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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.
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.
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 must 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. Additionally, a methodology for the computation of the notch radius as well as the weld seam angle is presented based on the scanned profiles of three analysis points of an automated manufactured tubular X-joint. Subsequently, these parameters are considered within the notch stress approach based fatigue design and their impact is quantified by a comparison with the structural stress approach using equivalent stress concentration factors.
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.
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.
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.
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.
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.
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%.
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.