Slag Inclusions Research Articles

Leakage failure of a stainless steel spiral plate condenser

The condenser is an indispensable basic equipment in chemical industry. Due to the complex working conditions, leakage failure accidents often occur for condensers. In this work, the leakage failure of a spiral plate condenser made of 304 stainless steel has been investigated. The failed condenser, which had serviced for just six months, was used to condense isopropylamine by circulating frozen brine. After cutting and opening the condenser, numbers of leakage points were found occurring near the welding joints between the spacing columns and stainless steel spiral plates contacting with the frozen brine. The evidences indicate that leakage of the condenser is due to pitting corrosion caused by chloride ions near the welding joints between the spacing columns and stainless steel spiral plates. The sensitization of stainless steel in the welding zone intensifies the risk of pitting corrosion. Welding defects, including welding cracks and slag inclusions, are observed in the welding zone of the spacing columns, which might also aggravate the development of corrosion in the welding zone.

Investigating the provenance of iron bars from Les Saintes‐Maries‐de‐la‐Mer Roman shipwrecks (south‐east France) with iron isotopes

AbstractFe isotopes were used to determine the origin of iron bars from Les Saintes‐Maries‐de‐la‐Mer Roman shipwrecks, which was a major archaeological finding at the end of the 20th century in France. Their Fe isotope composition was measured by multi collector‐inductively coupled plasma‐mass spectrometry (MC‐ICP‐MS) after chemical Fe purification. The results allowed us to suggest provenances that were compared with those based on trace element analyses of slag inclusions. For most of the bars, we validate the provenance hypotheses previously proposed. Two bar groups originate from the Montagne Noire metallurgical district (south‐west France), whereas a third group comes from another source, not clearly identified so far. In this context of Roman iron production, we argue for a non‐spatially segmented production, where bars were manufactured close to smelting sites. Combined trace element and Fe isotope analyses on the same objects provide crucial information about the nature of their ore source. The elemental heterogeneity, positive Eu anomaly and Fe isotopic homogeneity of several bars were inherited from gossan‐type ores, whereas the negative Eu anomaly and variable Fe isotopes signature of others most likely correspond to sedimentary iron ores. This study demonstrates that combined trace element and Fe isotopes analyses in a well‐defined archaeological context is a promising approach for provenance studies of iron metals of archaeological interest.

Formation Mechanism and Control Strategy of Edge Seam Defects for Hot Rolling Interstitial‐Free Steel

During the process of hot rolling, seam defects often appear on the edges of the interstitial‐free (IF) steel, which seriously affects product quality and yield. To this end, the macro‐ and micromorphology of edge seam defects are analyzed, their specific characteristics are summarized, and the defect cast slab rolling experiment is conducted. The experiment shows that the pore, crack, and slag inclusion are not the causes of the seam defects. Then, through a combination of theoretical analysis, actual parameters’ detection, and experiments, the formation mechanisms of the seam defects are evidently side folding of the intermediate slab and flipping of the corner metal. The mechanisms of the two types of folds are also described in detail. Finally, in view of the mechanisms, the advantages and disadvantages of control measures are analyzed, and the concave anvil of the slab sizing press is selected at last. To determine the effectiveness of the scheme, a pass experiment is conducted on a slab sizing press at the production site. Results show that the steel coils without slab sizing press generally have seam defects, whereas the coils with a concave anvil slab sizing press do not. The defects are almost totally eliminated.

A new path planning strategy based on level set function for layered fabrication processes

In this paper, a new equidistant filling theory based on the level set function and a corresponding numerical algorithm based on the dynamic finite difference method were proposed. Firstly, a closed curve is defined as the zero-value contour of the level set function. Then, the level set equation, a partial differential equation, was built to get the level set function, and a dynamic finite difference method was proposed to solve the level set function. Secondly, three types of cross sections, simple polygon, multi-island polygon, and multi-hole polygon, were used to test the equidistant filling effect of the algorithm. The test results show that the proposed theory and algorithm in this paper solved the equidistant filling problem of these cross sections well. In addition, any complex section can be equidistant filled by the algorithm proposed. The calculation cost is significantly related to the number of the offsets, but not directly related to the section complexity. Finally, the remanufacturing of a typical crankshaft hot forging die proves that the algorithm proposed in this paper can effectively produce the remanufacturing repair path of a complex forging die. The surface of the remanufactured die is smooth, and there is no efects such as porosity and slag inclusion after machining. Compared with making a new die, the manufacturing cost can be saved more than 50%, and the efficiency of die manufacturing can be improved more than 60%. This is because the machining allowance of the die after additive manufacturing is very small, and it can be quickly repaired on site.

Basic oxygen furnace and ground granulated blast furnace slag based alkali-activated pastes: Characterization and optimization

The steel production shows tremendous increase all over the world and the enormous production of steel has subsequently led to huge amount of basic oxygen furnace (BOF) slag generation which causes several environmental issues. Previous studies generally considered the use of BOF slag as aggregate, cement replacement material, and binder in combination with metakaolin, fly ash, gold mine tailings, and ferronickel slag in alkali-activated systems. Apart from these, the present study proposes alkali-activation of BOF slag in replacement with ground granulated blast furnace slag (GGBFS) using sodium hydroxide (NaOH) as the activator. The fresh-state, mechanical, and microstructural properties of the alkali-activated paste samples were analyzed on 24 mixes. Test results showed that BOF slag ratio and the NaOH concentration modified the workability and the setting time, and their effect was remarkable for 6 M of NaOH and BOF content beyond 20%. The alkali-activated pastes containing 20 and 40% of BOF slag had comparable strength, however the strength reduced significantly upon further BOF slag inclusion. The increment of Ca(OH)2 with increased BOF slag ratio revealed by thermogravimetric analysis denotes its less consumption in the formation of C–S–H and support the decreasing compressive strength at 28 days. The X-Ray diffraction analysis revealed phases such as C–S–H and hydrotalcite due to hydration reactions. The scanning electron microscopy analysis showed that the microstructure was altered with BOF slag incorporation, and the micro-cracks were lowered compared to the reference. The optimization study showed that 25.5% of BOF slag and 6 M of NaOH provided higher compressive strength within the analyzed range, which was experimentally verified. Alkali-activation of BOF slag blended with GGBFS can be an efficient way of utilizing BOF slag to reduce its environmental impacts.

An in-process multi-feature data fusion nondestructive testing approach for wire arc additive manufacturing

PurposeThe major problem that limits the widespread use of WAAM technology is the forming quality. However, most of the current research focuses on post-process detections that are time-consuming, expensive and destructive. This paper aims to achieve the on-line detection and classification of the common defects, including hump, deposition collapse, deviation, internal pore and surface slag inclusion.Design/methodology/approachThis paper proposes an in-process multi-feature data fusion nondestructive testing method based on the temperature field of the WAAM process. A thermal imager is used to collect the temperature data of the deposition layer in real-time. Efficient processing methods are proposed in this paper, such as the temperature stack algorithm, width extraction algorithm and a classification model based on a residual neural network. Some features closely related to the forming quality were extracted, containing the profile image and width curve of the deposition layer and abnormal temperature features in longitudinal and cross-sections. These features are used to achieve the detection and classification of defects.FindingsThermal non-destructive testing is a potentially superior technology for in-process detection in the industrial field. Based on the temperature field, extracting the most relevant features of the defect information is crucial. This paper pushes current infrared (IR) monitoring methods toward real-time detection and proposes an in-process multi-feature data fusion non-destructive testing method based on the temperature field of the WAAM process.Originality/valueIn this paper, the single-layer and multi-layer WAAM samples are preset with various defects, such as hump, deposition collapse, deviation, pore and slag inclusion. A multi-feature nondestructive testing methodology is proposed to realize the in-process detection and classification of the defects. A temperature stack algorithm is proposed, which improves the detection accuracy of profile change and solves the problem of uneven temperature from arc striking to arc extinguishing. The combination of residual neural network greatly improves the accuracy and efficiency of detection.

Research on Detection Method for Welding Seam Defects in Ultrasonic TOFD Image Based on Mask R-CNN

In this paper, the technology of ultrasonic TOFD was used in the welding seam inspection of construction steel structure. 162 ultrasonic TOFD scanning images including five kinds of common defects were obtained through field test. The five kinds of common welding defects include stoma, slag inclusion, lack of fusion, incomplete penetration and crackle. Combined with artificial intelligence image recognition technology, an automatic detection algorithm of welding seam defects in ultrasonic TOFD scanning images based on Mask R-CNN was developed. By comparing the effects of automatic location and classification of welding seam defects based on Mask R-CNN after the same number of iterative training under different parameter configurations, the results show that Mask R-CNN can automatically locate and classify welding seam defects and the recognition effect is the best when epoch is 667, steps_per_epoch is 15 and learning rate is 0.001. Under this parameter configuration, the recognition and classification of five kinds of common defects such as stoma, slag inclusion, lack of fusion, incomplete penetration and crackle are correct. The correct recognition confidence of all five kinds of defects can reach more than 0.9, and the location is precise.

Dynamic mass variation and multiphase interaction among steel, slag, lining refractory and nonmetallic inclusions: Laboratory experiments and mathematical prediction

Dynamic mass variation and multiphase interaction among steel, slag, lining refractory and nonmetallic inclusions: Laboratory experiments and mathematical prediction

IDENTIFIKASI CACAT LASAN FCAW PADA FONDASI MESIN KAPAL MENGGUNAKAN METODE ULTRASONIC TESTING

Ultrasonic testing is one of the non-destructive inspection methods for welding results. The ultrasonic testing method has several advantages, namely it can be used to analyze the position of the defect in the object, both the depth of the defect and the dimensions of the defect, and it is an environmentally friendly method. Physical defects that are in solid objects of course cannot be known from direct vision so it is necessary to carry out an inspection of an object to see whether or not there are defects that occur in solid objects. Ultrasonic testing of the results of FCAW welding on the foundation of the ship's engine. FCAW welding is applied to the foundation with two types of welding positions, namely the overhead position coded P1 and the horizontal position coded P2. The test was carried out using a wave frequency of 4 MHz and using a 0° probe for analysis of defects in the area around the weld metal and a 70° probe for analysis of the weld metal. The tests were carried out using the ASME section V and ASTM E164 standards as the standard for determining defects. The test results at the P1 welding position found two types of defects, namely incomplete fusion defects with five welding points with the longest defect length of 40mm and porosity defects with two points with the longest defect length of 30mm. While the results of ultrasonic testing at the P2 welding position found two types of defects, namely slag inclusion defects with a defect length of 35mm and incomplete penetration defects with a defect length of 20 mm. The conclusion of ultrasonic testing is that the difference in welding positions is that the welding position greatly affects the quality of the welding results. The defects resulting from the welding position also vary.

Research of the Microstructure of the Deposited Layer during Electric Arc Surfacing with Control Impacts

Electric arc surfacing is widely used for the application of protective and restorative coatings on units and parts of metallurgical production equipment in order to increase their durability in harsh operating conditions and in an aggressive environment. Increasing the efficiency of melting the electrode material is an important task, since it allows one to reduce the required volume of deposited metal and the cost of surfacing. In addition, when surfacing by traditional technology of parts with a complex shape of the working surface, it was found that the deposited layer can contain such defects as single gas and line pores, as well as slag inclusions. The work is devoted to the study of improving the surfacing technology by controlling heat input into the base metal using controlled mechanical actions.

Nanoindentation-probed Oliver-Pharr half-spaces in alkali-activated slag-fly ash pastes: Multimethod identification of microelasticity and hardness

The mechanical interactions of C-(N-)A-S-H (Calcium-sodium-aluminum-silicate-hydrate) gel with slag and fly ash inclusions in alkali-activated materials (AAM) are quantified through image-supported grid nanoindentation. Nonuniform distributions of indent-specific indentation properties reveal that the elasticity-related domain is up to 130 times the contact indentation depth, while the hardness-related domain, in turn, is by a factor of two to three smaller. These rather large domains are consistent with the slag/fly-ash inclusions being much stiffer and harder than the surrounding C-(N-)A-S-H gel. Corresponding Hashin-Shtirkman bounds for the overall AAM stiffness consistently frame ultrasonic data characterizing this homogenized material scale. This confirms our new testing protocol.

Fatigue mechanism of medium-carbon steel welded joint: Competitive impacts of various defects

Fatigue of welded joint is a scientific issue of great significance, because welding process always causes the loss of fatigue strength up to 40–60% for welded joint of the key components, resulting in a relatively poor reliability in service. In the present work, the fatigue behavior and damage mechanism of a medium-carbon steel welded joint were systematically investigated by microstructure observation and fatigue tests. It was found that, for the medium-carbon steel welded joint, fatigue crack mainly initiated at the welding defects, e.g., welding porosity, slag inclusion and heterogeneous microstructure with a poor mechanical property (i.e., the network-block proeutectoid ferrite). The competitive impact of various defects on the fatigue damage behaviors of welded joint was discussed, i.e., the competition between the volume defects (e.g., porosity and inclusions) and the heterogeneous structure. It is revealed that the smaller surface defects are more susceptible to fatigue damage due to the low constraint of plane stress state and higher stress intensity factor at high stress amplitude, while the larger internal defects easily cause fatigue damage at low stress amplitude because the driving force for crack propagation is larger than that of the damage case from the sample surface. Generally, the fatigue lives of samples with fatigue crack initiating from the weak phase are relatively longer, about 10 times as long as those of the samples with fatigue crack starting from the sample surface. In addition, the residual fatigue crack growth life, Nf, and the initial stress intensity factor (SIF), ΔK1 at the volume defect tip exhibit a linear relation in the double logarithmic coordinate system. The present findings can provide a theoretical basis for the anti-fatigue design and fatigue life extension technology for the metallic component with welded structures.

Numerical analysis of lost foam casting for large-caliber water meter shell

Large-caliber water meter shells are prone to shrinkage porosity, wrinkles, air entrapment, slag inclusion, and other defects during the lost foam casting process. Taking the vertical spiral wing WS-100 water meter as the research object, through the analysis of the structure of the water meter shell, the flow field and temperature field of the design of outer bottom injection-vertical pouring, outer bottom injection-horizontal pouring and inner bottom injection-horizontal pouring involved in the filling and solidification process are numerically simulated and solve analysis, respectively. The results showed that: when the inner bottom injection-horizontal pouring process was adopted, the filling process of the casting was stable, the isolated liquid phase area of the solidification process was relatively small, and the possibility of forming defects was less. The casting performance is excellent, and the numerical analysis is verified to be effective.

16MnCr5 gear shaft fracture caused by inclusions and heat treatment process

Gear shaft of 16MnCr5 steel is an important moving part to transfer torque in truck steering, which fatigue design life is 50,000 times. However, the lifetime of the test results is only about half in two design life. The microstructure, slag inclusion, phase composition and microhardness profiles of failure gear shaft were characterized by the optical microscope, scanning electron microscope and microhardness tester, respectively. The results show that cracks appeared at the fillet of the top, pitch circle and root of the gear. The size and distribution of slag inclusions in16MnCr5 steel also have a certain effect on the initiation of surface cracks of gears. The surface hardness of carburizing quenching hardening layer is low. After the heat treatment, a non-martensitic microstructure is formed, and machining hardening occurs on the right tooth surface, which seriously affects the contact fatigue degree of the gear.

Understanding the Effects of CoAl2O4 Inoculant Additions on Microstructure in Additively Manufactured Inconel 718 Processed Via Selective Laser Melting

The effect of varying amounts of CoAl2O4 inoculant ranging from 0 to 2 wt pct on the microstructure evolution of Inconel 718(IN718) fabricated by selective laser melting (SLM) was evaluated. Characterization of the as-built microstructure revealed that addition of CoAl2O4 resulted in a modest degree of grain refinement with a slight increase in microstructural anisotropy. Increasing the total CoAl2O4 content beyond 0.2 wt pct resulted in severe agglomeration of the non-metallic particles and the formation of slag inclusions measuring up to 100 μm in size present in the as-built microstructure. In addition to large agglomerates, the inoculant was chemically reduced to form a fine dispersion of submicron-sized Al2O3 particles throughout the IN718 matrix. The fine dispersion of oxides significantly hindered grain recrystallization during the post-fabrication heat treatment due to a Zener pinning effect. The findings from this study indicate in order to effectively utilize CoAl2O4 as a grain refining inoculant for additive manufacturing, the process parameters need to be optimized to avoid agglomeration of the non-metallic particles and other process-related defects.

Failure analysis on girth weld cracking of underground tee pipe

Three girth weld cracking events were found by X-ray inspection in one natural gas station. To determine the failure cause, one of the three failure events was studied by visual inspection, nondestructive testing, microstructure examination, scanning electronic microscopy (SEM) coupled with energy dispersive spectrometry (EDS), blasting tests, finite element simulations and a series physical and chemical tests. The results revealed that the welding defects were original failure factor, and these welding defects led to crack initiation and propagation through the wall thickness under three aspects of stress concentration effects with internal pressure. The stress concentration effects were originated from the unqualified inner chamfering angle, unequal wall thickness, and inherent shape of tee pipe. The reason causing welding defects of girth weld is that the slag inclusions were not cleaned up timely, and then the slag inclusions led to the existence of welding defects.

Features of structure and properties formation in welded joints made of A500C and B500C strength classes reinforcing steels

In the manufacture of welded reinforcing mesh, rolled products of various strength classes are used. High requirements for mechanical properties and structural condition are imposed on welded joints. Connections must provide a set of operational properties. This article presents the results of studies of the structure and mechanical properties of welded joints of reinforced rolled products of strength classes A500C and B500C, performed by spot welding. It is established that the weld (core) of A500C strength class steel is characterized by the presence of a layer of cast metal (hardness 180–190 HV) with slag inclusions. In the heat-affected zone, widmanstett ferrite and bainite — like structures with a hardness of 251–268 HV are observed. The temporary breaking resistance of A500C steel joints is 322–350 MPa. It is shown that the welded joint of steel of strength class B500C does not have a clear division into structural zones. Similar bainite structures in the form of batch formations are observed in the seam and the heat-affected zone. The hardness of the metal of the welded joint is in the range from 205 to 241 HV, and the level of temporary resistance is 510–525 MPa. It is established that the probable cause of premature failure of welded joints of A500C steel is the presence of large slag formations in the metal seam (core). This may be due to insufficient cleaning and preparation of the weld site. Particles of scale and other contaminants fall into the molten metal of the core and "freeze" in it, forming slag inclusions. Cavities filled with slag reduce the cross-section of the seam and as a result significantly weaken it. In addition, slag inclusions are additional stress concentrators and act as a source of destruction when an external load is applied. For the manufacturer of reinforcing nets, it is proposed, as a technological recommendation, to use additional tools for cleaning the welding site in the form of metal brushes or abrasive tools with additional surface degreasing.

Early age activation of slag concrete for applications in hollowcore slabs

Prestressed hollowcore slabs are potentially critical segments in the construction sequence of a precast concrete structure, in which very early age strength is vital for ensuring factory productivity. Importantly, the construction industry is striving to reduce concrete's carbon footprint by using Portland cement substitutes, particularly using ground granulated blastfurnace slag (GGBS) in Ireland. This paper investigates the early age strength enhancement methods for slag-concrete mixes, in order to address the well-known retarding effects arising from slag's inclusion. The strength enhancement methods, including temperature curing and a novel accelerating admixture, are used to activate the slag in the concrete mixes, with replacement rates up to 50% GGBS. The efficacy of these methods is investigated in relation to establishing the development of compressive strength and modulus of elasticity over time (being relevant to stress transfer), particularly at very early and at later ages for strength compliance. The study demonstrates the potential for using up to 50% GGBS mixes for slab production while still maintaining the strengths sufficient to achieve existing productivity targets in precast concrete production.

Weld Defect Detection From Imbalanced Radiographic Images Based on Contrast Enhancement Conditional Generative Adversarial Network and Transfer Learning

When a sensor data-based detection method is used to detect the potential defects of industrial products, the data are normally imbalanced. This problem affects improvement of the robustness and accuracy of the defect detection system. In this work, welding defect detection is taken as an example: based on imbalanced radiographic images, a welding defect detection method using generative adversarial network combined with transfer learning is proposed to solve the data imbalance and improve the accuracy of defect detection. First, a new model named contrast enhancement conditional generative adversarial network is proposed, which is creatively used as a global resampling method for data augmentation of X-ray images. While solving the limitation of feature extraction due to low contrast in some images, the data distribution in the images is balanced, and the number of the image samples is expanded. Then, the Xception model is introduced as a feature extractor in the target network for transfer learning, and based on the obtained balanced data, fine-tuning is performed through frozen-unfrozen training to build the intelligent defect detection model. Finally, the defect detection model is used to detect five types of welding defects, including crack, lack of fusion, lack of penetration, porosity, and slag inclusion; an F1-score of 0.909 and defect recognition accuracy of 92.5% are achieved. The experimental results verify the effectiveness and superiority of the proposed defect detection method compared to conventional methods. For other similar applications to defect detection, the proposed method has promotional value.

An autonomous technique for weld defects detection and classification using multi-class support vector machine in X-radiography image

Non-destructive tests are a major evaluation process in the metal, oil, and gas industries. In these industries, weld defect inspection is one of the important parts of testing. Manual inspection may complicate for proper justification and it produces false identification during detection of weld defects in the human perspective less situations. X-radiography testing is utilized in the weld defect inspection and now this method is mostly outdated further it is enhanced into analysis on X-radiography digital image. Therefore, an autonomous weld defect detection and classification is required for the error free inspection. This paper proposed an autonomous technique for weld defects detection and classification using multi-class support vector machine (MSVM) in X-radiography images where weld defects such as porosity, gas pores, tungsten inclusions, longitudinal cracks, lack of penetration, and slag inclusions are considered. Three modules are involved in this proposed method. In the first module, the images were smoothened using modified anisotropic diffusion method. The segmentation process was performed using improved Otsu’s method in the second module. Finally, the features of the region of interest are extracted and given as input to the multi-class support vector machine with the kernel Gaussian radial basis function. The results of proposed scheme were compared with artificial neural network, Bayes and MSVM with other kernel functions like multi-layer perceptron and polynomial. The implementation and experimental outcomes reveal that the proposed scheme can positively detect and classify the weld defects in X-radiography images.