a serial jacket production based on automated manufactured tubular joints combined with standardized pipes has to be achieved. Therefore, this paper ad-dresses the welding process of automated manufactured tubular X-joints. Additionally, fatigue tests of the automatically welded tubular joints are presented focusing on the location of the technical fatigue crack. The detected location of the technical crack is compared to numerical investigations predicting the most fatigue prone notch con-sidering the structural stress approach as well as the notch stress ap-proach.
To increase the competitiveness of jacket substructures compared to monopiles a changeover from an individual towards a serial jacket production based on automated manufactured tubular joints combined with standardized pipes has to be achieved. Therefore, this paper addresses fatigue tests of automatically welded tubular X-joints focusing on the location of the technical fatigue crack. The detected location of the technical crack is compared to numerical investigations predicting the most fatigue prone notch considering the structural stress approach as well as the notch stress approach. Besides, the welding process of the automated manufactured tubular X-joints is presented.
Life cycle assessment of fusion welding processes considering upstream and downstream process steps
(2023)
In manufacturing, fusion welding processes consume significant resources, presenting a significant opportunity for reducing environmental impact. Although there is a qualitative understanding of the environmental implications of these processes, a quantitative assessment of key parameters remains complex. This study introduces a welding-specific methodology that employs life cycle assessment (LCA) to quantitatively evaluate the environmental footprint of fusion welding technologies. Our approach identifies and analyses the principal parameters affecting the environmental performance of various welding techniques, including traditional joint welding and additive manufacturing via the Direct Energy Deposition-Arc (DED-Arc) process. Real-time resource usage data is integrated to offer an innovative framework for directly deriving environmental impacts. This research contributes to optimising welding processes by providing a precise and quantifiable measure of their ecological impact. This facilitates the advancement of sustainable manufacturing practices.
In manufacturing, fusion welding processes use a lot of resources, which presents an opportunity to reduce environmental impact. While there is a general understanding of the environmental impact of these processes, it is difficult to quantitatively assess key parameters. This study introduces a welding-specific methodology that uses life cycle assessment (LCA) to evaluate the environmental impact of fusion welding technologies. Our approach analyses the main parameters that affect the environmental performance of different welding techniques, including traditional methods and additive manufacturing through the Direct Energy Deposition-Arc (DED-Arc) process. We integrate real-time resource usage data to offer an innovative framework for directly deriving environmental impacts. This research contributes to optimising welding processes by providing a precise and quantifiable measure of their ecological impact, facilitating the advancement of sustainable manufacturing practices.
Direct energy deposition additive manufacturing technologies utilizing an electric arc offer a great potential in generating large volume metal components. However, the selection of process parameters that yield the desired near net shape design as well as the requested mechanical component behavior is not a trivial task due to the complex relationship. Exemplarily for additive manufacturing of high-strength precipitation hardening AlMgSi-aluminum alloy this paper shows the application of a newly developed matching solid welding wire doped with TiB as grain refiner. The correlation between process parameters and component quality is examined analyzing the size and distribution of pores as well as the grain morphology. Furthermore, the influences of different post-weld heat treatments are evaluated to meet the reference mechanical properties of the corresponding wrought material. Finally, the digital integration of the entire additive manufacturing chain enables an overall traceability of the relevant process steps which is the basis for a reliable subsequent quality assessment.
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.
Offshore wind energy plays an important role for the desired transition towards a carbon dioxide free industry within the next decades. However, the grounding of the offshore wind plants governs the overall installation process besides bureaucratic bottlenecks.
The application of lightweight principles in steel construction, e.g. the usage dissolved load-bearing structures, so called Jackets foundations, offer great potential in reducing the resource consumption, especially with respect to the needed amount of steel.
In this context this paper focuses on a fully digitalization of the welding manufacturing and as well as testing chain to enable a fully automated manufacturing as well as quality assessment of tubular nodes as key element of Jackets foundation structures. Furthermore, the relationship between the seam shape geometry and resulting fatigue strength is evaluated by numerical methods incorporating bionic principles. It is shown that tubular nodes can be welded fully automatically taking geometry tolerances into account. Moreover, the seam shape could be manufactured as requested by the numerical models which offers great potential for an extended lifetime. Subsequently, the improvements in resource efficiency and reduction of carbon dioxide emissions are evaluated by a life-cycle-assessment.
Offshore wind energy plays an important role for the desired transition towards a carbon dioxide free industry within the next decades. However, the grounding of the offshore wind plants governs the overall installation process besides bureaucratic bottlenecks.
The application of lightweight principles in steel construction, e.g. the usage dissolved load-bearing structures, so called Jackets foundations, offer great potential in reducing the resource consumption, especially with respect to the needed amount of steel.
In this context this paper focuses on a fully digitalization of the welding manufacturing and as well as testing chain to enable a fully automated manufacturing as well as quality assessment of tubular nodes as key element of Jackets foundation structures. Furthermore, the relationship between the seam shape geometry and resulting fatigue strength is evaluated by numerical methods incorporating bionic principles. It is shown that tubular nodes can be welded fully automatically taking geometry tolerances into account. Moreover, the seam shape could be manufactured as requested by the numerical models which offers great potential for an extended lifetime. Subsequently, the improvements in resource efficiency and reduction of carbon dioxide emissions are evaluated by a life-cycle-assessment.
The present thesis provides a contribution to the solution of the inverse heat conduction problem in welding simulation. The solution strategy is governed by the need that the phenomenological simulation model utilised for the direct solution has to provide calculation results within short computational time. This is a fundamental criterion in order to apply optimisation algorithms for the detection of optimal model parameter sets. The direct simulation model focuses on the application of functional-analytical methods for solving the corresponding partial differential equation of heat conduction. In particular, volume heat sources with a bounding of the domain of action are applied. Besides the known normal and exponential distribution, the models are extended by the introduction of parabolically distributed heat sources. Furthermore, the movement on finite specimens under consideration of curved trajectories has been introduced and solved analytically. The calibration of heat source models against experimental reference data involves the simultaneous adaptation of model parameters. Here, the global parameter space is searched in a randomised manner. However, an optimisation pre-processing is needed to get information about the sensitivity of the weld characteristics like weld pool dimension or objective function due to a change of the model parameters. Because of their low computational cost functional-analytical models are well suited to allow extensive sensitivity studies which is demonstrated in this thesis. For real welding experiments the applicability of the simulation framework to reconstruct the temperature field is shown. In addition, computational experiments are performed that allow to evaluate which experimental reference data is needed to represent the temperature field uniquely. Moreover, the influence of the reference data like fusion line in the cross section or temperature measurements are examined concerning the response behaviour of the objective function and the uniqueness of the optimisation problem. The efficient solution of the inverse problem requires two aspects, namely fast solutions of the direct problem but also a reasonable number of degrees of freedom of the optimization problem. Hence, a method was developed that allows the direct derivation of the energy distribution by means of the fusion line in the cross section, which allows reducing the dimension of the optimisation problem significantly. All conclusions regarding the sensitivity studies and optimisation behaviour are also valid for numerical models for which reason the investigations can be treated as generic.
The application of welded aluminum constructions has increased over the last decades due to the high demand for lightweight design. In this context aluminum alloys have a significant importance especially the heat treatable Al-Mg-Si alloys. With regards to welding the heat input causes the dissolving of the precipitates yielding a degradation of the strength properties. Furthermore, there is the risk of solidification cracking during welding for Al-Mg-Si alloys, especially AW 6082-T6. As a consequence Al-Mg-Si alloys are welded using a dissimilar filler material based on 5xxxx aluminum alloys that yields a reduction of resulting strength properties in comparison to the base material. Therefore, the paper presents the application of a novel massive filler wire for Al-Mg-Si alloys. The wire consists of AW 6082 with additionally added AlTi5B1 master alloy fostering the grain refinement of the weld metal. Exemplarily for the base material AW 6082-T6 GMA welding experiments are performed using the novel filler wire 6082TiB. It could be shown that solidification cracks could totally be avoided. The tensile strength of the welded joints are evaluated and compared with weldments using a conventional 5183 filler wire. Artificial aging is performed after welding in order to improve the strength properties by solution hardening showing the potential of these alloys.
The digitalization of industrial processes is the most discussed topic in society these days. New business models have been developed to benefit from the opportunities offered by a digitally connected world. However, the focus in on the smart factory consisting of autonomous acting cyber physical systems (CPS). The efficient implementation of such CPS within an industrial environment requires the digitalization of the corresponding production processes. The digital twin of the process under investigation enables to develop sophisticated monitoring and control strategies which are necessary to fulfil the requirements of individual product design.
The need for a digitalization of the welding process is a logical consequence especially with regards to its industrial importance. The theoretical investigations and derived mathematical models of the welding process are well known since many decades. Anyhow, there is still a lack of industrial applicability of such models for an efficient and safe design of welded components. With respect to structural welding simulation that targets the heat effects of welding in terms of global quantities like temperature, solid phase distribution and residual stresses as well as distortions, the limited predictability of these quantities for arbitrary process parameters hinders its usability.
This presentation aims to give an overview of the current state of the art in structural welding simulation to predict the evolution of welding induced temperatures, stresses and distortions. Emphasis is given to industrial applicability of such models by reduction of the calculation times for large real-world structures and improved prediction of optimal process parameters. Furthermore, the role of such models within a weld data management system is demonstrated. The accumulation and relational storage of simulation and measuring data improves the overall process knowledge. This enables virtual cause and effect analyses of new process parameters as basis for a control system design.
The development within the offshore wind energy sector towards
more powerful turbines combined with increasing water depth
for new wind parks is challenging both, the designer as well as
the manufacturer of support structures. Besides XL-monopiles
the jacket support structure is a reasonable alternative due to the
high rigidity combined with low material consumption. However,
the effort for manufacturing of the hollow section joints reduces
the economic potential of jacket structures significantly. Therefore,
a changeover from an individual towards a serial production
based on automated manufactured tubular joints combined with
standardized pipes has to be achieved. Hence, this paper addresses
the welding process chain of automated manufactured
tubular joints including digitization of the relevant manufacturing parameters such as laser scanning of the weld seam geometry.
Numerical Sensitivity Analysis of TRIP-Parameter K on Weld Residual Stresses and Weld Distortion
(2016)
A combined experimental numerical approach is applied for a sensitivity analysis of the transformation induced plasticity (TRIP)-parameter K on welding residual stresses and welding distortion for the welding of the low-alloyed high-strength S960QOL with the high-alloyed hig-strength filler material CN13-4-IG. A thermo-mechanical FE model of a real GMA welding process was experimentally validated against termperature field, X-Ray stress measurments and optical distortion measurement. Within the sensititvity analysis K was varied and the influence on the calculated welding residual stresses and welding distortion is evaluated by performing corresponding FEA. The correct order of K magnitude is necessary in order to reproduce the residual stresses qualitatively and quantitatively. For the sufficient reproducing of the welding distortion the transformation induced plasticity can be neglected.
More than 80 representatives of SMEs, industrial companies and research institutes met on September 12 at the workshop "Challenges in Additive Manufacturing: Innovative Materials and Quality Control" at BAM in Adlershof to discuss the latest developments in materials and quality control in additive manufacturing.
In special lectures, researchers, users and equipment manufacturers reported on the latest and future developments in additive manufacturing. Furthermore, funding opportunities for projects between SMEs and research institutions on a national and European level were presented.
Ultrasonic vibration enhanced friction stir welding (UVeFSW) is a recent modification of conventional friction stir welding (FSW), which transmits ultrasonic vibration directly into the localized area of the workpiece near and ahead of the rotating tool. In this study, a high strength aluminium alloy (2024-T4) was welded by this process and conventional FSW, respectively. Then tensile tests, microhardness tests and fracture surface analysis were performed successively on the welding samples. The tests results reveal that ultrasonic vibration can improve the tensile strength and the elongation of welded joints. The microhardness of the stir zone also increases.
The paper presents bounded volume heat sources and the corresponding functional-analytical expressions for the temperature field. The power density distributions considered here are normal, exponential and parabolic. The sources model real heat sources like the welding arc, laser beam, electron beam, etc., the convection in the weld pool as well as the latent heat due to fusion and solidification. The parameters of the heat source models are unknown a priori and have to be evaluated by solving an inverse heat conduction problem. The functional-analytical technique for calculating 3D temperature fields in butt welding is developed. The proposed technique makes it possible to reduce considerably the total time for data input and solution. It is demonstrated with an example of laser beam welding of steel plates.
This paper presents volume heat sources and the corresponding functional analytical Solutions for the transient temperature field. The considered energy distributions are normal, exponential and parabolic. The method follows the common approach in Computational Welding Mechanics (CWM) to account for the physics of the welding process and the resulting temperature field by phenomenological models for heat conduction. Therefore, the used heat source models are apparent heat sources that incorporate the real heat input as well as the fluid flow in the weld pool and the latent heat connected with phase transformations. The heat source models provide welding characteristics like thermal cycle and Fusion line in the cross section within short computational time. Consequently, inverse techniques on basis of optimisation algorithms enable the adaptation of the models to the experimental data efficiently. Furthermore, the direct evaluation of the energy distribution for the experimental fusion line in the cross section is demonstrated which enhances the numerical optimisation by reducing the number of unknown model Parameters and providing a reasonable initial guess within the model parameter space. The proposed temperature field models are validated with real laser beam welding experiments.
The determination of mechanical properties of welded Steel structures such as strength or ductility is a subject of high interest for the majority of Companies in the area of metal Processing. The material Parameters can be obtained by performing the tensile test on the samples made from a part of a component. In some cases, it is highly expensive to produce the tensile specimens especially from the weld metal, which contains different type of microstructure such as weld seam or heat affected zone in an extremely small area. Therefore, a method is described in this paper to determine the material Parameters of high strength Steel structures and welded joints locally and without any additional effort to perform the tensile test. In this method, instrumented indentation technique (IIT), an indenter is pushed on the flat surface of a specimen in a certain period of time and simultaneously the applied force and the corresponding indentation path are measured. The data related to the force-indentation diagram is given as input to an artificial neural network (ANN) to obtain the material Parameters. The ANN can be trained by generating the large qualitative data sets with numerical Simulation of the IIT procedure. The Simulation must be run several times with the different material model parameter sets to generate the numerous
force-indentation diagrams as the inputs of ANN. Then, the trained ANN is validated by performing the IIT on the welded joints and comparing the obtained material Parameters from ANN with the tensile test.
Consequently, the mechanical properties of welded joints can be determined by performing the IIT and evaluating the resulting data by the ANN.
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 measurement 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 to 25 mm and wire feed rates in the range of 9 to 13 m/min were used in the course of this study. Artificial neural networks were used 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 used as inputs to calculate the gap width. Evaluation the proposed arc sensor model show very good estimation capabilities for parameters sufficiently covered during experiments.
An experimental setup to integrate laser sensor into conventional GMAW setups via a unified control architecture is described. The setup is used to automate and monitor narrow-gap GMAW. A way to develop GMAW arc-sensors using artificial neural networks using the setup is shown.
The control system is connected to a relational database to store various process measurements. The database can be accessed to filter previous weldments by numerous criteria which allows modelling of process parameter correlation among vast datasets. Such models can be used for process monitoring and control in future applications.