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Article

Thermodynamic Simulation of O Content Variation Roadmap in Submerged Arc Welding Process: From Droplet to Weld Metal

by
Jin Zhang
1,2 and
Dan Zhang
3,*
1
School of Mechanical and Electrical Engineering, Suqian University, Suqian 223800, China
2
School of Metallurgy, Northeastern University, Shenyang 110819, China
3
Department of Science and Technology, Suqian University, Suqian 223800, China
*
Author to whom correspondence should be addressed.
Processes 2023, 11(3), 784; https://0-doi-org.brum.beds.ac.uk/10.3390/pr11030784
Submission received: 7 December 2022 / Revised: 27 January 2023 / Accepted: 2 March 2023 / Published: 6 March 2023
(This article belongs to the Section Manufacturing Processes and Systems)
Browse Figures
Versions Notes

Abstract

:
Submerged arc welding is a complex metallurgical system involving various phases with a temperature higher than 2000 °C. Since the hot weld pool is shielded beneath the flux, thermodynamic investigation on the O content variation during the welding process remains nebulous. Within this framework, a thermodynamic approach has been proposed to estimate the variation tendency of O content in metal during the overall submerged arc welding process. The modeling is based on the assumptions of Oxygen Layer Theory, Local Attained Equilibrium, and Scheil Solidification. The simulated and measured data show that this approach is capable of predicting the variation of the O content roadmap when typical CaO–Al2O3 based fluxes are employed. Then, factors pertinent to the level of O content are evaluated from thermodynamic perspectives. Additionally, it is revealed that the decomposition mechanisms of the oxides in welding can be constrained via the incumbent approach.

1. Introduction

Submerged arc welding (SAW) has been widely applied for the joining of the thick plates for decades owing to the high deposition rate and excellent reliability [1]. Flux is a granular material primarily made up of oxides and CaF2 [2]. During SAW process, the arc cavity and weld pool are invisible since they are shielded under the granular flux and molten slag (flux means the granule before welding while slag means the molten or solidified flux, similarly hereinafter) [1,3,4].
Flux is an indispensable consumable for the performing of SAW. During the SAW process, the molten slag that forms during the SAW process covers the weld pool and protects it from the contamination of the atmosphere [1,3,4]. Generally, flux is employed in SAW to stabilize the arc and refine the weld pool (such as decarbonization, dephosphorization, desulphurization, etc.) [2]. SAW is a complex metallurgical system with various phases [5]. The high temperature attained in such a system induces complex chemical interactions that enable the compositional change of the weld metal (WM) [6,7,8].
Oxygen (O) is an essential element dictating the microstructure and mechanical properties of the WM [4,9,10]. Redundant O tends to incur reduced toughness and/or depreciated hardenability, whereas WM with low O levels shows poor mechanical properties, especially in terms of the toughness, since there are insufficient inclusions to promote the formation of the acicular ferrite (AF, a microstructure with interlocking nature that provides resistance to the crack propagation by cleavage) [11,12].
From the perspective of the control for the WM compositions, the O concentration in the hot metal is also an essential parameter pertinent to the transfer of alloy elements, such as Si, Mn, Ti, C, S, and P, etc. For instance, Si and Mn are basic alloy elements dictating the microstructures and mechanical properties of the weldment. Up to 0.6 wt pct, Si has little effect on the value of the toughness, but the addition level of Si higher than 0.6 wt causes an increase in the transition temperature subject to the WM [13]. Mn is a traditional moderate deoxidizer and AF promotion agent for the submerged arc welded metal. An increase in Mn level up to 1.2 wt pct results in an improvement in the toughness, whereas Mn contents higher than 1.6 wt pct tend to case a rapid deterioration in terms of the toughness [1]. The thermodynamic model developed on the possible slag-metal equilibrium revealed that Si and Mn contents are strongly dictated by the O in the WM (the flux O potential) [1]. C is another essential alloying element for WM. Increased C level improves the hardness and strength [2]. However, the addition of C at too high a level may cause severe and undesirable impacts upon the WM, including, but not limited to, reduction in the elongation, notch toughness, and weldability [2]. In comparison to other arc welding processes, a salient feature of the SAW is the significant O uptake from the flux [5]. Due to the existence of the gas-related chemical interface, the plasma-metal interface and the plasma-slag-metal interface, decarbonization is possible within the SAW process [5].
During the SAW process, oxides in flux are susceptible to decomposition, release O2, and improve the O level in the hot metal due to the presence of the arc plasma [4,13,14,15]. Generally, the flux constitutes the major source of O for the metal in the SAW process [9,10]. Therefore, an understanding of the O content variation in the SAW process is vital to properly control the mechanical properties. Typical studies concerning the subject have been performed by Lau et al. [9,16]; they measured the O content in the droplet and solidified WM and revealed that the O content undergoes a spike in the droplet and then decreases to a relatively lower level in the solidified metal [9].
In earlier trials, the flux O potential is assessed by the basicity index model [15]. In terms of the basicity index equation, the so-called basic oxides include CaO, CaF2, MgO, Na2O, K2O, MnO, and FeO, whilst the acidic oxides include SiO2, Al2O3, Cr2O3, TiO2, and ZrO2 [2]. Based upon the value of the basicity index, fluxes can be classified into three major categories, namely, the acidic flux (basicity index < 1.0), the neutral flux (1 ≤ basicity index < 1.2), and the basic flux (basicity index ≥ 1.2) [15]. Empirically, it is accepted that the flux O potential (the O content in the final submerged arc welded metal) generally decreases with an increasing basicity index value and then reaches a constant [17]. Eagar [10], on the other hand, declared that CaF2 should be removed from the basicity index equation since he assumed that CaF2 only acts as a dilutant, rather than as an active component. Based on the basicity index equation, several regression models have been developed to estimate the flux O potential and O content in the submerged arc welded metal [15]. However, some investigators concluded that there is no fundamental basis for the interconnection between flux composition, as defined by the basicity index, the flux O potential, and the mechanical properties of the weldment; recently, investigators have stated that too much emphasis has been placed upon the interconnection between the basicity index and flux O potential [1,2,9,17]. In later studies, some researchers stated that the pressure of the O2 gas should be considered as an essential parameter in the determination of the flux O potential [1,2,9,17]. In this regard, attempts were made to measure the accurate volume percent of O2 in the arc cavity; unfortunately, none of them were able to achieve success [5]. Additionally, researchers tried to sample the molten metal during the SAW process, but none of them succeeded with this issue [3].
In sum, in-depth investigation of the O content variation in the SAW process was limited in early trials because the SAW is an ultra-high temperature metallurgical system, for which the thermodynamic data is unmeasurable. Furthermore, it is impossible to obtain the molten samples for analytical purposes since the liquid slag and weld pool are submerged under the granular flux [15].
To estimate the O content in the weld pool, the first application of the Calphad technique, regarding SAW, is the development of the slag-metal equilibrium model [18]. It is noted that this model is semi-thermodynamic, since it relies on the empirical relationship between flux formulation (basicity index) and flux O potential [15]. Recently, the gas-slag-metal equilibrium calculation has been performed to provide higher prediction accuracy [15].
However, the SAW is a complex metallurgical process with O content in the metal varying at different stages, viz. the Droplet Reaction Zone, the Weld Pool Reaction Zone, and the Weld Pool Solidifying Zone [3,5,19,20]. The slag-metal and gas-slag-metal equilibrium calculations only consider the O content in the Weld Pool Reaction Zone, which is insufficient to make a comprehensive understanding of the O content variation roadmap in the overall welding process. Within this framework, a thermodynamic approach is proposed to simulate an O content variation roadmap for the SAW process when typical CaO–Al2O3 based fluxes are applied. The novelty of this study lies in the fact that:
  • The O contents in the droplet, weld pool and solidified meta have been fully considered via the Calphad technique using a reasonable scientific hypothesis of the thermodynamics in SAW.
  • Attempts are made to simulate the O content variation roadmap in the overall SAW process.
  • To clarify the scientific assumptions raised previously [16], the thermodynamic factors pertinent to the O content in metal at various stages in the SAW process are to be interpreted by analyzing the measured and simulated data.
  • To evaluate the capabilities, as well as to clarify the limitations of the models developed by the Calphad technique.
  • To identify and address issues to further improve the prediction accuracy of the models.

2. Thermodynamic Modeling

From a thermodynamic perspective, equilibrium could not be attained in the overall SAW due to large temperature gradients, the presence of different phases, and the large radiative transfer of energy from the arc plasma [2,4,21]. Despite such a departure, one may still employ equilibrium considerations to place constraints on the chemical reactions in the SAW process, on the basis that the high temperatures and surface/volume ratios, counteract the short time available for the completion of the chemical reactions [2,4,21].
In SAW engineering, a common approach is to assume that the state of thermodynamic equilibrium is attained locally [17]. Then, one can employ the knowledge of thermodynamic equilibrium to analyze the chemical behaviors in the SAW process, such as the elemental transfer behavior or compositional prediction [15]. Nonetheless, it is noted that the chemical interactions in the SAW process are also kinetically limited [2]. Therefore, the kinetic model (such as the Mitra Kinect model) helps to further improve prediction accuracy [20].
The SAW process can be divided into three zones, namely, the Droplet Reaction Zone, the Weld Pool Reaction Zone, and the Weld Pool Solidifying Zone based on the features of the chemical interactions, as shown by Figure 1 [3,20,22,23].

2.1. Droplet Reaction Zone

Within this zone, the droplet detaches from the electrode tip and then travels through the arc cavity. The temperature in this zone is in the order of 2500 °C [5]. It has been assumed that the O2 derived from the decomposition of the oxide should be responsible for the high O concentration in the droplet metal [9,10]. Preliminary experiments concluded that there is a negligible transfer of alloy elements in the Droplet Reaction Zone [20,22]. Mitra et al. [3,20,22,23] assumed that an active O layer is built up at the metal-plasma interface that prevents alloy elements from reaching the metal-plasma interface, as is exhibited in Figure 1b.

2.2. Weld Pool Reaction Zone

In this zone, large convective forces enable the mixing of the molten weld pool and slag [5,15]. The complex chemical interaction in this region leads to the transfer of elements among different phases (see Figure 1c) [24].

2.3. Weld Pool Solidifying Zone

After the electrode moves away, the weld pool starts to cool and solidify, as shown in Figure 1d [5]. The increased stability of oxides results in the formation of the inclusions inside the molten metal; these inclusions coalesce, separate from the liquid weld pool, and transfer into the molten slag [4,20,22]. According to the study of Bhadeshia et al. [25], the Scheil Cooling Model is applied to simulate the variation of O content in metal during the solidification process.

2.4. Data Source and Simulation Tools

2.4.1. Data Source

The measured data in the study of Lau et al. [9] will be employed to verify the validity of the models. The details and data source of the experimental procedure and measured contents for flux and metal are stated elsewhere [9]. The compositions of flux, base metal (BM), and WM are summarized in Table 1 and Table 2 [9].

2.4.2. Simulation Tools

Calphad stands for Computer Coupling of Phase Diagrams and Thermochemistry. It is a phenomenological technique for calculating/predicting thermodynamic properties of multi-component systems [26] and is developed from binary and ternary systems. Using extrapolated base data regarding binary and ternary systems, Calphad predicts the properties of the systems with higher order, via applicable thermodynamic models [26]. Recently, the Calphad technique has been successfully applied in the fields of design for engineering materials [27]. Although the temperature of the chemical reactions in SAW is higher than 2000 °C, applying thermodynamic models (such as the Modified Quasichemical model, Associate model, and Cell model, etc.) in the Calphad technique have paved a reliable way to obtain thermodynamic data at higher temperatures [27]. For instance, the gas–slag–metal equilibrium model has been developed via the Calphad technique in previous studies to predict the compositions in the submerged arc welded metal processed by various fluxes [1,4,19].
Factsage (version 7.3, CRCT, Montreal, Canada and GTT, Aachen, Germany) will be applied in this study to perform the thermodynamic modeling. Factsage is a typical thermodynamic software developed on the Calphad technique [28,29]. Factsage runs on a PC and consists of a series of calculation and manipulation modules that access various pure substances and solution databases [27].
The Equilib module in FactSage software was employed to simulate the O content in each stage of SAW, based on the assumed local attained equilibrium mentioned previously [26,29]. The Equilib module is the Gibbs energy minimization module of FactSage. The module calculates the concentrations of chemical species when elements or compounds reach a state of chemical equilibrium [26,29]. For the present thermodynamic modeling, the input stream comprises the flux, electrode, and BM, while the output stream comprises the concentrations of the phases of gas (plasma), metal, and slag [26,29].
FactPS, Fstel, and FToxide (CRCT, Montreal, Canada and GTT, Aachen, Germany) have been widely applied in terms of thermodynamic simulation for steelmaking or welding [15]. Within the present framework, these databases are poised to be employed to simulate the O content in the zones of the droplet (the zone with a higher temperature than that of the weld pool zone), and the solidification subject of the SAW process.
FactPS stands for the FactSage pure substances database. Fstel stands for the FactSage steel database containing data for alloy systems. FToxide stands for FactSage oxide database and contains data for all pure oxides and oxide solutions (solid and liquid) [27]. In this study, Fstel is used to model the steel phase, FactPS is used to model gas phases, and FToxide is used to model the flux/slag phase [26,29]. The scientific assumptions, as well as the database to be employed, are shown in Figure 2.

3. Simulation and Discussion

3.1. Droplet Zone

It has been concluded that the decomposition of oxide in the arc cavity should be considered as the major source of O uptake for the metal (droplet) in the Droplet Reaction Zone [9,10,11]. Considering the possible attained equilibrium at the plasma–metal interface locally, the model is developed to predict the O content in the droplet [15,28]. The level of equilibrium PO2 is calculated by the equilibrium model, during which the temperature of 2500 °C is set according to the physical phenomena in SAW [1,15,19,30].
The Equilib module of FactSage is applied to perform the modeling. The details subject to the modeling process are as follows [1,15,19,30]:
  • FToxid, Fstel, and FactPS databases were selected. Solution phases of ASlag-liq all oxides, S (FToxid-SLAGA), and LIQUID (FStel-Liqu) were selected to model the molten slag and steel phases.
  • The equilibrium temperature in SAW was set at 2500 °C (temperature of the arc plasma).
  • Nominal compositions (the contents considering only the dilution effects of the BM and electrode) [21,31] were used as the input metal chemistries (if the dilution value is not given, it may be assumed to be 0.5) [18]. The output regarding PO2 is given in Table 3.
  • Based on the Oxygen Layer Theory, the equilibrium calculation with Fe and O as input metal components were performed to simulate the O concentration in the droplet since the transfer of alloying elements is hindered by the oxygen layer.
  • The simulated PO2 data in Table 3 was set during the equilibrium calculation. The output of simulated O content in the droplet is given in Table 3.

3.2. Weld Pool Reaction and Solidifying Zones

Following the computational process in previous studies, the O content in the WM is simulated [1,13,15,19].
The details subject to the modeling process are as follows [1,13,19]:
  • FToxid, Fstel, and FactPS databases were selected. Solution phases of ASlag-liq all oxides, S (FToxid-SLAGA), and LIQUID (FStel-Liqu) were selected to simulate the molten slag and steel.
  • The equilibrium temperature in SAW was set at 2000 °C (the assumed gas–slag–metal equilibrium temperature).
  • Nominal compositions [21,31] were used as the input metal chemistries.
  • Scheil Cooling Model was applied to simulate O content in WM during the solidifying process with FSstel-Liqu as the target phase [27].
  • The output of the model of O content, coupled with the measured one, is given in Table 4.

3.3. Evaluation of O Content Variation

The investigation regarding the physical and chemical phenomena, especially in terms of the control mechanisms regarding O content variation, is restrained because [4,15]:
  • It is impossible to determine the gas compositions in the arc cavity since it is shielded under the granular flux and molten slag.
  • Since the molten slag and weld pool are shielded under the granular flux, it is impossible to sample the molten slag or hot metal at a high-temperature state during welding.
The variation of the O content in metal has been plotted in Figure 3 (Tip indicates the original electrode). It is seen that the proposed approach can predict the O content variation roadmap, the O content undergoing a spike at the Droplet Zone and then decrease.
Although some empirical-based models, such as the flux basicity index and regression models have been developed, none of these reflects the thermodynamic interconnection between the flux formula and O potential properly [17,32,33,34].
To investigate the thermodynamic factors dictating the level of flux O potential, Chai et al. [11] designed CaF2-based binary fluxes and measured the O content in the WM; it was revealed that even stable oxides tend to decompose, release O2, and improve the O content in the metal. Lau et al. [9,16] postulated that the flux decomposition level should be considered as the major source of O in submerged arc welded metal. Indacochea et al. [21] assumed that the level of equilibrium PO2 in the arc plasma controlled the extent to which the flux could chemically improve the level of flux O potential. To clarify the assumptions above, equilibrium PO2 is plotted against measured O content in Figure 4.
As is seen from Figure 4, the level of equilibrium PO2 generally increases with the higher O content in the metal subject to both Droplet and Weld Pool Reaction Zones [21].
However, the simulated O content is lower than the measured data in both Droplet and Weld Pool Reaction Zones, as shown in Table 4. It is noted that the thermodynamic models only considered the chemical interactions in the SAW process.
As was concluded by Lau et al. [9,16] and Davis et al. [35], the physical factors, especially the oxide entrapment, must be considered as one of the sources of O in metal; the experimental evidence indicates that the compositions of some oxides in the metal are essentially analogous to those in the flux [9,16,35]. Therefore, although the thermodynamic models can predict the variation trends of O content, the overall O content is underestimated because the physical contribution from flux to the O potential is not considered. Additionally, the bias between equilibrium and real states may incur the deviation between real and simulated data.
Due to the high cooling rate in SAW, it was assumed that the O content in the final WM is equal to the equilibrium O content at 2000 °C. Nonetheless, Mitra et al. [20] assumed that a slight reduction in WM O content may occur due to the redistribution of O between metal and slag. To clarify this assumption, the O content variation in WM is plotted as a function of weld pool temperature in Figure 5. This shows that the reduction of O content within this zone is predictable. However, the solidification behavior during the SAW process remains nebulous due to the limitation of detection technology [5]. Therefore, the simulated data, coupled with the assumption raised by Kou [24], demonstrate that only qualitative analysis can be made with respect to O content variation in solidifying zone via Scheil Cooling Model.

3.4. Evaluation of Gas Formation

Several thermodynamic mechanisms have been proposed to interpret the decomposition mechanisms of oxides in the flux. For instance, SiO2 and MnO tend to decompose via Reactions (1) and (2), thereby increasing the flux O potential [15]. Additionally, although it has been accepted that the decomposition of Al2O3 and MgO is feasible, the thermodynamic evidence, subject to the corresponding mechanisms is not provided [11].
( SiO 2 ) = SiO ( g ) + 1 2 O 2 ( g )
( MnO ) = Mn ( g ) + 1 2 O 2 ( g )
The simulated gas compositions in terms of Si, Mn, Al, Mg, and O have been summarized in Table 5. It is observed from Table 5 that:
  • Decomposition behaviors of SiO2 and MnO in the arc cavity can be predicted, as shown by the fugacity value of SiO, Mn, and O2 gases.
  • Lau et al. [9,16] assumed that Al2O3 would decompose and release the gases of Al, Al2O, AlO, Al2O3, and O. The information in Table 5 reveals that such a mechanism is predictable from the model, as shown by the fugacity of Al, Al2O, AlO, Al2O3, and O gases.
  • It is well-known that the evaporation of Mn tends to occur at the plasma-metal interface, during the arc welding process. It is seen from Table 5 that such evaporation behavior can be forecast, that is, significant fugacity for Mn gas is observed, even when MnO-free is employed (Flux F-2).
  • Chai et al. [11] assumed that MgO decomposition is possible due to high vapor pressure of Mg, which can be reflected by the simulated composition of Mg(g) for MgO-containing flux (Flux F-2).

4. Concluding Remarks and Further Research

Within this framework, a thermodynamic approach has been proposed to simulate the variation of O content in the metal during the SAW process when typical CaO–Al2O3 fluxes are applied. The following conclusions can be drawn:
  • By using Calphad technology, the prediction for an O content variation roadmap in the SAW process is feasible, based upon the Oxygen Layer Theory, Local Attained Equilibrium, and Scheil Solidification.
  • In both Droplet and Weld Pool Reaction Zones, the level of equilibrium PO2 plays a vital role in the control for flux O potential.
  • The gas formation, especially in terms of the oxide decomposition mechanisms at the plasma-flux(slag) interface, can be constrained via the proposed models.
However, it is noted that the O content is underestimated in comparison with the measured data. To further improve the prediction accuracy, the following issues should be addressed:
  • The physical factor, especially the entrapment of oxides should be considered.
  • The kinetic models in terms of O transfer, in the overall SAW process, are needed to compensate for the bias between equilibrium and real states.

Author Contributions

Conceptualization, J.Z. and D.Z.; methodology, software, J.Z. and D.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the National Natural Science Foundation of China (No.50474085), the Initial Fund of Suqian University (No. 2022XRC040), Suqian Science & Technology Project (No. K202239).

Conflicts of Interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

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Figure 1. Reaction zones which control the O content in metal during the SAW process. (a) Overall schematic diagram of the SAW process, (b) Droplet reaction zone, (c) Weld pool reaction zone, (d) Weld pool solidifying zone.
Figure 1. Reaction zones which control the O content in metal during the SAW process. (a) Overall schematic diagram of the SAW process, (b) Droplet reaction zone, (c) Weld pool reaction zone, (d) Weld pool solidifying zone.
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Figure 2. Scientific assumptions and thermodynamic databases employed for modeling.
Figure 2. Scientific assumptions and thermodynamic databases employed for modeling.
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Figure 3. Measured (a) and simulated (b) O content in WM [9].
Figure 3. Measured (a) and simulated (b) O content in WM [9].
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Figure 4. Equilibrium PO2 level as a function of measured O content in the metal.
Figure 4. Equilibrium PO2 level as a function of measured O content in the metal.
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Figure 5. Simulated O content as a function of temperature. (a) Flux F-1, (b) Flux F-2, (c) Flux F-3.
Figure 5. Simulated O content as a function of temperature. (a) Flux F-1, (b) Flux F-2, (c) Flux F-3.
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Table
Table 1. Compositions of fluxes (wt pct) [9].
Table 1. Compositions of fluxes (wt pct) [9].
FluxCaOAl2O3MnOSiO2MgO
F-142.332.425.300
F-237.132.0024.76.2
F-339.836.513.010.60
Table
Table 2. Compositions of base metal (BM) and electrode (wt pct) [9].
Table 2. Compositions of base metal (BM) and electrode (wt pct) [9].
CMnSiMoCrAlO
Electrode0.111.060.27--0.01-
BM0.071.790.230.140.210.020.004
Table
Table 3. Simulated equilibrium PO2 (atm.) and O content in droplet (ppm).
Table 3. Simulated equilibrium PO2 (atm.) and O content in droplet (ppm).
FluxPO2O
F-14.18 × 1007850
F-22.15 × 1007610
F-33.06 × 1007728
Table
Table 4. Measured and simulated O content (ppm) [9].
Table 4. Measured and simulated O content (ppm) [9].
FluxMeasured O Content in DropletSimulated O Content in DropletMeasured O Content in WMSimulated O Content in WM
F-12445850616481
F-2174061056582
F-32192728513267
Table
Table 5. The data concerning the simulated compositions of gases in the arc plasma (atm.).
Table 5. The data concerning the simulated compositions of gases in the arc plasma (atm.).
FluxF-1F-2F-3
Mn4.98 × 10−17.31 × 10−22.69 × 10−1
Al2.42 × 10−45.88 × 10−44.69 × 10−4
Al2O2.30 × 10−59.73 × 10−57.39 × 10−5
AlO3.12 × 10−55.44 × 10−55.18 × 10−5
O3.14 × 10−52.25 × 10−52.68 × 10−5
SiO6.90 × 10−41.53 × 10−13.53 × 10−2
Mg07.31 × 10−20
O24.18 × 10−72.15 × 10−73.06 × 10−7
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Zhang, J.; Zhang, D. Thermodynamic Simulation of O Content Variation Roadmap in Submerged Arc Welding Process: From Droplet to Weld Metal. Processes 2023, 11, 784. https://0-doi-org.brum.beds.ac.uk/10.3390/pr11030784

AMA Style

Zhang J, Zhang D. Thermodynamic Simulation of O Content Variation Roadmap in Submerged Arc Welding Process: From Droplet to Weld Metal. Processes. 2023; 11(3):784. https://0-doi-org.brum.beds.ac.uk/10.3390/pr11030784

Chicago/Turabian Style

Zhang, Jin, and Dan Zhang. 2023. "Thermodynamic Simulation of O Content Variation Roadmap in Submerged Arc Welding Process: From Droplet to Weld Metal" Processes 11, no. 3: 784. https://0-doi-org.brum.beds.ac.uk/10.3390/pr11030784

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