Casting Process Research Articles

Machine learning techniques for the comprehensive analysis of the continuous casting processes: Slab defects

Continuous casting route is the most widely produced process in the world every year, accounting for around 95% of global steel production. Due to the various inevitable defects, including cracks, segregations, inclusions and breakout involved in the production process, tranditional control and monitoring approaches are pushed to their limits. Over the past decade, the increasing global competition has combined metals engineering with digital technology and artificial intelligence skills, to help the manufacturing industries to reap the benefits of “big data.” By targeting critical machine learning (ML) techniques, the casting industry leaders rapidly take advantage of the latest discoveries in manufacturing processes through digital twinning to enable defect-free casting. This study offers an analytical overview of ML methods applied to the examination of the continuous casting procedure. This paper examines the current research on ML in steel continuous casting, organizing the findings into categories, which aids in identification of typical application cases and approaches. This comprehensive analysis concludes with the elaboration of challenges, potential solutions, and a future outlook for further cutting-edge research and development to unleash the potential of future ML techniques and maintain casting industry's reputation.

EFFECT OF PROCESS PARAMETERS ON TRIBOLOGICAL PROPERTIES OF AA8079-ZRB2 COMPOSITE VIA TAGUCHI TECHNIQUE

Aluminum metal matrix composites (AMMCs) are currently widely engaged in industrial sectors. No other monolithic material can match the characteristics of AMMCs. AMMCs are stronger than traditional materials and have a wide range of industrial uses. This research work aims to study the tribological properties of AA8079/Zirconium boride (ZrB2) composite manufactured via the stir casting (SC) process. The different combinations of composites are AA8079/0[Formula: see text]wt.% ZrB2, AA8079/5[Formula: see text]wt.% ZrB2, AA8079/10[Formula: see text]wt.% ZrB2, and AA8079/15[Formula: see text]wt.% ZrB2. The parameters are reinforcement wt.% [A], load [B], sliding velocity [C], and sliding distance [D]. When designing experiments using the Taguchi method, an L[Formula: see text] orthogonal array was used. In order to determine which process parameter had the biggest influence on the output variables, wear rate (WR), coefficient of friction (COF), and analysis of variance (ANOVA) were applied. Successful fabrication of different weight fractions of ZrB2 was synthesized with AA8079 matrix through the SC process. The microstructural investigations revealed the dispersion of ZrB2 particles over the surface of the base AA8079. The response table clearly depicts that the combinations of A and C are the more dominant factor for WR, while the combinations of B and C are the more interacting parameters for COF. From the ANOVA results, it is clear that A with a 55.26% contribution, is the most predominant parameter in attaining the least WR, and for COF, B with a 31.39% contribution, is the major influencing parameter.

Particle Image Velocimetry Measurements and Numerical Simulation of the Flow and Vortex in a Hydraulic Mountain‐Bottom Submerged Entry Nozzle

The submerged entry nozzle (SEN) is a critical component in the continuous casting process, facilitating the transfer of molten steel from the tundish to the mold. The internal flow dynamics within the SEN are crucial as they influence several key aspects of casting, such as mold flow characteristics, inclusion transport, susceptibility to nozzle clogging, and the ultimate quality of the produced steel. In this study, a hydraulic nozzle model is established, and particle image velocimetry (PIV) is employed to measure velocity magnitudes inside the nozzle. Computational fluid dynamics simulations of the flow within the hydraulic nozzle model are conducted using the Reynolds‐averaged Navier–Stokes model and large eddy simulation (LES) with varying mesh sizes. The time‐averaged velocity magnitude calculated by the shear stress transport model using a medium mesh and the LES model with finer mesh resolution exhibits good agreement with the PIV measurements. Vortices are predominantly observed near the nozzle bottom and in close proximity to the nozzle wall. Notably, a pair of counter‐rotating vortices are identified at the nozzle bottom. Furthermore, transient fluctuations in velocity magnitude are effectively captured by LES employing finer mesh resolutions.

Analysis and Characterization of Green Sand Mould Parameters for Understanding their Dynamic Behavior

Production of quality castings results from proper control of process parameters involved in casting. This study shows that the values of the selected green sand mold process parameters for an individual mold can be established by modeling and characterizing process parameters. Thus, proving the uniqueness of individual mold. This paper considers sand and melting parameters, which are traditionally assumed to be constant and the same over all the molds. However, this investigation has shown that the parameters are not constant but dynamic and change over time. The investigation establishes that no two molds are the same due to differences in their mold and melting parameters. The time series method has been incorporated into this study. Systematic predictive changes of the selected process parameters were observed, which can be utilized effectively for individual molds. Process parameters were recorded. A variation was found in the values of each parameter in different molds. Values can be obtained by regression analysis. Thus, this paper determines mold health by exclusively predicting the process parameter values of individual molds, which can be effectively correlated with the generation of casting defects.

Vibrant Things

The root of the English word ‘object’ is a compound of the Latin prefix, ob, meaning in front of, and jacere, meaning to throw. This applies to the word both as a verb: to oppose, I object to [x], and as a noun: a “tangible thing, something perceived with or presented to the senses.”[1] In both cases, the definition of ‘object’ invokes a relationship between ourselves and the thing itself, in our sensing or perception of it. Perhaps because of this, it is easy to infer a human-centred definition in which the object is defined by our perception and exists for us; physical objects stop us, present obstacles for us to manoeuvre around, much like an objection: an argument presented in opposition. But what if objects are not obstacles, are not in opposition to us, are not primarily defined by our sensing or perception? My preference is for the latter half, the thrown-ness, jacere, of this etymology; objects present themselves to our senses, they throw (jacere) themselves in front of (ob) us. This definition accentuates an animacy in materiality, and an energetic lived relationality to all matter — if objects throw themselves in front of us, they arrive at us just as much as we arrive at them. Our senses are constantly being presented with objects, whether we register them or not. John, Virginia Woolf’s character in “Solid Objects,” is presented with objects (beach glass, broken porcelain, meteorite) that influence the course of his life. My visual art practice engages deeply with objects, and, like John, objects have influenced the course of my life. For this reason, object-theory resonates with me, as do stories like that of Woolf’s character for whom life is, in a sense, a series of object-relations. In this paper, I formulate a conceptual framework for an ontology of vibrant things to explore what I intrinsically already know: all matter is active, fluid, non-hierarchical, and in relation. I describe a shift where I theoretically and physically orientate myself to objects as vibrant things, speculate on how this orientation might be queer, and recount how these relations are registered in my art practice and research methodology through the process of casting. [1] “Object” Online Etymology Dictionary, accessed March 17, 2021, https://www.etymonline.com/word/object.

Significance of viscous dissipation effect during the rapid filling process in the non-adiabatic mold: A full analytical and validating solution

Significance of viscous dissipation effect during the rapid filling process in the non-adiabatic mold: A full analytical and validating solution

Superior electrochemical performance and reduced heat generation in 3D printed vs. 2D tape-casted NMC622 electrodes

This study compares the charge storage mechanisms, thermodynamics behavior, ion transport, and heat generation in NMC622 electrodes fabricated using a novel 3D printing process or the conventional 2D tape casting process. First, potentiometric entropy measurements revealed that the charge storage mechanisms for both types of electrodes consisted of lithium deintercalation in a homogeneous solid solution of NMC622 followed by a transition from a hexagonal (H1) phase to another hexagonal (H2) phase through a monoclinic (M) phase. Both types of electrodes had similar thermodynamics behavior with overlapping entropic potential profiles. Furthermore, operando isothermal calorimetry at high C-rates indicated that the 3D printed electrodes featured larger specific capacity and better rate performance than the 2D tape-casted electrodes. The better performance of 3D printed electrodes was attributed to their larger electrode/electrolyte interfacial surface area and electrical conductivity as well as their faster lithium ion transport. As a result, the instantaneous heat generation rates were smaller in 3D printed electrodes than in 2D tape-casted electrodes, thus resulting in lower overall specific electrical energy and thermal energy dissipation per unit charge stored. Overall, additive manufacturing techniques offer great potential in producing electrodes with superior electrochemical performance and reduced heat generation for fast charging batteries.

Chemical corrosion resistance mechanism of titanium alloy radiation rods with self-protected structure.

The chemical corrosion of the TC4 radiation rod surface (TRRS) during the ultrasonic casting process has the potential to significantly impair the smooth conduction of ultrasonic waves. However, in the later stages of corrosion, a self-protected structure (TSPS) emerges under the ultrasonic cavitation effect, which serves to impede the chemical corrosion of the TRRS and markedly reduce the rate of mass loss of the radiation rod. This ensures the smooth ultrasonic conduction of the radiation rod during operation. In this paper, an analysis of the microstructure of TSPS was conducted. The surface energy ratio at different crystal planes in TC4 and the self-diffusion coefficient for two phases of Ti in TC4 were calculated. The results indicated that TSPS is characterized by α-Ti grain basal planes concentrated parallel to the TRRS, higher α phase content, and fewer crystal defects. TSPS not only inhibits Ti dissolution and delays the onset of chemical corrosion, but also reduces the chemical corrosion rate.

Microstructure, microhardness and wear properties investigation in friction stir processing of stir cast Mg/B4C metal matrix composite

Abstract Friction Stir Processing (FSP) has emerged as an excellent processing approach to tailor the microstructural and other properties of cast alloys and composite materials. In the current investigation, a stir-cast magnesium metal matrix composite (MMMC) reinforced with 12 wt% B4C particles was processed using single-pass FSP. FSP was carried out with a simple cylindrical tool pin using different tool rotational speeds of 800, 1000, 1200 rpm and transverse speed of 60 mm min−1. Severe deformation occurred during FSP which helped to refine the distribution of the B4C particles and grain refinement of as-cast composites. Microstructural examination showed an appreciable grain refinement from 98 to 5 μm because of dynamic recrystallization during FSP. The maximum microhardness of the friction stir processed (FSPed) composites increased from 73 Hv to 105.4 Hv. Pin-on-disk wear tests were conducted under dry sliding conditions in the load range of 1 kg to 5 kg at a 1 m s−1 sliding velocity. The wear results indicated an enhancement of wear properties of FSPed composites in comparison to as-cast magnesium metal matrix composites. The improved hardness and wear resistance results were pertaining to the remarkable refinement in grain size coupled with refined B4C particulates and uniform distribution. The best results for hardness and wear resistance of the FSPed composite were obtained for a sample processed at a tool rotation speed of 1000 rpm. SEM/EDS of the worn samples was carried out. The wear mechanism was found as slight abrasion and oxidation. After single pass FSP, the surface of Mg/12 wt% B4C cast composite showed remarkable changes in worn surface morphology.

Determination and Sensitivity Analysis of Target Flaw Sizes for Performance Demonstration of Cast Austenitic Stainless Steel Pipe by Probabilistic Fracture Mechanics

Abstract The material of primary coolant pipe of nuclear power plants is cast austenitic stainless steel (CASS), which has a coarse crystal structure and its anisotropy causes low permeability of ultrasonic waves and low detectability. Also, the material strength and fracture toughness of CASS are affected by thermal aging depending on ferrite content, chemical compositions and casting process. The ASME Section XI Code Case N-838 provides the target flaw sizes for performance demonstration (PD) examination system of ultrasonic testing (UT) based on probabilistic fracture mechanics (PFM) analysis incorporated a thermal aging model. In this study, the target flaw sizes for Japanese pressurized water reactor (PWR) plants were investigated by using the PFM analysis code “PREFACE.” Thermal aging prediction models for tensile strength and fracture toughness of CASS were incorporated into the PREFACE Code depending on not only ferrite content and chemical compositions but also the casting process, centrifugal casting, or static casting. Those parameters were input as probabilistic variables, which were based on the material database from the Japanese PWR plants. The PFM analysis revealed that static CASS pipes have smaller target flaw sizes than centrifugal CASS pipes and the obtained target flaw sizes were very close to those in ASME Code Case N-838.

Microstructural Evolution and Properties of ZrB2‐Reinforced AA6111 Aluminum Matrix Composites Subjected to Double‐Sided Friction Stir Processing

Single‐sided friction stir processing (S‐FSP), owing to its intrinsic structural characteristics, including the advancing side and the retreating side and the nonuniformity of attributes, restricts the enhancement of the strength of aluminum composite materials. Herein, the preparation of AA6111/ZrB2 aluminum matrix composites, 4 mm in thickness, via an in situ autogenous casting process is presented. The composites undergo double‐sided FSP (D‐FSP) with varying parameters, utilizing an orthogonal test method. In these findings, it is indicated that the mean grain size of the nugget zone (NZ) post D‐FSP is reduced from 5.56 μm in S‐FSP to 4.65 μm, the percentage of low‐angle grain boundaries diminishes from 31.4% to 26.9%, and the recrystallized structure escalates from 49.7% to 65.2%. At a rotational speed of 1000 r min−1 and a processing speed of 40 mm min−1, the average hardness of the NZ of D‐FSP is augmented by 6.3% relative to S‐FSP; the ultimate tensile strength and elongation of the material are enhanced by 1.6% and 31.7%, respectively, compared to S‐FSP, while the product of strength and elongation is increased by 33.2%.

Thermal Simulation of MnS Evolution in Solidification of a Low‐Carbon Alloy Steel Bloom

The continuous casting process of a newly developed low‐carbon alloy steel is simulated using a thermal simulation method to investigate the evolution of MnS inclusion. The results indicate that MnS mainly appears as aggregated small‐sized spherical shapes (type I MnS) in the chill zone of the bloom, while in columnar zone, it tends to form strip‐like or irregular morphologies (type II MnS), and no type III MnS is observed. The size of MnS increases from the surface to the center of the samples, with the maximum equivalent diameter increasing from 1.2 to 6.0 μm. A model, considering the effects of solute redistribution and cooling rate, is established to calculate the precipitation and growth of MnS in continuous casting bloom, which is achieved by coupling theoretical calculations with the discrete solidification units. The calculated results demonstrate that sulfur segregation is the controlling factor for the precipitation and growth of MnS, which are well consistent with experiments. This work suggests that enhancing the cooling rate in the secondary cooling zone or improving homogenization of this new low‐carbon alloy steel bloom can effectively reduce the growth rate of MnS and mitigate the formation of type II MnS.

On the High Elastic Modulus Mechanism of Iron Matrix Composites

High modulus steels are characterized by high specific strength and specific stiffness, which can be attributed to the presence of hard reinforced particles. This paper investigates two common iron matrix composites, namely Fe/TiB2 and Fe/TiC, prepared through in situ reaction, focusing on their structures and properties. The results show that both types of reinforced particles in the high modulus steels consist of coarse primary particles and fine eutectic particles. In comparison to Fe/TiC composites, Fe/TiB2 composites exhibit larger elastic modulus (210 GPa). The reasons for the phenomenon that the experimentally measured values of the modulus of elasticity are lower than the calculated values at equilibrium are discussed. It was found that microporous defects left over from the casting process are often present inside the coarse primary particles, which can be the source of microcracks or fractures. In addition, matrix/particle interface stability calculations revealed that TiB2 possesses a distinctive hexagonal structure, resulting in a smaller interfacial distance (d0 = 1.375 Å) with the ferrite matrix phase. The high interfacial work of adhesion (Wad = 3.992 J/m2) further confirms the stronger interfacial stability of the Fe/TiB2 composite in comparison to the Fe/TiC composite.

Preparation and corrosion resistance to cathode materials for lithium‐ion batteries of CA6 foam ceramics

AbstractCA6 foam ceramics (CA6‐FCs) with CA6 as the main crystalline phase were prepared by adding CA6 powder through gel casting process, which reduced the severe shrinkage in the reaction synthesis process of CA6. This simple preparation process can realize the industrial production of CA6‐FCs. The linear change and physical properties of CA6‐FCs can be controlled by adjusting the additional amount of CA6 powder and the solid content of the slurry. The corrosion resistance of CA6‐FCs is better than that of the current mainstream mullite thermal insulation materials in lithium‐ion battery cathode materials. Through the simple process of this study, on the basis of industrial production, CA6‐FCs can replace mullite lightweight thermal insulation materials to improve the alkali corrosion resistance, service life, and maintain production safety of kiln lining.

Multi-Objective Optimization of Injection Molding Process Parameters for Junction Boxes Based on BP Neural Network and NSGA-II Algorithm

Many factors affect the quality of the injection molding of plastic products, including the process parameters, mold materials, type and geometry of plastic parts, cooling system, pouring system, etc. A multi-objective optimization method for injection molding process parameters based on the BP neural network and NSGA-II algorithm is proposed to address the problem of product quality defects caused by unreasonable process parameter settings. Taking the junction box shell as the object, numerical simulation was carried out using Moldflow2019 software and a six-factor five-level orthogonal experiment was designed to explore the influence of injection molding process parameters, such as the mold temperature, melt temperature, injection pressure, holding pressure, holding time, and cooling time, on the volume shrinkage rate and warpage deformation of the junction box. Based on a numerical simulation, the BP neural network and NSGA-II algorithm were used to optimize the optimal combination of injection molding process parameters, volume shrinkage rate, and warpage deformation. The research results indicate that the melt temperature has the most significant impact on the quality of the injection molding of junction boxes, followed by the holding time, holding pressure, cooling time, injection pressure, and mold temperature. After optimization using the BP neural network and the NSGA-II algorithm, the optimal process parameter combination was obtained with a melt temperature of 230.03 °C, a mold temperature of 51.27 °C, an injection pressure of 49.13 MPa, a holding pressure of 69.01 MPa, a holding time of 15.48 s, and a cooling time of 34.91 s. At this time, the volume shrinkage rate and warpage deformation of the junction box were 6.905% and 0.991 mm, respectively, which decreased by 33.2% and 3.8% compared to the average volume shrinkage rate (10.34884%) and warpage deformation (1.030764 mm) before optimization. The optimization effect was significant. In addition, the errors between the volume shrinkage rate and warpage deformation predicted by BP-NSGA-II and the simulated values using Moldflow software were 1.9% and 3.4%, respectively, indicating that the optimization method based on the BP neural network model and NSGA-II algorithm is reliable.

The Influence of the Melting and Casting Parameters on the Surface Quality of Deep-Drawn Steel Coils

Industrial production today increasingly prioritizes sustainability, emphasizing not only efficiency but also minimizing environmental and social impacts. Quality control is key in steel production. The continuous casting process is crucial, as early defect detection can lower costs and prevent unnecessary material use, thereby conserving energy and raw materials. Eliminating defects early reduces the need for costly reworking, saving resources and reducing equipment wear. Additionally, this defect prevention supports efficiency in later steps, like rolling, benefiting overall energy and material consumption. During this research, we identified several parameters whose influence we analyzed on the surface quality of deep-drawn steel. The research confirmed that, for example, the casting speed has a significant influence on the occurrence of surface defects, while, for example, the final bubbling had no statistically significant effect on the surface quality. From a sustainability perspective, monitoring and optimizing key production parameters, like the casting speed, is essential, as improper speeds can cause surface defects that risk the functionality of the final products. By optimizing these parameters, it is possible not only to reduce the risk of product failure but also to contribute to the long-term sustainability of the entire production process, reducing waste and fostering a more considerate approach to natural resources.

Study of the Hibridation of Ablation Casting and Laser Wire Metal Deposition for Aluminum Alloy 5356

The rapidly growing field of metal additive manufacturing (AM) has enabled the fabrication of near-net-shape components with complex 3D structures in a more reliable, productive, and sustainable way compared to any other manufacturing process. The productivity of AM could be significantly increased combining conventional and AM technologies. However, the application at an industrial level requires the validation of the AM process itself and the assurance of the soundness of the junction between the substrate and the deposited metal at a sufficiently rapid metal deposition rate. In this work, the validation of additively manufactured samples of Al-5356 alloy was performed. These were manufactured partially via an ablation casting process and partially via laser metal deposition using a metallic wire (LMwD). The deposited material showed low porosity levels, i.e., below 0.04%, and a small number of lack-of-union defects, which are detrimental to the mechanical properties. In the tensile samples centred at the junction between the ablated and deposited materials, it was found that when the AM part of the sample exhibited no lack-of-union defects, the region manufactured using LMwD showed higher strength than the ablation-cast part. These results suggest that the combination of ablation casting and LMwD is a competitive technique for the manufacturing of Al-5356 alloy parts with complex geometries.

Investigation of Mechanical Properties of AL-7SI With 6 WT% of 40- and 90-Micron Size Boron Carbide Metal Matrix Composite

To create and evaluate the mechanical behaviour of B4C-reinforced A356 alloy metal composites that are 6 wt. % and range in size from 40 to 90 microns. Method: By using the liquid melt stir cast process, an alloy called A356 with 6 wt. % B4C reinforced composites was created. SEM and EDS were used to characterise the microstructure of these produced composites. According to ASTM standards, mechanical characteristics such as hardness and tensile strength were assessed. Findings: The extensive dispersion of B4C particles in the A356 matrix was demonstrated by a SEM of A356 alloy with 6 wt. % of B4C composites. The A356 alloy matrix's EDS signals verified the presence of B4C particles. The hardness increased by 28.6%, ultimate strength by 26%, and yield strength by 44.4 percent with a little loss in ductility with the addition of 6 wt. % of B4C particles. Novelty: Aerospace-grade aluminium alloy A356 is often utilised in industrials. B4C particles with a size range of 40 to 90 microns were included into advanced metal composites to assist reduce weight. The choice of A356 alloy and B4C reinforcement was made strategically to meet the demanding conditions of mining operations. The results indicate a clear potential for improving the efficiency and overall performance of mining equipment.

Experimental and numerical evaluation of the green sand compaction process

ABSTRACT Determining the parameters of the sand moulding process plays an important role in obtaining green sand mould without wasting the energy used in the moulding process. The present work focuses on studying the variation effect of the sand density and elasto-plastic properties on the compaction process of sand moulding. Triaxial and uniaxial compression tests were used to estimate the properties of bentonite-bonded green sand. The behaviour of the green sand mould during the compaction process was investigated numerically by commercial finite element software, and experimentally using a flowability sensor. Detection of the green sand movement by a flowability sensor showed good agreement between the experimental and numerical results. Similar behaviour was observed for the distance-dependent displacement decrease with increasing green sand density. Stress concentration has an effect on the sand flow, density distribution and displacement of green mould sand.

Real-Time Temperature Prediction Model for Online Continuous Casting Control Using Simplified Boundary Condition Computing Method

Numerical process modeling of continuous casting is increasingly applied to optimize production practices for higher product quality guarantees, in which real-time temperature prediction is the key factor that makes it possible to observe and optimize the solidification behavior of the continuous casting process. For offline simulations, the completeness of boundary conditions and accuracy of calculation are core concerns; as for online control, the stability of the model calculation and the correctness are equally important. This study demonstrates a process tracking and online control model of continuous casting based on IoT technology and proposes a simplified calculation method for secondary cooling boundary conditions. The proposed method calculates a comprehensive heat transfer coefficient based on offline simulated parameters and computes the total heat flux of a secondary cooling zone. The experimental results show that the temperature field calculated by this method is stable, and the difference between the actual measured temperature is within an acceptable range of 15 °C. The proposed method no longer requires an online model to consider four types of heat transfer boundary conditions, improving the versatility of the online model. The smoother surface temperature curve is beneficial for dynamic control of secondary cooling water. It can be an alternative method for implementing a more conducive online continuous casting model.