scholarly journals Design of As‐Cast Structures of Continuously Cast Steel Grades: Modeling and Prediction

2020 ◽  
Vol 91 (11) ◽  
pp. 2000235
Author(s):  
Carolin Fix ◽  
Sina-Maria Elixmann ◽  
Dieter Georg Senk
Keyword(s):  
Cast Steel ◽  
Modeling And Prediction ◽  
Steel Grades ◽  
Continuously Cast

scholarly journals Investigations on decreased high temperature ductility of different continuously cast steel grades

2021 ◽  
Author(s):  
Carolin Fix ◽  
Lukas Borrmann ◽  
Sina-Maria Elixmann ◽  
Carolin Grahe ◽  
Svenja Kurenbach ◽  
...  
Keyword(s):  
High Temperature ◽  
Cast Steel ◽  
Steel Grades ◽  
Continuously Cast

Inter-Columnar Macro-Segregation in Continuously Cast Steel; Characterization, Possible Reasons, and Consequences

2021 ◽  
Author(s):  
Seenivasan Rajiah ◽  
Manjini Sambandam ◽  
Sethu Prasanth Shanmugam ◽  
Saju Vikraman ◽  
Rajendra Taticherla
Keyword(s):  
Cast Steel ◽  
Continuously Cast

scholarly journals Development of Universal Mould Geometry for the Teeming of Cylindrical Iron-Base Alloy Ingots

Metals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 471
Author(s):  
Josef Odehnal ◽  
Pavel Ludvík ◽  
Tomáš Studecký ◽  
Pavel Michálek
Keyword(s):  
Alloy Steel ◽  
Base Alloy ◽  
Cast Steel ◽  
Solidification Process ◽  
High Alloy ◽  
High Alloy Steel ◽  
Iron Base Alloy ◽  
Steel Grades ◽  
Borated Stainless Steel ◽  
Filling And Solidification

The presented work is aimed at developing a mould geometry suitable for casting both low- and high-alloy steel grades into 500 kg experimental ingots. The high Height-to-Diameter (H/D)-ratio mould currently used in COMTES FHT Inc. served as a reference and for finite element method simulations (FEM) of the filling and solidification process. The optimized mould geometry, balancing the porosity and segregations, was determined using MAGMA software. Four different steel grades were defined for the simulation. Case studies were carried out for 34CrNiMo6 (W.Nr. 1.6582), DHQ8, CB2 and borated stainless steel grades ranging from low-alloy steel to high-alloy steel. Extended user-defined criteria and verified boundary conditions were used to predict the formation of A-segregations in cast steel. Both primary (PDAS) and secondary (SDAS) arm spacings were modelled as well. The optimized mould shape and the casting assembly were designed based on the simulation results.

scholarly journals The Structure of the Silumin Coat on Alloy Cast Steels

2012 ◽  
Vol 12 (2) ◽  
pp. 215-220
Author(s):  
T. Szymczak
Keyword(s):  
Phase Structure ◽  
High Speed ◽  
Cast Steel ◽  
Intermetallic Phases ◽  
External Layer ◽  
Cast Steels ◽  
Steel Grades ◽  
The Absolute ◽  
The Given ◽  
Alloy Cast

The Structure of the Silumin Coat on Alloy Cast Steels The work presents the analysis results of the structure of the coat obtained by dipping in silumin AlSi5 of two grades of alloy cast steel: GX6CrNiTi18-10 (LH18N9T) and GX39Cr13 (LH14). The temperature of the silumin bath was 750±5°C, and the hold-up time of the cast steel element τ = 180 s. The absolute thickness of the coat obtained in the given conditions was g = 104 μm on cast steel GX6CrNiTi18-10 and g = 132 μm on GX39Cr13. The obtained coat consisted of three layers of different phase structure. The first layer from the base "g1" was constructed of the phase AlFe including Si and alloy additives of the tested cast steel grades: Cr and Ni (GX6CrNiTi18-10) and Cr (GX39Cr13). The second layer "g1" of intermetallic phases AlFe which also contains Si and Cr crystallizes on it. The last, external layer "g2" of the coat consists of the silumin containing the intermetallic phases AlFeSi which additionally can contain alloy additives of the cast steel. It was shown that there were no carbides on the coat of the tested cast steels which are the component of their microstructure, as it took place in the case of the coat on the high speed steels.

scholarly journals Model for Predicting the Machinability of Continuously Cast and Subsequently Rolled Steel Using the Artificial Neural Network

2021 ◽  
Vol 15 (3) ◽  
pp. 381-386
Author(s):  
Miha Kovačič ◽  
Shpetim Salihu ◽  
Uroš Župerl
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Production Process ◽  
Chemical Elements ◽  
Cast Steel ◽  
Model Development ◽  
Cutting Speed ◽  
Steel Production ◽  
Continuously Cast ◽  
Artificial Neural

The paper presents a model for predicting the machinability of steels using the method of artificial neural networks. The model includes all indicators from the entire steel production process that best predict the machinability of continuously cast steel. Data for model development were obtained from two years of serial production of 26 steel grades from 255 batches and include seven parameters from secondary metallurgy, four parameters from the casting process, and the content of ten chemical elements. The machinability was determined based on ISO 3685, which defines the machinability of a batch as the cutting speed with a cutting tool life of 15 minutes. An artificial neural network is used to predict this cutting speed. Based on the modelling results, the steel production process was optimised. Over a 5-month period, an additional 39 batches of 20MnV6 steel were produced to verify the developed model.

Quantification of macrosegregation in continuously cast steel structures

1998 ◽  
Vol 69 (6) ◽  
pp. 228-236 ◽  
Author(s):  
Jacek Komenda ◽  
Gunilla Runnsjö
Keyword(s):  
Cast Steel ◽  
Steel Structures ◽  
Continuously Cast
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