Mechanical Properties Of Steel Materials Research Articles

Study on microstructure characterization of steel using on multi-frequency electromagnetic detection and FE simulation calculation

Microstructures dominate mechanical properties of steel materials. Monitoring and controlling microstructure variations are important for high-quality steel productions. In this study, the multi-frequency electromagnetic technology is used to effectively characterize changes of steel microstructures. Steel samples with individual micro- components are obtained using different heat treatments and are measured using a self-designed multi-frequency electromagnetic system. Micro- and Macro- FE models are developed to discuss electromagnetic responses on steel microstructures with different phases, grain size and grain boundaries. The relative permeability of different steel microstructures are calculated and discussed. Results show that the low frequency inductance will increase with the increase of ferrite grain size and ferrite fraction. The relative permeability of single ferrite grain boundary is determined to be 165 and the orientation of grain boundary can influence the relative permeability of steel microstructures.

Multiobjective Evolutionary Learning for Multitask Quality Prediction Problems in Continuous Annealing Process.

In industrial production processes, the mechanical properties of materials will directly determine the stability and consistency of product quality. However, detecting the current mechanical property is time-consuming and labor-intensive, and the material quality cannot be controlled in time. To achieve high-quality steel materials, developing a novel intelligent manufacturing technology that can satisfy multitask predictions for material properties has become a new research trend. This article proposes a multiobjective evolutionary learning method based on a two-stage model with topological sparse autoencoder (TSAE) and ensemble learning. For the structure characteristics of a typical autoencoder (AE), a topology-related constraint is incorporated into the loss function of the AE, thus maintaining the global relationship among multistage input data to improve the data reconstruction quality. Then, a sparse representation of the data is added to the AE to achieve dimensionality reduction. Moreover, the extreme gradient boosting (XGBoost) method is applied to predict the mechanical properties of steel materials through collaboration learning mechanisms. To enhance the model accuracy, a multiobjective evolutionary algorithm (MOEA) with a knee solution strategy is used to optimize the network structure and hyperparameters of the two-stage model. Experiments are conducted using real steel production data from a continuous annealing process (CAP). The results verify that the proposed method obtains a higher prediction accuracy than other state-of-the-art methods and can guide practical production and new material design.

The Influence and Mechanism of Cryogenic Treatment on the Mechanical Properties of Steel Materials

The Influence and Mechanism of Cryogenic Treatment on the Mechanical Properties of Steel Materials

Mechanical Performance Forecast for BP Neural Network Materials Optimized by Genetic Algorithm

The mechanical properties of steel materials play a crucial role in their design, selection, and application. In order to better predict the mechanical properties through chemical composition and process parameters, this paper uses genetic algorithm to optimize the BP neural network to establish a mechanical property prediction model for steel materials. The model can predict three mechanical properties, including yield strength, tensile strength, and elongation, through chemical composition and process parameters. After optimization by genetic algorithm, the problems of insufficient convergence effect, random initialization of weights and thresholds in the BP neural network model are improved, and the prediction error is significantly reduced. The experimental results show that the GA-BP algorithm model has excellent performance in predicting the mechanical properties of steel materials.

The Mechanical Performance Prediction of Steel Materials based on Random Forest

The mechanical performance of steel materials is crucial for the design, selection, and application of materials. In order to better predict the mechanical performance through chemical composition and process parameters, this paper establishes a predictive model for the mechanical properties of steel materials based on the random forest algorithm. The model predicts yield strength, tensile strength, and elongation based on chemical composition and process parameters. The results indicate that the random forest algorithm model demonstrates excellent performance in predicting the mechanical properties of steel materials.

Design fundamentals of demountable steel structures: from materials to members

AbstractThe impact of greenhouse gas emissions, especially CO2 emissions, on the global environment is receiving more and more attention. Most countries around the world had reached a consensus to reduce carbon emissions after holding a series of climate conferences. In 2021, the buildings and construction sector accounted for around 37% of energy and process‐related CO2 emissions globally. To mitigate the CO2 emissions produced by the construction industry, the application of demountable steel structures that can be reused is a viable solution. This study investigated the design fundamentals of demountable steel structures that aims to reduce carbon emissions by reusing the main components of the steel structure. In this paper, the demountable reusability performance parameter γd of steel members is proposed and used for the reusable performance design of demountable steel members. An overview of the mechanical properties of steel materials under static and cyclic loading are presented as a basis for the reuse of steel structures. A brief review of existing forms of demountable steel connection joints is presented and the feasibility of reuse of demountable steel systems is explored.

The austenite to polygonal ferrite transformation in low-alloy steel: multi-phase-field simulation

The austenite to ferrite phase transformation is a critical structural transformation in steel production, where the morphology and grain size of ferrite substantially influence the mechanical properties of steel materials. In this work, the influences of cooling rate, prior austenite grain size (PAGS), and Mn content on the microstructure evolution and component distribution of austenite-to-polygonal ferrite phase transformation are investigated by a multi-phase-field model. It is found that higher cooling rates intensify the driving force for austenite to polygonal ferrite phase transformations and delay the phase transformation process. As PAGS decrease, the increased proportion of austenite grain boundary offers more nucleation sites for polygonal ferrite and thus refines the polygonal ferrite grain. Additionally, increased Mn content results in significant grain refinement due to a reduction in the transformation temperature of austenite to polygonal ferrite. This work provides valuable insights into adjusting and designing desired microstructures of polygonal ferrite for enhancing the mechanical performance of steel.

Investigating the behaviour of steel framed-tube and moment-resisting frame systems exposed to fire

This paper investigates the behaviour of two popular structural systems subjected to overheating and column removal cases, which may follow fire incidents. A typical 15–storey steel building is designed with two types of structural system framed-tube and moment-resisting frame. The nonlinear behaviour of these structures under different fire scenarios is investigated using OpenSees Software. The results indicate that deflection of heated beams is insignificant below 400 °C but after that, degrading mechanical properties of steel material leads to large deflection and runaway of heated beams at temperatures below 600 °C. Also, heating the beams of structures initially induces large axial forces in the beams due to restraints on thermal expansion. Thermal expansion of heated floors induces large horizontal displacement and consequently causes additional bending moments in the exterior column. So columns reach their elastic limit at the early stages of fire. Columns of the framed-tube system reach their elastic limit at lower temperatures (130 °C) but fail at higher temperatures (380 °C) compared to columns of the moment-resisting frame system (210 °C). In addition, the lower storey and interior columns are more vulnerable to progressive collapse and fail at lower temperatures (330 °C) due to carrying more gravity loads. In most fire scenarios, beams and columns of framed-tube systems fail at higher temperatures and perform well in the fire than moment-resisting frame systems. In column removal scenarios, mid-span displacement of the heated beam increases significantly, leading to downward movement of upper stories. Also, column removal in the framed-tube system is more destructive than in the moment-resisting frame system. In general, in both structural systems, column removal scenarios, which may follow fire, induce more damage to the structures than general temperature rise in considered fire scenarios.

The microstructure and properties of Cr/Ni alloying layer after surface alloying treatment induced by continuous scanning electron beam process

The surface alloying of scanning electron beam can improve the microstructure and mechanical properties of steel materials. In this paper, Cr/Ni alloying treatment was performed on 35CrMo alloy structure steel by using continuous scanning electron beam to improve surface performance. The influence of scanning electron beam technology on the structure of alloy layer is studied, and the influence of coating thickness on the structure and properties of the alloying layer is discussed. The results show that the surface of 35CrMo steel is composed of alloying layer, heat affected zone and matrix. The microstructure of the alloying layer is short columnar crystal, equiaxed crystal and acicular martensite. The surface hardness can reach 770HVwhen the coating thickness is 5μm, which is 2 times of the matrix. With the increase of Cr/Ni coating thickness, the surface of sample hardness decreases, and the corrosion resistance of the sample increases.

Causes detection of unqualified bendability of hot rolled strip via improved RankBoost with multiple feature ranking algorithms

ABSTRACT In hot rolling process, mechanical properties of steel materials are important to steel quality. The bendability is one of the key parameters to evaluate the formability of the strip. When the bendability is unqualified, how to detect causes becomes a big challenge. In this paper, a model to find the causes of bendability of hot rolled strip based on improved RankBoost with multiple feature selection algorithms using historical data is built. Firstly, the related process variables and bendability results are collected. And then, seven feature ranking methods including Fisher score, Relief, Gini index, T-test, Kruskal–Wallis, mutual information entropy and minimum redundancy maximum relevance (MRMR), are used to rank the significance of features individually. Finally, to summarize the results of the seven methods, the total importance of every feature can be obtained using the improved RankBoost method to select the most important features as the major causes. The real field data set from hot rolling strip steel process is used to validate the model. The results demonstrate that the RankBoost method can give a more credible result.

Modelling tensile tests on high strength S690 steel materials undergoing large deformations

Standard tensile tests are commonly used to determine mechanical properties of metallic materials, such as yield strength and tensile strength as well as ductility. In general, these standard tensile tests are able to provide basic mechanical properties of steel materials, commonly referred as engineering stress-strain curves. These curves are considered to be effective for linear elastic and post yielding deformations up to mobilization of tensile strengths, and they are widely adopted in structural design and analysis of steel structures. However, for detailed investigations into structural behaviour of steel structures in large deformations beyond onset of necking, cross-sectional changes in the steel materials often become very large. Hence, an improved stress-strain curve, commonly known as a true stress-strain curve, with proper adjustment according to large longitudinal deformations should be adopted in advanced finite element models.In order to develop full range true stress-strain curves of various steel materials for large deformations, a research project is conducted to perform an integrated experimental and numerical study. Standard tensile tests on two S275 steel coupons and two S690 steel coupons are carried out, and advanced optical measurements using a digital imaging correlation technique are adopted to measure deformation fields of these coupons with a high precision during the entire deformation ranges. After data analyses using three different transformation rules, namely, i) Power Law Method, ii) Linear Law Method, and iii) Instantaneous Area Method, three different true stress-strain curves for each of S275 and S690 steel materials are derived. These curves are then incorporated into advanced finite element models to simulate large deformations of these steel coupons observed in the tensile tests. Improvements to the true stress-strain curves derived from Instantaneous Area Method are made through successive corrections according to measured and predicted deformation characteristics of the steel coupons. Consequently, the proposed true stress-strain curves determined with Instantaneous Area Method are shown to be highly acceptable for numerical analyses of steel structures undergoing large plastic deformations up to fracture. Expressions of the proposed full range true stress-strain curves for S275 and S690 steel materials are also provided.

Mechanical properties of hot-rolled and cold-formed steels after exposure to elevated temperature: A review

Abstract Due to the structural integrity and redundancy in structural design, a steel building may not collapse in a fire hazard. Then the residual mechanical properties of steel materials are important indexes to evaluate the postfire performance of the entire structure and the reuse of the steel members. Many studies have been performed to explore the postfire residual performance of different structural steels. However, the observed varying trends and proposed evaluation guidance are too specific and are different from each other. In this paper, existing postfire test data for hot-rolled steels and cold-formed steels are collected from an extensive literature survey. Statistical analyses on the effects of heating experience on the mechanical properties of steels are conducted. The influencing mechanisms are explained from the point of microstructure phase changes during and after the fire heating. The cold-formed steels exhibit a higher level of influence from the fire heating due to the release of cold-working dislocation. Two series of predictive models for postfire residual strength evaluation are calibrated, and they are highly universal and can be easily applied for the residual strength assessment of hot-rolled and cold-formed steels after a fire.

Prediction model based on XGBoost for mechanical properties of steel materials

In order to predict the mechanical properties of steel materials, an intelligent prediction approach based on XGBoost model and big data is presented in this paper. The effectiveness of the model was verified by using it to predict the mechanical properties of hot-rolled strips. Firstly, a dataset with 17,710 samples was established by using the practical hot-rolled process data, where every sample has 17 characteristics (C, Si, Mn, P, S, Alt, V, Ti, Nb, Ni, Cr, Cu, Mo, B, N, final rolling temperature and curling temperature) and three output variables (tensile strength, compressive strength and elongation). 90% of 17,710 samples were used as training samples and others were used as testing samples. The simulation results showed that the accuracy of the model for tensile strength, compressive strength and elongation of the hot-rolled strip was 0.99895, 0.99576, 0.96260, respectively, which were superior to the results by using BP neural network model.

First principle study of occupancy, bonding characteristics and alloying effect of Zr, Nb, V in bulk <i>α</i>-Fe(C)

The volume change rate, total energy, binding characteristics, state density, charge distribution number and mechanical properties of cells formed by solid solution of Zr, Nb and V in α-Fe(C) are calculated by using the first-principles method. Thus, the effect of Zr, Nb, V on α-Fe(C) are studied in this paper. The results show that V displaces Fe atoms which is at the apex angle of α-Fe (C) cells preferentially, while Zr and Nb displace Fe atoms at the body center of α-Fe(C) cells. Zr and Nb reduce the stability of ferrite, but Zr is more difficult to solidly solubilize in α-Fe(C) than Nb. Solid solution of V increases the binding energy of crystal cells, meanwhile the toughness of crystal cell is mainly improved. After solid is solubilized in ferrite, Zr and Nb atoms only form metal bonds with Fe atoms while V and Fe atoms form the metal bonds and Fe—V ionic bonds. The ionic bonds of Fe—V are stronger than metal bonds of Zr and Nb atoms with Fe atoms, which is the main factor of the cell increasing. Zr and Nb mainly improve the mechanical properties of steel material by means of dispersion strengthening. To some extent, V solid solution can improve the toughness of ferrite, which is the main reason for improving the mechanical properties.

Prediction model based on XGBoost for mechanical properties of steel materials

Prediction model based on XGBoost for mechanical properties of steel materials

Mechanical properties of lean duplex stainless steel at post-fire condition

This paper reports an experimental investigation of the mechanical properties of cold-formed lean duplex stainless steel after exposure to high temperatures up to 1000 °C. The test specimens were extracted from rectangular and square hollow sections that were cold-rolled from flat plates of lean duplex stainless steel. The mechanical properties, Young's modulus, yield strength, ultimate strength, Ramberg-osgood parameter and strain at ultimate strength of lean duplex stainless steel, are reported. The residual mechanical properties of steel materials are compared with the predicted values calculated by the existing equations. It is shown that the existing equations cannot provide accurate predictions for the post-fire mechanical properties of lean duplex stainless steel materials. Thus, a unified equation is proposed to predict residual mechanical properties for lean duplex stainless steel specimens in post-fire conditions. A constitutive model is also proposed to predict the stress-strain relationship of the test specimens after exposure to high temperatures up to 1000 °C. A reliability analysis was conducted for the proposed equation. The proposed equation compared favourably with the experimental results, and was found to be reliable for predicting lean duplex stainless steel mechanical properties after exposure to high temperatures.

Structural features of cold-formed steel profiles

Using capacity of cold-formed steel sections increases thanks to the opportunities which are offered by the developing technology. Low production cost and variety of profiles that can be produce easy, fast, high quality provide to improve its popularity as a structural material. In production, Sulphur and Phosphorous accumulation region occurs at intersection region of flanges and web of hot rolled steel profile. This causes to decrease strength of profile. Other difference between cold-formed and hot rolled steel sections is that mechanical properties of steel material homogeneously distributes throughout the profile. Both in frame and truss systems, cold-formed steel profiles develop both as main and secondary bearing element. These present variety options to the designers with pure, galvanized, aluminized applications. As with many building materials, mechanical behavior of cold-formed steel profile is quite complex due to the nature of thin walled steel sections. Design and analysis methods of cold-formed steel profile are rapidly shaped day by day. The general theory of beams investigated in past studies make possible analyses of cold-formed steel profile. Moreover, in structural systems, using of cold-formed steel profile provide height strength besides sustainable, environmentalist, green building because it requires less material and cost. Although these profiles have many advantages, use of cold-formed steel profiles in our country structures is rather limited unfortunately. New steel construction regulations in Turkey also do not mention cold-formed thin walled steel structure. Main purpose of this study reviews structural specifications of cold-formed steel profiles which are applied world-wide.

Identification and Visualization of Fine Precipitates in a Cr-Mo Steel Using SEM Contrasts

A precise characterization of fine precipitates is crucial because these precipitates control mechanical properties of steel materials. Different types of carbide precipitates appear in heat resistant Cr-Mo steels. Their identification requires characteristic X-ray and diffraction analysis because it is usually not possible to differentiate carbides from their size and morphology alone. Latest scanning electron microscopes that are equipped with multiple image detectors can give rich information on microstructures. Thus, in this paper, we study the conditions where secondary electron (SE) and/or backscattered electron image contrast will clarify the types of precipitates in a common 2.25Cr-1Mo steel. A mechanically polished bulk specimen was observed by systematically changing the SEM the acceleration voltages and working distances. We have found that low accelerating voltages with a short working distance enables differentiation of four types of carbides and AlN precipitate in this steel. A small penetration depth of primary electrons and selective acquisition of SE/BSE is the key to extracting material contrast. This technique will allow quantification of size, distribution and area fraction of each precipitate for a large area using a bulk specimen.

Microstructure Changes of Steel Materials under Isothermal Heat Treatment in Salt Bath

Abstract To improve the mechanical properties of steel materials such as Vanadis 4extra, Vanadis 10, Vancron 40, and Böhler S600, the isothermal heat treatment procedure using salt bath was used. Samples of the steels were processed at different time of austempering at various temperatures and compared to the samples processed by heat treatment (i.e. quenching in air or quenching in oil and tempering in air) which is most widely used in practice. Hardness properties are determined by the steel microstructure, the size and number of carbide particles in this microstructure. The suitability of heat treatment for improving mechanical properties of different steel materials is assessed.

Experimental and numerical study on moment-rotation relations of welded end-plate tubular connections

Ductile behaviour of steel structures depends on mechanical properties of steel materials and steel structures are designed so that plastic deformations occur on beams particularly in beam-to-column connections under cyclic loads. Details on moment-resisting beam-to-column connections are given only for I-profiles in the Turkish Earthquake Code (TEC, 2007) and no details about beam-to-column connections consisting of box or circular hollow sections is available in the relevant code. That is why there is an uncertainty in the definition of the ductility level of the structural system consisting of box and circular hollow sections. The purpose of this study is to prevent local buckling effects to occur under bending in welded connections of circular hollow sections. In this context, the contribution of cover stiffness plates of different sizes to the behaviour and the effect of plate sizes on the capacity were investigated numerically and experimentally. Results obtained from experimental analysis are given comparatively supported by ANSYS program.