Low Carbon Structural Steel Research Articles

Analysis of Laser Cladding Bead Morphology for Developing Additive Manufacturing Travel Paths

Laser cladding is a method of material deposition used to envelop a substrate with a surface of material which has superior characteristics, such as corrosion or abrasion resistance. There are several process parameters to be adjusted to generate a deposited bead or a layer, and developing a model to predict a bead shape is challenging due to the highly level of coupling between the manufacturing process parameters and the bead geometry. This paper will present results for an experimental study where P420 steel cladding powder (a steel commonly used in injection molding) is deposited on low carbon structural steel plates using the coaxial powder flow laser cladding method. Five process parameters such as laser power, scanning speed and powder flow rate etc. are varied to explore their impact on the bead height, width, penetration, area, dilution area, and the bead shape. The bead shape to process parameter relationships are explored and predictive models are developed using analysis of variance, a ‘lumped parameter model, and artificial neural network (ANN) approaches. The best fit for a predictive model is achieved with the ANN approach. This work will be extended to incorporate a variety of substrate and clad materials, and layering parameters.

Optimization of Flux Cored Arc Welding Process Parameter Using Genetic and Memetic Algorithms

AbstractMost of the manufacturing enterprises indulge in the bonding of metals during the production process. This makes welding one of the most important processes in industries. Subsequently, due to the high usage of welding process, industrial engineers desire to optimize the parameters concerned to achieve the desired weld bead characteristics. This paper focuses on optimization of flux cored arc welding process parameters, which are used for deposition of duplex stainless steel on low carbon structural steel plates. Experiments were conducted based on central composite rotatable design and mathematical models were developed using multiple regression method. Further, optimization with objectives as minimizing percentage dilution, maximizing height of reinforcement and bead width was carried out using genetic algorithm and memetic algorithm. This problem was formulated as a multi objective, multivariable and non-linear programming problem. The algorithms were implemented using basic functions of C language making it highly reliable, adoptable, very user friendly and extendable to other welding processes such as GMAW, GTAW, robotic welding, etc. The adopted optimization techniques were further compared based on various computational factors.

Optimization of Ferrite Number of Solution Annealed Duplex Stainless Steel Claddings Using Integrated Artificial Neural Network – Genetic Algorithm

Cladding is the most economical process used on the surface of low carbon structural steel to improve the corrosion resistance. The corrosion resistant property is based on the amount of ferrite present in the clad layer. Generally, the ferrite content present in the layer is expressed in terms of ferrite number (FN). The optimum range of ferrite number plays an instrumental role to bring adequate surface properties like chloride stress corrosion cracking resistance, pitting and crevice corrosion resistance and mechanical properties. For achieving maximum economy and enhanced life, duplex stainless steel (E2209T1-4/1) is deposited on the surface of low carbon structural steel of IS: 2062. The problem faced in the weld cladding towards achieving the required amount of ferrite number is the selection of an optimum combination of input process parameters (welding current, welding speed, contact tip to specimen distance and gun angle). This paper mainly concentrates on estimating FN and analysis of input process parameters on FN of heat treated duplex stainless steel cladding. To predict FN, mathematical equations was developed based on four factor five level central composite rotatable design with full replication using regression methods. In this paper, artificial neural network (ANN) and genetic algorithm (GA) techniques were integrated and labeled as ANN-GA to identify the optimum process parameters in FCAW to get maximum FN. From the results, the integrated ANN-GA (I OR II) is capable of giving maximum FN at optimum process parameters compared to that of experimental, regression and ANN modeling

Method for detecting austenite grains in low-carbon steel after hot deformation

The structure of low-carbon steel after hot deformation at 1060 and 960°C with different degrees is studied. A procedure is developed for specimen etching in a reagent based on picric acid making it possible to detect clear austenite grain boundaries and sub-boundaries after hot deformation.

Nitriding and Carbonitriding Influence on Stainless Steels Surface Layers Changes

The structure of low-carbon steels after saturation by nitrogen and carbon in the mode of electrolytic-plasma nitriding and carbonitriding on the surface structure of austenitic stainless steel 12Cr18Ni10Ti has been studied. Optimum modes of electrolytic-plasma nitriding and carbonitriding are determined ensuring the maximum saturation of nitrogen and carbon, the microhardness of the surface. It is established, that after electrolyte-plasma processing microstructure of steel 12Cr18Ni10Ti has martensite structure. As a result of the research it is revealed that steel 12Cr18Ni10Ti after the electrolyte-plasma processing has high hardness.

Defect structure and impact strength of low-carbon steel after equal-channel angular pressing and electroplastic rolling

The microstructure and defect structure of low-carbon steel after equal-channel angular pressing and electroplastic rolling are considered. The influence of such treatment on the microhardness and impact strength of steel is established.

Modification of Stainless Steels Surface Layers by Nitriding and Carbonitriding

The structure of low-carbon steels after saturation by nitrogen and carbon in the mode of electrolytic-plasma nitriding and carbonitriding on the surface structure of austenitic stainless steel 12Cr18Ni10Ti has been studied. Optimum modes of electrolytic-plasma nitriding and carbonitriding are determined ensuring the maximum saturation of nitrogen and carbon, the microhardness of the surface. It is established, that after electrolyte-plasma processing microstructure of steel 12Cr18Ni10Ti has martensite structure. As a result of the research it is revealed that steel 12Cr18Ni10Ti after the electrolyte-plasma processing has high hardness.

Annealing behavior of ultrafine grained structure in low-carbon steel produced by equal channel angular pressing

The influence of annealing (400–700°C, 1h) on the microstructure and mechanical properties of ultrafine grained low-carbon Fe–Mo–Nb–V–C carbide-strengthened steel produced by equal channel angular pressing was investigated. The grain size and the mechanical properties of the ultrafine grained steel are stable up to 500°C. The grain growth kinetics during annealing in the temperature interval of 400–700°C was studied, and an activation energy for grain growth of 420kJ/mol was determined.

Optimization of GMAW Process Parameters Using Particle Swarm Optimization

To improve the corrosion-resistant properties of carbon steel cladding process is usually used. It is a process of depositing a thick layer of corrosion resistant material-over carbon steel plate. Most of the engineering applications require high strength and corrosion resistant materials for long-term reliability and performance. By cladding, these properties can be achieved with minimum cost. The main problem faced in cladding is the selection of optimum combinations of process parameters for achieving quality clad and hence good clad bead geometry. This paper highlights an experimental study to optimize various input process parameters (welding current, welding speed, gun angle, contact tip to work distance, and pinch) to get optimum dilution in stainless steel cladding of low-carbon structural steel plates using gas metal arc welding (GMAW). Experiments were conducted based on central composite rotatable design with full-replication technique and mathematical models were developed using multiple regression method. The developed models have been checked for adequacy and significance. Using particle swarm optimization (PSO) the parameters were optimized to get minimal dilution.

Effect of Zinc Galvanization on the Microstructure and Fracture Behavior of Low and Medium Carbon Structural Steels

Microstructure and fracture behavior of ASTM 572 Grade 65 steels used for wind tower applications have been studied. Steels of two carbon level chemistries designed for this grade were used in the study. Fracture toughness of the steels was studied using 3-point bend test on samples coated with zinc and not coated with zinc. Lower carbon steel showed higher resistance to fracture than medium carbon steel after zinc galvanization. SEM study suggests that zinc and zinc bath additives that migrated to crack tips are responsible for the loss in ductility. The phenomenon of Liquid Metal Embrittlement (LME) is suggested to have taken place. Zinc bath additives traced at crack zones are suggested to have migrated at the zinc galvanizing temperatures.

Estimation of Optimum Dilution in the GMAW Process Using Integrated ANN-GA

To improve the corrosion resistant properties of carbon steel, usually cladding process is used. It is a process of depositing a thick layer of corrosion resistant material over carbon steel plate. Most of the engineering applications require high strength and corrosion resistant materials for long-term reliability and performance. By cladding these properties can be achieved with minimum cost. The main problem faced on cladding is the selection of optimum combinations of process parameters for achieving quality clad and hence good clad bead geometry. This paper highlights an experimental study to optimize various input process parameters (welding current, welding speed, gun angle, and contact tip to work distance and pinch) to get optimum dilution in stainless steel cladding of low carbon structural steel plates using gas metal arc welding (GMAW). Experiments were conducted based on central composite rotatable design with full replication technique, and mathematical models were developed using multiple regression method. The developed models have been checked for adequacy and significance. In this study, artificial neural network (ANN) and genetic algorithm (GA) techniques were integrated and labeled as integrated ANN-GA to estimate optimal process parameters in GMAW to get optimum dilution.

Ways of improving the quality of the surface of rolled products made of low-carbon structural steel ingots

Study of the nature of low-carbon structural steel rolled product surface defects by a metallographic method makes it possible to establish that formation of flaws in rolled product in the bottom part of ingots is connected with the presence of gas bubbles and extraneous inclusions. The effect of aluminum on rolled product surface quality is analyzed. The optimum aluminum content in steels 09G2S – 0.011–0.015%, S355j2G3 – 0.021–0.025% is established, and this makes it possible to improve metal ductility, reduce the degree of ingot defect development, and reduce rolled product rejection for surface defects.

Microplastic Limit of Steels as a Means of Fatigue Limit Determination

The experimental determination of fatigue limit in case of steels represents an expensive and time consuming process not speaking about the necessity of a sufficient volume of representative material necessary for the specimens manufacturing, manufacturing of numerous test specimens, the need of an expensive (electrohydraulic) test equipment etc.Microplastic strains occurring at stresses below the yield point play a significant role at cyclic loading of metals within high cycle fatigue region. The microplastic strains cannot be measured by common methods due to the discontinuity of their distribution and a varying character of their level in the metal structure, but however, owing to the magnetoelastic effect the threshold stress at which dislocation pile-up stresses begin to obstruct the magnetic domains in rotation to the direction of the tensile stress can be determined by means of changes in magnetic permeability during tensile loading.In the paper, the changes of the magnetic permeability were measured indirectly – by means of the changes of the electrical impedance (a.c. resistance). The measurement was performed on the normalized low-carbon structural steel CSN 41 1375. The microplastic limit was determined by evaluation the ΔR-σ records. A comparison with the fatigue limit in a reversed fatigue loading showed that the MPL was below the fatigue limit. The microplastic limit can thus be considered to separate non- damaging and damaging cyclic stresses.The paper presents the results of the abovementioned characteristics what may shorten and make cheeper the determination of the fatigue limit and non-damaging cyclic stresses of structural materials.

Effect of Intercritical Quenching Temperature on the Microstructure and Performance of 650 MPa Low-Carbon Structural Steel

The effect of intercritical quenching temperature on the microstructure and performance of a 650 MPa low-carbon structural steel was investigated by optical microscope and mechanical test. The results showed that the obtained microstructures at different temperature were mainly bainites, the volume fraction of the bainites was gradually increased and the size of which became finer with the increase of the quenching temperature. Moreover, as the temperature increased, the yield strength and tensile strength gradually increased; the yield ratio decreased initially and then increased; the impact energy increased among the temperature range of T3°C and T4°C, subsequently dropped significantly at T5°C, and then increased atT6°C. The best comprehensive performance was obtained at T4°C in this study.

Research methods of ultrafine steels after equal channel angular pressing

Steel subjected to ECAP has very high mechanical characteristics. The goal of the present work is to investigate the influence of thermal treatment on steel cold brittle resistance after ECAP. The influence of equal-channel angular pressing and heat treatment on structure-phase state and mechanical characteristics of Fe360 is investigated. Also, the investigations of deformation in metals and steels are carried out with the use of infrared imaging cameras. The results concerned with the evaluation of storage energy in the process of plastic deformation of the structural low carbon steel are presented.

Effect of nitrogen plasma immersion ion implantation of polyamide-6 on its sliding properties against steel surface

The sliding behaviour of polyamide-6 (PA6) treated by nitrogen plasma immersion ion implantation (N PIII) has not been studied yet, even if PIII is a promising technique for polymer surface modification. The effect of N PIII of PA6 on its sliding properties against low carbon structural steel S235 was studied. The surface changes were characterised by XPS, contact angle measurements and optical microscopy, while alterations in the sliding properties including friction coefficient, wear and temperature close to contact were studied by a pin-on-disc tribometer under dry and variously lubricated conditions. The N-content of the surface layer increased, while those of C and O decreased upon N PIII treatment. The contact angles decreased and the total surface energy and its polar and dispersive components increased significantly. Under dry sliding in the low Pv regime, the friction coefficient of the treated sample started from a value lower than that of the untreated version and the corresponding specific wear rate was also smaller. Under dry sliding, the increased surface energy caused increased adhesion of the treated PA6, associated with the formation of a transfer layer on the steel disc. Water lubrication was more efficient – in accordance with the increased polar component of surface energy – for the treated PA6 than found earlier for PETP. For the treated PA6, a decreased friction was observed upon run-out type lubrication test with gearbox oil, due to increased retention of oil on the treated surface characterised by an increased dispersive component of the surface free energy.

Optimization of GMAW Process Parameters in Austenitic Stainless Steel Cladding Using Genetic Algorithm Based Computational Models

Weld cladding is a process of depositing a thick layer of anticorrosive metal on a corrosive substrate surface to impart better corrosion resistance properties. In weld cladding process, the difficulty generally encountered will be the problem of selecting optimum combination of input process parameters to achieve the desired dilution level. Until recently trial and error methods were employed to determine the optimum process parameters, which result in wastage of cost and time. This paper focuses on optimization of GMAW process parameters, which are used for deposition of austenitic stainless steel on low carbon structural steel plates. Experiments were conducted based on four-factor five-level central composite rotatable design with full replication technique. Mathematical models relating to gas metal arc welding process parameters to clad bead geometry were developed using multiple regression method. Developed mathematical models are helpful in predicting the clad bead geometry and in setting process parameters at optimum values to accomplish the desirable dilution level at relatively low cost with a high degree of reproducibility. The accuracy of the results was tested by conducting conformity tests using the same experimental set up. Moreover, Genetic Algorithm tool with GUI available in MATLAB 7.0 was used to optimize the process parameters to achieve optimum dilution.

Mold Material Selection and Development Trends

With wide use of mold in modern industry, to extend its service life has become urgent problem to solve. Based on its usage, components of mold can be divided into 2 parts. One is structural parts which consist of guide, set (dynamic) template, ejecting machine, supporting member, etc. These are usually made of low carbon structural steel, alloy structural steel, or carbon tool steel. the other is molding parts which include cavity, type core, forming insert, etc. these are key parts for direct molding. Because they must bear temperature, pressure, erosion, wear and tear when used, the service life depends on material of them. Appropriate material is the main way to extend its service life.

Atomic force microscopy of the nanostructure of metals and alloys subjected to mechanical and thermal stresses

Low-carbon structural steels are an extremely important material used widely in all industries, e.g., in the manufacture of industrial pipelines and equipment operating at elevated temperatures and pressures, in contact with chemically aggressive environments. In this work, we study nanoscale changes in the substructure of structural steels that result from operational wearing out.

Modelling and Prediction of Stainless Steel Clad Bead Geometry Deposited by GMAW Using Regression and Artificial Neural Network Models

To improve the corrosion-resistant properties of carbon steel, usually cladding process is used. It is a process of depositing a thick layer of corrosion-resistant material over carbon steel plate. Most of the engineering applications require high strength and corrosion resistant materials for long-term reliability and performance. Cladding these properties can be achieved with minimum cost. The main problem faced in cladding is the selection of optimum combinations of process parameters for achieving quality clad and hence good clad bead geometry. This paper highlights an experimental study to predict various input process parameters (welding current, welding speed, gun angle, contact tip-to-work distance, andpinch) to getoptimum dilutionin stainless steel cladding of low carbon structural steel plates using Gas Metal Arc Welding (GMAW). Experiments were conducted based on central composite rotatable design with full replication technique, and mathematical models were developed using multiple regression method. The developed models have been checked for adequacy and significance. Using Artificial Neural Network (ANN) the parameters were predicted, and percentage of error was calculated between predicted and actual values. The direct and interaction effects of process parameters on clad bead geometry are presented in graphical form.