Metallurgical Fields Research Articles

Optimization of the horizontal overlap step of AWS A5.9 ER385 (904L) weld overlay deposited by MIG-VP

The application of coating by electric arc processes is widely used in the oil and gas, offshore, and large-scale metallurgical fields for the recovery of components and surface protection against corrosive and abrasive atmospheric environments. Cost and process efficiency are important indicators in large-scale industrial applications, along with ensuring quality in coating deposition. Mechanical and metallurgical properties, as well as morphological characteristics, depend not only on welding parameters but also on correct overlap between them. Studies aimed at investigating input variables to achieve optimized horizontal overlap between layers are increasingly common in the literature, as the search for an efficient process with better cost-effectiveness, less material waste, and that meets minimum regulatory quality requirements is extremely important. Therefore, this study aims to quantitatively investigate the minimum percentage value of bead width for horizontal overlap of coatings deposited via electric arc. To this end, a Box-Behnken design of experiment and optimization via the "desirability" method for a single bead was conducted, followed by a study of the ideal degree of overlap for theoretical overlaps of 5%, 15%, 25%, and 35% of the optimized bead width. The results showed that it is possible to achieve an overlap of approximately 23% of the optimized bead width at the minimum levels of welding speed and weaving amplitude, with maximum weaving frequency within the design experiment limits, leading to lower discard area values, with a total average dilution of the overlapped layers of 7.2%. The average experimental error regarding the total width of the overlapped beads, for theoretical and experimentally obtained overlap values, was approximately 3%.

The fracture toughness and tribological performance of NiAl/Al2O3-40 Wt.% TiO2 coating generated by air plasma spraying

Aluminum titanate ceramic coating materials have great a potential application in the mechanical and metallurgical fields. Al2O3-40 wt%TiO2(AT40) is one of the most substantial ceramic materials, which is extensively used for thermal barrier coating due to its combination of excellent properties like high wear and corrosion resistance, high ductility, and density as well as a good deal of durability against fatigue. However, AT40 ceramic coating still faces some poor mechanical properties, such as low fracture toughness, combined with high hardness and brittleness, which limits to achieving widespread application. The doping of metals in AT40 ceramic composite coating positively affects the mechanical properties of AT40 ceramic coating. In this study, NiAl with different concentrations was doped in AT40 by air plasma spraying (APS) to produce NiAl/Al2O3-40 wt%TiO2 composite coating, and its microstructure and mechanical properties were investigated by employing various characterization techniques. The results showed that a 20 wt% NiAl concentration in AT40 coating improved fracture toughness, strengthened bonding, and reduced 80–85% in crack propagation and porosity in the composite coating. Additionally, the 20 wt% NiAl coating displayed an excellent wear resistance, lower energy release rate, and lower micro hardness, compared to 0 wt% NiAl/AT40 coating.

Kinetics and mechanism for efficient Co(II) removal from zinc sulfate solution by ultrasonic-enhanced zinc powder replacement

The purification of zinc sulfate electrolytes in zinc hydrometallurgy has always been a vexing problem. The aggregation of zinc powder and the removal of recalcitrant Co(II) are the most challenging. Here, we propose a new method for removing Co(II) from a zinc sulfate solution using ultrasonic-enhanced zinc powder replacement. The parameters affecting Co(II) removal are investigated to obtain the optimum conditions. The Co(II) removal efficiency increases remarkably by 26.6% and the required amount of zinc powder was correspondingly reduced by 50% after introducing ultrasound and activators. The optimal dosage of activators Sb2O3 and Cu(II) is CCu(II): CSb(III): CCo(II) = 2: 1: 1. Moreover, the addition of Cu(II) does not deteriorate the quality of zinc sulfate solution because of its low residual concentration (0.84 mg/L). The removal kinetics show that the activation energy of Co-precipitation decreases by 32.27 kJ/mol, and the conversion range of the kinetic mechanism is increased to CCo(II),0 = 60–80 mg/L. The particle diameter of the purified slags decreases from 136.22 to 19.81 µm compared with that of conventional experiments. The cobalt removal mechanism mainly involves that ultrasound promotes the dispersion of zinc powder, opens the package and reduces the activation energy; the Co-Sb-Cu alloys reduce the Co-precipitation overpotential and inhibit the redissolution of Co. The proposed method presents a promising solution to the challenging problem of Co(II) removal. This study opens new possibilities for the application of ultrasound in the metallurgical fields for more efficient and energy-saving production.

System identification of excited beam immersed in granular materials: A multifrequency data-based method in a variational framework

Granules and immersed structures coupling vibration systems are common in civil, pharmaceutical, mining, and metallurgical fields. These systems present frequency-dependent physical parameters and nonlinear dynamic characteristics owing to the multiphase, cross-scaled, and highly nonlinear discrete media. The research on such coupling vibration systems has just started in recent years, mainly focusing on simulations and experiments, and the theoretical model has not been publicly reported. In order to obtain the general form of the dynamic equation of the granules and immersed beam coupling vibration systems, in this paper, the integral variational equation of the granules-beam system was first constructed based on the variational principle. A deflection curve reconstruction method was introduced to obtain the flexural function of the beam through data captured by a few strain measuring points. Furthermore, the coupling mechanism between the mass and stiffness data of the system with single-frequency responses was explained under an integral variational framework, and a multifrequency data-based method was proposed to identify the granules and immersed beam coupling vibration system. Numerical studies were conducted on the effectiveness and robustness of the proposed method, including the measurement noise and number of strain measuring points. Experimental studies on the granules and immersed beam coupling vibration system were based on dynamic strain testing techniques. The identification results further verified the feasibility of the proposed method, and the general form of the dynamic equation of the system and variations in the system parameters with excitation frequencies were obtained. The frequency-dependent characteristics generated new peak and jump phenomena, respectively, below and slightly above the first-order natural frequency of the beam.

Validated Multi-Physical Finite Element Modelling of the Spot Welding Process of the Advanced High Strength Steel DP1200HD.

Resistance spot welding (RSW) is a common joining technique in the production of car bodies in white for example, because of its high degree of automation, its short process time, and its reliability. While different steel grades and even dissimilar metals can be joined with this method, the current paper focuses on similar joints of galvanized advanced high strength steel (AHSS), namely dual phase steel with a yield strength of 1200 MPa and high ductility (DP1200HD). This material offers potential for light-weight design. The current work presents a multi-physical finite element (FE) model of the RSW process which gives insights into the local loading and material state, and which forms the basis for future investigations of the local risk of liquid metal assisted cracking and the effect of different process parameters on this risk. The model covers the evolution of the electrical, thermal, mechanical, and metallurgical fields during the complete spot welding process. Phase transformations like base material to austenite and further to steel melt during heating and all relevant transformations while cooling are considered. The model was fully parametrized based on lab scale material testing, accompanying model-based parameter determination, and literature data, and was validated against a large variety of optically inspected burst opened spot welds and micrographs of the welds.

Prototype Network for Text Entity Relationship Recognition in Metallurgical Field Based on Integrated Multi-class Loss Functions

It is of great significance to recognize the metallurgical entity relations in order to construct the Knowledge graph of Metallurgical Literature and to further understand the metallurgical literature. However, there are few researches on the textual entity relations in metallurgical fields either few marked Corpora. The syntactic structure of the same entity relationship category is relatively simple and has strong domain characteristics. The traditional entity relationship model can not identify the domain entity relationship well. Meanwhile the syntactic structure of the same entity relations class is relatively simple, and the syntactic structure is relatively simple in the recognition of entity relations in metallurgy field. Furthermore, the entities with similar syntactic structure often have the same entity relations and the different words in the sentence have different contribution to the entity relations. In order to solve the mentioned problems, this paper will combine the algorithm that can highlight the syntactic structure in sentences and improve the accuracy of the model with the Algorithm that can highlight the contribution of words in sentences and the loss function level integration is carried out in the framework of small sample prototype network, so as to maximize the advantages of each algorithm and improve the accuracy –firstly, in the coding layer of the prototype network, we use the CNN algorithm which can highlight the important words in the sentences and the TreeLSTM algorithm which can parse the sentences in the text so that the syntactic relations between the words in the sentences can be acted on in the relation recognition, the sentences are coded together by two algorithms, then, the EUCLIDEAN distance loss is calculated by using this high quality coding and the prototype coding, finally, the traditional entity relation recognition model with Attention Mechanism is integrated into the loss function, further highlighting the decisive role of important words in text sentences in relation recognition and improving the generalization of the model. The results showed that compared with the traditional methods such as CNN, RNN, PCNN and Bi-LSTM, the proposed method in this paper has better performance in the case of small sample data set.

FEM modeling and experimental validation of quench-induced distortions of large size steel forgings

Abstract Industrial-level water quenching operations generally lead to high residual stresses and distortion, especially for large steel parts, due to the high temperature gradient present. In this work, a 3D Finite Element (FE) model was used to simulate the water quenching process of a large size forged block made of high-strength steel in a bid to predict the induced distortion and residual stresses. The FE model considers the coupling between the thermal, mechanical and metallurgical fields and in addition to that the mechanical properties related to each phase at different temperatures were experimentally generated to feed the FE model with reliable material data. Furthermore, an experimental approach was designed to accurately measure the shape change after quenching. The results indicated that the FE model was able to predict the pattern of the distortion induced by the quench process. Also, the value of the maximum magnitude of thickness reduction was predicted at the center region of the block with a deviation of 0.5 mm.

Temperature and strain response of in-fiber air-cavity Fabry-Perot interferometer under extreme temperature condition

In this work, a simple fiber Fabry-Perot air-cavity interferometer (FPI) is formed by splicing a 246 μm long hollow core silica tube (HCST) between two single mode fibers (SMFs). In the thermal characterization test, the FPI exhibits limited linear range up to 700 °C in the first cycle of isochronal annealing treatment from room temperature up to 1000 °C. However, after a series of repeated isochronal thermal annealing, the temperature response of the proposed FPI is extended further to 1000 °C with a good thermal repeatability. Meanwhile, the annealed FPI has linear axial strain sensitivities up to 1000 με from room temperature up to 800 °C. The proposed fiber structure is a potential sensor for high-temperature or stress measurement in aeronautical or metallurgical fields.

A parallel multi-fidelity optimization approach in induction hardening

Purpose Reliable modeling of induction hardening requires a multi-physical approach, which makes it time-consuming. In designing an induction hardening system, combining such model with an optimization technique allows managing a high number of design variables. However, this could lead to a tremendous overall computational cost. This paper aims to reduce the computational time of an optimal design problem by making use of multi-fidelity modeling and parallel computing. Design/methodology/approach In the multi-fidelity framework, the “high-fidelity” model couples the electromagnetic, thermal and metallurgical fields. It predicts the phase transformations during both the heating and cooling stages. The “low-fidelity” model is instead limited to the heating step. Its inaccuracy is counterbalanced by its cheapness, which makes it suitable for exploring the design space in optimization. Then, the use of co-Kriging allows merging information from different fidelity models and predicting good design candidates. Field evaluations of both models occur in parallel. Findings In the design of an induction heating system, the synergy between the “high-fidelity” and “low-fidelity” model, together with use of surrogates and parallel computing could reduce up to one order of magnitude the overall computational cost. Practical implications On one hand, multi-physical modeling of induction hardening implies a better understanding of the process, resulting in further potential process improvements. On the other hand, the optimization technique could be applied to many other computationally intensive real-life problems. Originality/value This paper highlights how parallel multi-fidelity optimization could be used in designing an induction hardening system.

Analysis of the Informative Data of Industrial Data-Based Modelling

Modelling plays an important role in continuously operated plants as in chemical, metallurgical and aerospace fields, directly affecting subsequent researches of industrial processes. Rapid industrial development requires a high-quality model. Generally, external excitation is applied to the industrial process, ensuring the informative data for system identification. However, these processes are regularly operated to achieve a secure operation and to meet production objectives. For the safety and avoid violating product quality, external excitation can be forbidden or limited in the plant. Historical records are logged, which is natural to use them for analysis. These data are available at less, even no cost for identification. In this paper, based on the definition of information matrix and attenuating excitation, a detailed standard is aimed to propose to help extract informative data with respect to the chosen model structure to support system identification. The assessment of this standard is evaluated in a case, and the benefits are demonstrated, which ensures identification information enough, decreases information waste and achieves less, even no impact or cost of industrial processes.

A more efficient method for calibrating discrete element method parameters for simulations of metallic powder used in additive manufacturing

Laser powder bed fusion (LPBF) is an additive manufacturing (AM) process that uses a high-power laser to selectively melt metal powder that has been spread, layer-by-layer, to create parts with highly complex features. Because of the strong influence that the powder spreading process has on the final part quality, a better understanding of the powder behavior and its interactions with existing powder layers and the solidified surfaces during this process is needed. Discrete element method simulations (DEM) provide a particle-scale approach capable of examining these mechanisms. While proper calibration of these simulations provides confidence in the quantitative results, the usual calibration process (hopper method) is computationally time intensive. Because of the wide variety of powder material used in LPBF, which will affect the powder spreading process, and because of the large numbers of particles present in only a small volume of powder, a more efficient calibration process was necessary. Use of a new cloud method was shown to make calibrations more tractable and reduce simulation times by up to 89% when compared to a typical hopper method. Similar to previous studies shown in the literature, a reduction in the particle material’s Young’s modulus was also used to reduce simulation times by up to 62%. Both sliding and rolling friction were needed for the DEM angles of repose to match the empirical data because of the non-sphericity of some of the powder particles, which has been quantified. The calibrated parameters resulted in determination of a powder density within 10% and an angle of repose within 1% of the targeted experimental values. These parameters will be used in extensive future DEM simulations of the LPBF powder spreading process. While AM processes were the main motivation for this work, the calibration procedures summarized herein can be extended to other gas-atomized powders used in injection molding and other metallurgical fields, as well as many other granular materials.

Preliminary Study on Impact of Disruptive Technologies in Chemical, Metallurgical, and Material Fields

Preliminary Study on Impact of Disruptive Technologies in Chemical, Metallurgical, and Material Fields

Numerical simulation of resistance spot welding of Al to zinc-coated steel with improved representation of contact interactions

The resistance spot welding (RSW) process involves electrical, thermal, mechanical and metallurgical fields and contact interactions across faying interfaces. The contact interactions include mechanical, electrical and thermal contacts where the electrical and thermal conduction across the faying interface are affected strongly by the mechanical contact pressure and temperature at the interface in addition to material composition and surface conditions. However, representation of the contact interactions is often simplified with no or limited consideration of a combination of above-mentioned effects in state-of-the-art numerical simulation models due to extremely limited availability of electrical and thermal contact resistance data at various pressures and temperatures. As a result, existing numerical models, mainly to simulate the process of dissimilar RSW process like Al to steel, often have difficulties in accurately capturing the dynamic voltage response, especially during the initial stage when the contact interactions start to engage with rapid changes in interfacial temperature and pressure and in predicting progress of nugget growth and joint deformation all through the welding stage. In this study, we present an improved representation of both electrical contact resistance (ECR) and thermal contact resistance (TCR) in Al to zinc-coated steel RSW process. The calculation of ECR is based on analytical formulations and referencing experimentally measured contact resistance curves from existing literature, with multiple effects of interfacial temperature, contact pressure, zinc coating and Al oxide involved. The corresponding TCRs are obtained from the ECRs according to the Wiedemann–Franz Law for consistency. The model with the improved ECR and TCR representations is established in ANSYS, sequentially coupling mechanical field and electro-thermal field, and it is used to simulate a benchmark Al to zinc-coated steel RSW process using rounded-tip electrode where ECR and TCR are both critical respectively due to important heat generation by electrical contact resistance at preheat stage and significant imbalance of heat generation by Al sheet and steel sheet. Eventually, the simulation results provide a significantly improved prediction of the voltage response and weld profile compared to a conventional approach. It accurately captures the bulging of the steel sheet into the aluminum sheet, which was missed by previous work. The improved model is further used to study nugget development, heat generation and re-distribution and nuggets development during the whole RSW process. Finally, the temperature history at the Al–steel interface obtained from the model is used to predict intermetallic compound (IMC) growth and it accurately captures the bimodal profile of IMC thickness distribution along the Al–steel interface. Findings from the above-mentioned discussions are summarized and can be used to guide future welding schedule development or electrode geometry design for the RSW of Al to steel.

The nature of Schwertmannite and Jarosite mediated by two strains of Acidithiobacillus ferrooxidans with different ferrous oxidation ability

Jarosite and Schwertmannite are iron-oxyhydroxysulfate materials. These materials gain increasing interest in geological and metallurgical fields. Especially, for it can effectively scavenge heavy metals, less toxic ions and better biocompatibility, the application potential in environment becomes more and more intriguing. In this study, the nature of Jarosite and Schwertmannite mediates synthesized by two strains of Acidithiobacillus ferrooxidans with different ferrous oxidation ability is investigated. The precipitates are characterized by SEM, XRD, FTIR, and TG/DSC analysis. The materials are varied in color, shape, surface area, elemental composition and crystallinity. The crystallinity of precipitate produced by A. ferrooxidans 23270 with lower oxidation ability in optimized medium is significantly better than the precipitate produced by A. ferrooxidans Gf. A. ferrooxidans Gf will tend to mediate the formation of Schwertmannite with the decreasing of monovalent cation concentration in optimized medium. Cr(VI) adsorption capacity difference exists among the four materials. The adsorption efficiency of Schwertmannite is higher than Jarosite. Adsorption capacity of the materials formed by A. ferrooxidans Gf is higher than that of A. ferrooxidans 23270. Adsorption capacity decreases with the increasing of crystallinity.

OS0403 高温割れに関する力学モデルの構築(OS4-1 シミュレーション技術,OS-4 溶接変形・残留応力の計測技術,シミュレーション技術)

It is an important subject to clarify the mechanism of welding crack formation to eliminate that in weld in structures. There are many studies in metallurgical fields about hot cracking. But it requires consideration of mechanical factors as well as metallurgical factors to control hot cracking, because mechanical factors such as heat input and constraint influence hot cracking freguently. In this study, mechanical models are suggested to control hot cracking and the results calculated by proposed method are compared with those by finite element method. This model is also applied to pipe joints and the applicability of the proposed method is performed.

Role of Alloying Additions in Glass Formation and Properties of Bulk Metallic Glasses.

Alloying addition, as a means of improving mechanical properties and saving on costs of materials, has been applied to a broad range of uses and products in the metallurgical fields. In the field of bulk metallic glasses (BMGs), alloying additions have also proven to play effective and important roles in promoting glass formation, enhancing thermal stability and improving plasticity of the materials. Here, we review the work on the role of alloying additions in glass formation and performance improvement of BMGs, with focus on our recent results of alloying additions in Pd-based BMGs.

E-Government Implications on Project Management in the Metallurgical Fields

This paper presents an overview on e-Government implications on the project management in the metallurgical fields. There are three purposes of this paper. The first purpose is to define the e-Government context related with the European Union documents. Second, this paper illustrates how project management specificities in the metallurgical fields determine a feedback in the e-Government systems and components. Third, to specify as conclusions the ways to obtain this e-Government-metallurgical project mixing.

Hydrogen Transport in a Coupled Elastoplastic-Diffusion Analysis near a Blunting Crack Tip

The role of hydrogen in hydrogen embrittlement, stress corrosion cracking and hydrogen induced cracking has been largely determined. The hydrogen cracking problem in metallurgical fields has been studied for many years. In spite of that, it is still not possible to explain exactly how the presence of hydrogen within the metal structure leads to hydrogen embrittlement and crack formation. Hydrogen-enhanced localized plasticity (HELP) is an acceptable mechanism of hydrogen embrittlement and hydrogen-induced cracking in materials. In the present work, a finite element analysis is implemented to estimate the large deformation elasto-plastic behavior of the material in conjunction with the hydrogen diffusion analysis results. Hydrogen is highly mobile and can diffuse through the crystal lattice dissolving into its interstitial sites. It is necessary to assume the model which can describe the hydrogen diffusivity near the blunting crack tip as well as the large deformation phenomena. Finite element analysis is here employed to solve the coupled boundary-value problem of large strain elasto-plasticity and equilibrium hydrogen distributions ahead of a blunting crack tip by taking into consideration the effect of hydrogen on local flow stress.

Single-molecule studies of DNA by molecular combing

Bulk metallic glasses (BMGs) are of current interest worldwide in materials science and engineering because of their unique properties. Exploring BMGs materials becomes one of the hottest topics in the materials science field. To date, there is very active worldwide development of new BMGs, and extensive efforts have been carried out to understand and improve the glass-forming ability of metallic materials supported by large government and industry programs in North America, Asia, and Europe. Minor addition or microalloying technique, which has been widely used in other metallurgical fields, plays effective and important roles in formation, crystallization, thermal stability and property improvement of BMGs. This simple approach provides a powerful tool for the BMG-forming alloys development and design. In this paper, we present a comprehensive review of the history and the recent developments of this technique in the field of BMGs. The roles of the minor addition in the formation and the properties of the BMGs and the BMG-based composites will be discussed and summarized within the framework of thermodynamics, kinetics and microstructure. The empirical criteria, or the principles and guidelines for the applications of the technique in BMG field are outlined. (c) 2006 Elsevier Ltd. All rights reserved.

Using confocal scanning laser microscopy for the in situ study of high-temperature behaviour of complex ceramic materials

The confocal scanning laser microscopy (CSLM) technique has been successful in many metallurgical fields. This paper assesses its applicability to the in situ investigation of the high-temperature behaviour of complex ceramic materials. Magnesia–chromite refractory is selected as a ceramic test material. At room temperature, CSLM images correspond well to typical light optical microscopy (LOM) and backscattered electron (BSE) micrographs. In fact, because of the high axial resolution (short focal depth) and the confocal optics of the CSLM technique, the porosity level of the mirror polished ceramic specimens is more truthfully assessed by the CSLM (2-D) images than by the BSE micrographs (long focal depth). However, at high-temperatures (1550–1650 °C) the observed CSLM (2-D) image quality is slightly poorer. The principal explanation is the in situ roughening of the specimen surface during heating. The roughening has two causes: differential thermal expansion of the two primary phases in the ceramic test material and, to a lesser extent, thermal grooving. Nevertheless, it is shown that the CSLM image quality suffices for an in situ study of the high-temperature behaviour of ceramic materials. This is illustrated for the magnesia–chromite system by examining the dissolution mechanism of secondary (magnesiochromite) spinel into the periclase phase.