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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.
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 flexibility and quality of a process. Typically, before producing a whole additive manufacturing structure, a simplified experiment in the form of a beadon-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 developed, 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 temperature.
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.
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.
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.
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.
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.
Wire arc additive manufacturing enables the production of near-net shape large-volume metallic components leveraging an established industrial base of welding and cladding technology and adapting it for layer-wise material deposition. However, the complex relationship between the process parameters and resulting mechanical properties of the components still remains challenging. In case of high-strength Al-Mg-Si aluminum alloys, no commercial filler wires are yet available due the high susceptibility of solidification cracking as well as the necessary efforts to obtain acceptable mechanical properties. To address this need, we evaluated a novel filler wire based on AlMg0.7Si doped with a Ti5B1 master alloy to foster fine equiaxed grains within the deposited metal. The correlation between the process parameters and component quality was examined by analyzing the size and distribution of pores as well as the grain morphology. Furthermore, we evaluated the influence of different post-weld heat treatment strategies to achieve mechanical properties corresponding to the reference wrought material. We demonstrated that fine equiaxed grains in the weld metal reduced the susceptibility of solidification cracking significantly. The novel AlMg0.7Si-TiB (S Al 6063-TiB) filler wire facilitated wire arc additive manufacturing of high-strength aluminum components with mechanical properties that were almost as superior as the corresponding wrought base material.
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.
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 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 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.
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.
This study examines the relationship between the magnetic mesostructure with the microstructure of low carbon steel tungsten inert gas welds. Optical microscopy revealed variation in the microstructure of the parent material, in the heat affected and fusion zones, correlating with distinctive changes in the local magnetic stray fields measured with high spatial resolution giant magneto resistance sensors. In the vicinity of the heat affected zone high residual stresses were found using neutron diffraction.
Notably, the gradients of von Mises stress and triaxial magnetic stray field modulus follow the same tendency transverse to the weld. In contrast, micro-X-ray fluorescence characterization indicated that local changes in element composition had no independent effect on magnetic stray fields.
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.
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.
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.
Evaluating innovative process technologies has become highly important within the last decades. As standard tools different Life Cycle Assessment methods have been established, which are continuously improved. While those are designed for evaluating single processes they run into difficulties when it comes to assessing environmental impacts of process innovations at macroeconomic level. In this paper we develop a multi-step evaluation framework building on multi regional inputeoutput data that allows estimating macroeconomic impacts of new process technologies, considering the network characteristics of the global economy.
Our procedure is as follows: i) we measure differences in material usage of process alternatives, ii) we identify where the standard processes are located within economic networks and virtually replace those by innovative process technologies, iii) we account for changes within economic systems and evaluate impacts on emissions.
Within this paper we exemplarily apply the methodology to two recently developed innovative technologies: longitudinal large diameter steel pipe welding and turning of high-temperature resistant materials. While we find the macroeconomic impacts of very specific process innovations to be small, its conclusions can significantly differ from traditional process based approaches. Furthermore, information gained from the methodology provides relevant additional insights for decision makers extending the picture gained from traditional process life cycle assessment.
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.
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%.
Single-wire gas metal arc welding (SGMAW) and high power tandem GMAW (TGMAW) are evaluated with respect to energy efficiency. The key performance indicator electrical deposition efficiency is applied to reflect the energy efficiency of GMAW in different material transfer modes. Additionally, the wall-plug efficiency of the equipment is determined in order to identify the overall energy consumption. The results show that energy efficiency can be increased by 24% and welding time is reduced over 50% by application of the tandem processes. A comparative life cycle assessment of a 30-mm-thick weld is conducted to investigate the influences of the energy efficiency on the environmental impacts. The environmental impacts on the categories global warming potential, acidification potential, eutrophication potential, and photochemical ozone creation potential can be reduced up to 11% using an energy-efficient TGMAW process.
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.
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.
The residual stress distribution of tungsten inert gas welded S235JRC+C plates was determined by means of neutron diffraction(ND). Large longitudinal residual stresses with maxima around 600 MPa were found. With these results as reference, the evaluation of residual stress with high spatial resolution GMR (giant magneto resistance) sensors was discussed. The experiments performed indicate a correlation between changes in residual stresses (ND) and the normal component of local residual magnetic stray fields (GMR). Spatial variations in the magnetic field strength perpendicular to the welds are in the order of the magnetic field of the earth.
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.
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.
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.
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.
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.
Increasing performance and energy efficiency of Gas Metal Arc Welding by a high power tandem process
(2016)
Standard Gas Metal Arc Welding (Standard GMAW) and a high power Tandem GMAW (TGMAW) process are evaluated with respect to energy efficiency. Current, voltage and overall equipment power are measured and energy consumption is determined. The new key performance indicator Electrical Deposition Efficiency is introduced to reflect the energy efficiency of GMAW processes. Additionally, wallplug efficiency of the equipment is determined in order to identify the overall energy consumption. Results show that energy efficiency as well as economic process performance can be significantly increased by application of the TGMAW process. Furthermore findings indicate that wall-plug efficiency of the equipment is independent of power level and material transfer mode. A metal plate of 30 mm thick structural steel is joined by Standard GMAW and TGMAW to demonstrate the total energy savings for a real weld. Electricity consumption is reduced by more than 20 % using the high power TGMAW process.
Selecting a welding process for a given application is crucial with respect to the sustainability of part manufacturing. Unfortunately, since welding processes are evaluated by a number of criteria, preferences for one or the other process can be contradictory. However, the prevalent procedure of weight assignment for each criterion is subjective and does not provide information about the entire solution space. From the perspective of a decision maker it is important to be able to assess the entire set of possible weightings and answer the question which welding process is optimal for which set of weights. This issue is investigated by means of a weight space partitioning approach. Two welding processes are considered with respect to three criteria that reflect their economic and environmental performance. In order to find the most sustainable welding process the underlying weight space partition is evaluated.