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Eingeladener Vortrag
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Life Cycle Assessment (LCA) and Social Life Cycle Assessment (SLCA) are applied in evaluating possible social and environmental impacts of the state-of-art welding technologies, such as Manual Metal Arc Welding (MMAW), Manual Gas Metal Arc Welding (GMAW), Automatic GMAW and Automatic Laser-Arc Hybrid Welding (LAHW). The LCA results indicate that for 1 meter weld seam, MMAW consumes the largest amount of resources (like filler material and coating on electrodes) and energy, which contributes to comparatively higher environmental impacts in global warming potential, acidification, photochemical ozone creation potential and eutrophication than other chosen processes. With regard to social aspects, the health issues and fair salary are under survey to compare the relative potential risk on human health caused by fumes in different welding technologies, and to indicate the sufficiency of current salary of welders in Germany. The results reflect that the wage status of welders is still fair and sufficient. The manual processes bring much higher potential risk of welders health than the automatic processes, especially MMAW.
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.
The increasing adoption of Open Science principles has been a prevalent topic in the welding science community over the last years. Providing access to welding knowledge in the form of complex and complete datasets in addition to peer-reviewed publications can be identified as an important step to promote knowledge exchange and cooperation. There exist previous efforts on building data models specifically for fusion welding applications; however, a common agreed upon implementation that is used by the community is still lacking. One proven approach in other domains has been the use of an openly accessible and agreed upon file and data format used for archiving and sharing domain knowledge in the form of experimental data. Going into a similar direction, the welding community faces particular practical, technical, and also ideological challenges that are discussed in this paper. Collaboratively building upon previous work with modern tools and platforms, the authors motivate, propose, and outline the use of a common file format specifically tailored to the needs of the welding research community as a complement to other already established Open Science practices. Successfully establishing a culture of openly accessible research data has the potential to significantly stimulate progress in welding research.
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 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.
Microcrack formation during gas metal arc welding of high-strength fine-grained structural steel
(2014)
The recent development of high-performance-modified spray arc processes in gas metal arc welding due to modern digital control technology and inverter power sources enables a focused spray arc, which results in higher penetration depths and welding speed. However, microcracks occurred in the weld metal while approaching the process limits of the modified spray arc, represented by a 20-mm double layer DV-groove butt-weld. These cracks were detected in structural steel exhibiting a yield strength level of up to 960 MPa and are neither dependent on the used weld power source nor a consequence of the modified spray arc process itself. The metallographic and fractographic investigations of the rather exceptional fracture surface lead to the classification of the microcracks as hot cracks. The effects of certain welding parameters on the crack probability are clarified using a statistical design of experiment. However, these microcracks do not impact the design specification for toughness in the Charpy V-notch test (absorbed energy at -40 °C for the present material is 30 J).
Austenite grain growth during welding is a critical factor for controlling weld microstructure in addition to nominal composition and thermal cycles. Recently, experimental data suggesting a decrease in martensite start temperature with a decrease in prior austenite grain size has been published. However, the actual sensitivity of this phenomenon on residual stresses evolution in the heat-affected zone has not been investigated, yet. Therefore, a numerical model was modified to consider this phenomenon. Numerical simulations were performed for welding of a low-alloy structural steel with minimum yield strength of 355 MPa (S355J2+N) and a heat-resistant steel P91 or 9Cr–1Mo, respectively. The results clarify the influence of prior austenite grain size on the residual stress development and show the importance martensite transformation temperatures and final martensite fraction. Consequently, the residual stress evolution of P91, which completely transforms to martensite while cooling, based on the enhanced model leads to maximum stress differences of 200 MPa in the heat-affected zone.
The sound numerical prediction of welding-induced thermal stresses, residual stresses, and distortions strongly depends on the accurate description of a welded material’s thermomechanical deformation behaviour. In this work, we provide experimental data on the viscoplastic deformation behaviour of a grade-s960ql steel up to a temperature of 1000 ◦C. In addition, a multi-phase viscoplastic material model is proposed, which accounts for the experimentally observed isothermal deformation behaviour of grade-s960ql steel base and austenitised material, as well as for athermal contributions that originate from solid-state phase transformations. The multi-phase viscoplastic and a classic rateindependent isotropic hardening material model were applied in the numerical simulations of both-ends-fixed bar Satoh tests and a single-pass gas metal arc weld. The influence of material modelling choices on the agreement between numerical simulation and experimental results is discussed, and recommendations for further work are given.
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.
Resistance spot welding (RSW) is widely used in the automotive industry
as the main joining method. Generally, an automotive body contains
around 2000 to 5000 spot welds. Therefore, it is of decisive importance to characterize the mechanical properties of these areas for the further optimization and improvement of an automotive body structure. The present paper aims to introduce a novel method to investigate the mechanical properties and microstructure of the resistance spot weldment of DP1000 sheet steel. In this method, the microstructure of RSW of two sheets was reproduced on one sheet and on a bigger area by changing of the welding parameters, e. g. welding current, welding time, electrode force and type. Then, tensile tests in combination with digital Image correlation (DIC) measurement were performed on the notched tensile specimens to determine the mechanical properties of the weld metal.
The notch must be made on the welded tensile specimen to force the fracture and elongation on the weld metal, enabling the characterization of its properties. Additionally, the parameters of a nonlinear isotropic material model can be obtained and verified by the simulation of the tensile specimens. The parameters obtained show that the strength of DP1000 steel and the velocity of dislocations for reaching the Maximum value of strain hardening, are significantly increased after RSW. The effect of sample geometry and microstructural inhomogeneity of the welded joint on the constitutive property of the weld metal are presented and discussed.
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.
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.
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.
A combined experimental and numerical approach is applied for a numerical analysis of the non-uniform martensitic transformation kinetic on welding residual stresses and distortion of a single pass weld. The (γ → α)-transformation kinetic within the weld pool region is governed by a non-uniform distribution of the elements chromium and nickel. The single-pass weld was performed by use of the low-alloyed high-strength steel S960QL with the high-alloyed high-strength filler wire CN 13/4-IG®. A thermo-mechanical FE model of the welding process was experimentally validated against temperature field, solid phase distribution, transformation behaviour, X-Ray stress measurements and transient optical distortion measurements.
The experimentally determined and calculated weld residual stresses and transient distortion are in good agreement. It can be shown that the change on the (γ → α)-transformation kinetic driven by the inhomogeneous distribution of the chemical contents causes a strong influence on the weld residual stresses within the volume of the weld pool, which could promote crack propagation within the solidified weld pool by use of high-alloyed filler materials. Furthermore, a significant influence on the development of the transient welding distortion is visible. This influence should be respected during numerically calculation of welding distortion in case of multi-pass welding using interpass temperatures and high-alloyed filler materials.
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.
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 Poisson’s-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 costsaving flat specimen-geometry appears reasonable.
A combined experimental numerical approach is applied to determine the transformation induced plasticity (TRIP)-parameter K for different strength low-alloy steels of grade S355J2+N and S960QL as well as the super martensitic filler CN13-4-IG containing 13 wt% chromium and 4 wt% nickel. The thermo-physical analyses were conducted using a Gleeble® 3500 facility. The thermal histories of the specimens to be tested were extracted from corresponding simulations of a real gas metal arc weldment. In contrast to common TRIP-experiments which are based on complex specimens a simple flat specimen was utilized together with an engineering evaluation method. The evaluation method was validated with literature values for the TRIP-parameter. It could be shown that the proposed approach enables a correct description of the TRIP behavior.
Numerical sensitivity analysis of TRIP-parameter K on weld residual stresses for steel S355J2+ N
(2016)
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.
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.
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.
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.
The high amount of resource consumption of fusion welding processes offers the potential to reduce their environmental impact. While the driving forces are known froma qualitative perspective, the quantitative assessment of the crucial parameters is not a trivial task. Therefore, herein, a welding-specific methodology to utilize life cycle assessment as a tool for evaluating the environmental impact of fusion welding processes is presented. In this context, two welding processes, resistance spot welding and laser beam welding, are analyzed for two different use cases.
These comprise the welding of shear test specimens and a cap profile made of electrogalvanized sheets of DC 05þ ZE (1.0312) as representative of an automotive application. For both welding processes, the main influences on the resulting environmental impact categories are evaluated and compared. The requirements for ecological efficient welding processes are discussed and implemented.
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 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.
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.
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.
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 com-bined with standardized pipes has to be achieved. Therefore, this paper addresses fatigue tests of automatical-ly welded tubular X-joints focusing on the location of the technical fatigue crack. For this X-joint, the detect-ed location of the technical crack is then compared to numerical investigations predicting the most fatigue prone notch considering the structural stress approach as well as the notch stress approach. Additionally, the fatigue prone hot spot according to both approaches is compared for a typical offshore jacket double-K-joint to emphasize the significance of the presented outcomes for the existing offshore structures. 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.
The development within the offshore wind 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 bottom fixed support structures. Besides XL-monopiles, the market developed an innovative and economic jacket support structure which is based on automatically manufactured tubular joints combined with standardized pipes. Besides the improvements for a serial manufacturing process the automatically welded tubular joints show a great potential in terms of fatigue resistance e.g. due to a smooth weld geometry without sharp notches. However, these benefits are not considered yet within the fatigue design process of automatically manufactured jacket substructures according to current standards due to the lack of suitable S-N curves. Therefore, 32 axial fatigue tests on single and double-sided automatically welded tubular X-joints have been performed to determine a new hot spot stress related S-N curve. Based on these constant amplitude fatigue tests a new S-N curve equal to a FAT 126 curve was computed which implicitly includes the benefits of the automatically welding procedure.
Grain refinement is an important possibility to enhance the mechanical properties such as strength, ductility and toughness of aluminium weld metal. In this study, grain refinement was achieved through the addition of commercial grain refiner Al Ti5B1 to gas tungsten arc weld metal of the aluminium alloys 1050A (Al 99.5) and 5083 (Al Mg4.5Mn0.7). The grain refiner additions led to a significant reduction of the weld metal mean grain size (Alloy 1050A, 86 %; Alloy 5083, 44 %) with a change in grain shape from columnar to equiaxed. Tensile tests showed for Alloy 5083 that the weld metal's ductility can be increased through grain refinement. No improvement in weld metal strength (i.e. yield strength and ultimate tensile strength) was observed. Furthermore, tear tests with notched specimens revealed that the resistance against initiation and propagation of cracks in the weld metal can be enhanced through grain refinement. The toughness was observed to increase clearly by grain refinement in weld metal of commercial pure Al (Alloy 1050A). In Alloy 5083 weld metal, the toughness was not improved through grain refinement, likely because of a semi-continuous network of brittle intermetallic phases that facilitate crack propagation.
Influence of solute content and solidification parameters on grain refinement of aluminum weld metal
(2013)
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.
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.