Thermomechanical Processing of Steels

Uranga, Pello; Rodríguez-Ibabe, J.M.

doi:10.3390/met10050641

Cited by 12 publications

(10 citation statements)

References 12 publications

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“…The optimized combination of high strength, ductility, and toughness of seismic steel is achieved through carefully controlled alloy chemistry and thermomechanical processing (TMP) steps, which involve precise control of heating, cooling, and mechanical deformation during steelmaking and hot rolling. [1], [2] TMP is a technique used to improve the properties of steel by controlling its microstructure through a combination of mechanical deformation and heat treatment. In the production of seismic steel, TMP has been shown to be particularly effective in improving the ductility and toughness of the steel, which are critical in the performance of steel structures during seismic events.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Seismic Steel for Earthquake-Resistant Structures: The Role of Alloy Chemistry and Thermo-mechanical Processing

El-Shenawy¹,

Hassan

Ganin

et al. 2023

The Bulletin Tabbin Institute for Metallurgical Studies (TIMS)

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The main focus of this article is to explain the scientific and engineering principles behind the development of seismic steel, which is specifically engineered to withstand seismic forces during earthquakes. Through careful control of the steelmaking process, including alloy chemistry and thermomechanical treatments, microstructures are created that provide the necessary strength, ductility, and toughness for seismic applications. S700 steel, also known as ultra-high-strength steel (UHSS), is an advanced material that has gained significant interest in recent years due to its exceptional mechanical properties. It is an example of seismic steel. This review aims to provide an overview of S700 steel, including its composition, characteristics, applications, recent advancements in the field, and potential benefits and challenges associated with using this material. The simulations using JMatPro have shown promising findings, concerning the potential for the studied modified S700 steel alloy to enhance structures' safety and resilience in earthquake-prone regions, as well as the combination of S700 steel and JMatPro represents a significant advancement in materials science and engineering.

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Section: Introductionmentioning

confidence: 99%

Optimizing Seismic Steel for Earthquake-Resistant Structures: The Role of Alloy Chemistry and Thermo-mechanical Processing

El-Shenawy¹,

Hassan

Ganin

et al. 2023

The Bulletin Tabbin Institute for Metallurgical Studies (TIMS)

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“…However, they did not link the research to the material type, such as the effect of the carbon content in carbon steel. In a thermomechanically controlled process, the mechanical properties and process stability during the process were influenced by the chemical composition, process parameter control, and optimization as well as post-forming cooling strategies and thermal treatments [33]. Therefore, the carbon content in carbon steel may influence the tensile properties of the RFW joint, as it involves the thermomechanical process.…”

Section: Introductionmentioning

confidence: 99%

Tensile Strength and Microstructure of Rotary Friction-Welded Carbon Steel and Stainless Steel Joints

Firmanto

Candra

Hadiyat

et al. 2022

JMMP

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Due to the different properties of the materials, the fusion welding of dissimilar metals may be difficult. Structural irregularities may form as a result of various phase transformations during welding. Solid-state welding, as opposed to fusion welding, occurs below the melting temperature. As a result of the melting and solidification phenomena that happen in fusion welding, solid-state welding is expected to reduce the potential for phase transformation. This paper describes the use of a rotary friction welding technique to join carbon steel and 304 stainless steel. The purpose of this work is to investigate the characteristics of rotary friction welding (RFW) when joining 304 stainless steel to carbon steels with different carbon contents. Experiments were carried out on the RFW of low- and medium-carbon steels with 304 stainless steel. The investigation was carried out using the Taguchi method of experimental design. The joints’ tensile strengths and microstructures were evaluated. The parameters that had the greatest influence on the tensile strengths of the welding results were identified. The combination of parameters resulting in the greatest tensile strength is also suggested. A microstructural examination of the weldment revealed mechanical mixing and interlocking.

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“…In hot strips making, control cooling process on run out table is vital for steel product pursuing excellent and stable performance [1]. After finishing rolling, the strip is cooled by water from a start cooling temperature to target temperature with a given cooling rate before coiled, which promotes obtaining more fine grain size and improving strengthening and toughness [2,3]. In control cooling process, high precise temperature distribution prediction and cooling path control are key factor for ensuring the mechanical property [4].…”

Section: Introductionmentioning

confidence: 99%

Temperature distribution prediction in control cooling process with recurrent neural network for variable-velocity hot rolling strips

Chen

Zhang

et al. 2022

Int J Adv Manuf Technol

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Control cooling is essential method for microstructure and mechanical properties control in hot rolling strip making. It is vital to realize high precises temperature distribution prediction and control in cooling process to ensure the industrial production. In this paper, a traditional mechanism model based on finite-difference method and combining with online cycle velocity calculation strategy was introduced as one of estimating temperature distribution baseline method. However, considering calculation time, variable-velocity rolling makes it difficult to rapidly realize temperature and water distribution modifying of each segment in cooling zone. Herein, a temperature distribution prediction method based on recurrent neural network was proposed, instead of only final cooling temperature prediction. And temperature distribution prediction performance of model with different recurrent cell and time steps were evaluated.The results indicated that the proposed model could realize temperature distribution prediction and the model based on bi-LSTM and 48 timesteps has the highest determination coefficient value of 0.976 and lowest root mean square error of 8.03 and mean absolute error of 5.7. Furthermore, compared with baseline model, the proposed model retained lower computational cost, making it applicable in industrial application by providing real-time temperature distribution prediction.

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Thermomechanical Processing of Steels

Abstract: The combination of hot working technologies with a thermal path, under controlled conditions (i [...]

Cited by 12 publications

References 12 publications

Optimizing Seismic Steel for Earthquake-Resistant Structures: The Role of Alloy Chemistry and Thermo-mechanical Processing

Optimizing Seismic Steel for Earthquake-Resistant Structures: The Role of Alloy Chemistry and Thermo-mechanical Processing

Tensile Strength and Microstructure of Rotary Friction-Welded Carbon Steel and Stainless Steel Joints

Temperature distribution prediction in control cooling process with recurrent neural network for variable-velocity hot rolling strips

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