Effects of Process Parameters prior to Annealing on the Formability of Two Cold Rolled Dual Phase Steels

Granbom, Ylva

doi:10.1002/srin.200806354

Cited by 9 publications

(2 citation statements)

References 4 publications

(6 reference statements)

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“…Phase quantification by image analysis resulted in an initial microstructure consisting of 72% ferrite and 28% pearlite. The banding is inherited from the solidification microstructure and has been reported as a consequence of Mn segregation during solidification of the slabs in dual-phase steels [29,30]. The uniaxial tensile mechanical properties of the steel in the as-received condition are: ultimate tensile strength (UTS) 1038 ± 5 MPa, yield strength (YS, 0.2% offset) 974 ± 10.6 MPa and total elongation to fracture (EL) of 2 ± 0.4%.…”

Section: Materials and Experimental Routementioning

confidence: 99%

Experimental Determination of Continuous Cooling Transformation (CCT) Diagrams for Dual-Phase Steels from the Intercritical Temperature Range

Bräutigam–Matus

Altamirano

Salinas‐Rodríguez

et al. 2018

Metals

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The phase transformation kinetics under continuous cooling conditions for intercritical austenite in a cold rolled low carbon steel were investigated over a wide range of cooling rates (0.1–200 ∘ C/s). The start and finish temperatures of the intercritical austenite transformation were determined by quenching dilatometry and a continuous cooling transformation (CCT) diagram was constructed. The resulting experimental CCT diagram was compared with that calculated via JMatPro software, and verified using electron microscopy and hardness tests. In general, the results reveal that the experimental CCT diagram can be helpful in the design of thermal cycles for the production of different grades of dual-phase–advanced high-strengh steels (DP-AHSS) in continuous processing lines. The results suggest that C enrichment of intercritical austenite as a result of heating in the two phases (ferrite–austenite) region and C partitioning during the formation of pro-eutectoid ferrite on cooling significantly alters the character of subsequent austenite phase transformations.

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Section: Materials and Experimental Routementioning

confidence: 99%

Experimental Determination of Continuous Cooling Transformation (CCT) Diagrams for Dual-Phase Steels from the Intercritical Temperature Range

Bräutigam–Matus

Altamirano

Salinas‐Rodríguez

et al. 2018

Metals

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“…Among AHSS, the most common is the dual-phase (DP) steel, whose microstructure is mainly composed of martensite particles scattered in a ductile ferrite matrix as a result of specific thermal treatments [2][3][4]. The mechanical strength and ductility level of these steel grades are mainly associated with the amount of martensite and ferrite in the microstructure, respectively [5][6][7][8][9]. These microstructural characteristics allow the manufacture of steel components with an excellent combination of mechanical properties [10,11].…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of Hot-Dip Galvanized DP Steels via Artificial Neural Networks and Multi-Objective Genetic Optimization

Reséndiz‐Flores

Altamirano-Guerrero

Costa³

et al. 2021

Metals

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This modeling and optimization study applies a non-linear back-propagation artificial neural network, commonly denoted as BPNN, to model the most important mechanical properties such as yield strength (YS), ultimate tensile strength (UTS) and elongation at fracture (EL) during the experimental processing of hot-dip galvanized dual-phase (GDP) steels. Once the non-linear BPNN is properly trained, the most important variables of the continuous galvanizing process, including initial/first cooling rate (CR1), holding time at the galvanizing temperature of 460 °C (tg) and the final/second cooling rate (CR2), are obtained in an optimal way using an evolutionary approach. The experimental development of GDP steels in continuous processing lines with outstanding mechanical properties (550 < YS < 750 MPa, 1100 MPa < UTS and 10% < EL) is possible by using a combined hybrid approach based in BPNN and multi-objective genetic algorithm (GA). The proposed computational method is applied to the specific design of an actual manufacturing process for the first time.

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Simulation of the Soaking and Gas Jet Cooling in a Continuous Annealing Line using Dilatometry

Granbom

Ryde

Jeppsson

2010

steel research int.

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The present study concerns the simulation of a continuous annealing line (CAL), using dilatometry. Simulations of CAL have been performed on four commercial steel grades with different chemical compositions in order to investigate how the alloying elements C, Mn, Si and B affect the microstructure and hardness of dual phase (DP) and martensitic steels. Three annealing cycles corresponding to those used in a CAL have been applied. When annealing intercritically, as is the case in DP‐steel production, the materials do not reach equilibrium during soaking. Mn and C increase the austenite content and consequently the hardness of the materials. Higher levels of Si (0.4 wt %) are required to retard the formation of new ferrite during cooling in the gas jet section, prior to quenching. B increases hardenability effectively when annealing in the austenite region but is not as efficient during intercritical annealing, which implies that boron restrains ferrite nucleation rather than impeding ferrite growth. Results from DICTRA calculations show that it is possible to simulate the phase transformations during soaking, gasjet cooling and quenching.

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Effects of Process Parameters prior to Annealing on the Formability of Two Cold Rolled Dual Phase Steels

Cited by 9 publications

References 4 publications

Experimental Determination of Continuous Cooling Transformation (CCT) Diagrams for Dual-Phase Steels from the Intercritical Temperature Range

Experimental Determination of Continuous Cooling Transformation (CCT) Diagrams for Dual-Phase Steels from the Intercritical Temperature Range

Optimal Design of Hot-Dip Galvanized DP Steels via Artificial Neural Networks and Multi-Objective Genetic Optimization

Simulation of the Soaking and Gas Jet Cooling in a Continuous Annealing Line using Dilatometry

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