Tangshan Heavy Plate Co.

Tangshan, China

Tangshan Heavy Plate Co.

Tangshan, China
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Chen W.,Hebei United University | Zhang Y.-Z.,Hebei United University | Zhu L.-G.,Hebei United University | Zhang C.-J.,Hebei United University | And 3 more authors.
Ironmaking and Steelmaking | Year: 2012

In order to increase the beam blank cleanliness, the aim of this work is to analyse the flow field in the mould of beam blank continuous casting, to find the factors influencing the strand cleanliness and then to optimise the process parameters. A three-dimensional steady finite element model was developed to simulate and analyse the turbulent flow field in the mould. The volume of fluid model was used to track the free surface evolution at the meniscus. The influences of processing parameters, such as casting speed and nozzle parameters, on the molten steel flow in the strand (such as vortex location, liquid steel impact depth, velocity and fluctuation of the liquid steel at free surface) were analysed and the optimum processing parameters determined based on mass calculation. The results of this research project have been applied in actual production, and it has been shown that they are very useful and efficient for improving the steel cleanliness and controlling the surface cracks on the beam blank web. © 2012 Institute of Materials, Minerals and Mining.


Chen W.,Hebei United University | Zhang Y.-Z.,Hebei United University | Zhu L.-G.,Hebei United University | Zhang C.J.,Hebei United University | And 3 more authors.
Ironmaking and Steelmaking | Year: 2012

The aim of this work was to analyse the influence of the nozzle structure and parameters on the molten steel flow in beam blank continuous casting. A three-dimensional steady state finite element model was developed to compute the flow field and the meniscus fluctuation in the mould. The volume of fluid model was used to track the free surface evolution at the meniscus. It can be concluded that compared with a through conduit submerged entry nozzle (SEN), a three lateral hole SEN will reduce the impact depth, change greatly the velocity at the free surface and intensify the fluctuation of the free surface. As a whole, the fluid flow in the mould will be improved, which will help to melt the mould powder and improve the absorption of non-metallic inclusions, thus improving steel cleanness. The most rational rake angle for the three lateral hole SEN is 9°. Meanwhile, the SEN immersion depth should be in the range 200-250 mm if the casting speed is about 0·9-1·1 m min -1. © 2012 Institute of Materials, Minerals and Mining.


Chen W.,Hebei United University | Zhang Y.-Z.,Hebei United University | Ma J.-H.,Hebei United University | Wang B.-X.,Tangshan Heavy Plate Co. | And 2 more authors.
Reviews on Advanced Materials Science | Year: 2013

In this paper, a new optimization program is developed to search out the optimum processing parameters for beam blank continuous casting. The parameters optimizing method is set up combined the multi-objective genetic algorithms (based on MATLAB) with finite element method (based on ANSYS). The finite element method is used to calculate the thermo-mechanical process for beam blank continuous casting. The multi-objective genetic algorithm is used to search out the optimum processing parameters for beam blank continuous casting. Those optimum parameters can meet all specified requirements but with a minimum expense of the operational and the design constraints and can make it possible to run the caster at its maximum productivity, minimum cost and to cast defect free products. Now, online verifying of this optimization project has been put in practice, which can prove that it is very helpful to control the real production. Compared with the zero order method, the result of this optimizing method is better. This developed optimizing method, taking full advantage of the feature of FEM that computes precisely and the feature of MOGA that search the optimal solution globally and rapidly, provides a method for solving the complex and large engineering problem, especially to the multi-objective optimizing problems © 2013 Advanced Study Center Co. Ltd.


Chen W.,Hebei Polytechnic University | Zhang Y.-Z.,Hebei Polytechnic University | Wang B.-X.,Tangshan Heavy Plate Co.
Ironmaking and Steelmaking | Year: 2010

Based on a coupled heat and stress model, an artificial intelligence optimisation program was developed to optimise the process parameters in the continuous casting of steel. The program can be used to identify the key factors for the cracks of the strand and obtain the optimum process parameters of continuous casting. The optimisation program contains two models, one is the thermomechanical model developed using the finite difference method, and the other is the optimisation model developed using the subproblem approximation method. The whole program works by automatic iteration between the two models. This study has taken the stress constraint in the solidified shell into consideration when studying the metallurgical constraints. The application of the achieved optimum parameters would make it possible to run the caster at maximum productivity, with minimum cost and fewer defects. After manufacturing verification of this optimisation project, the incidence of cracks has reduced from 8% to 2%, and water consumption in the secondary cooling zone has been decreased by 25%. © 2010 Institute of Materials, Minerals and Mining.


Chen W.,Hebei Polytechnic University | Wang B.-X.,Tangshan Heavy Plate Co. | Han H.-L.,Hebei Polytechnic University
Ironmaking and Steelmaking | Year: 2010

Silicon content in pig iron has long been used as one of the most important indices to represent the thermal state of a blast furnace. The control of silicon at a low level has been regarded as one of the most important operational techniques. In this paper, a mathematical program was developed to predict and control the silicon content in pig iron. The program includes three main models: the self-learning model, the prediction model and the control model. The first is to train the program by the intelligent method integrating artificial neural network with genetic algorithm according to the past processing variables. The second is to predict the next silicon content according to the current processing variables. The last is to control the subsequent behaviour of silicon based on the expert knowledge. From practical applications it was found that the program can provide both accurate predicted silicon content and corresponding operational guidance. It is very useful to stabilise silicon content and as low as possible. © 2010 Maney Publishing.


Chen W.,Hebei Polytechnic University | Wang B.X.,Tangshan Heavy Plate Co. | Chen Y.,Hebei Polytechnic University
Advanced Materials Research | Year: 2011

Sulphur content in pig iron is one of the most important indices to represent the quality of liquid iron in blast furnace. In order to timely control sulfur content, a mathematical model is developed to predict the sulfur content in pig iron. Compared with the conventional artificial neural network model, a new method is developed to integrate artificial neural network with genetic algorithm. The genetic algorithm with the binary coded chromosome is used to optimize initial neural network weights. In this project, the first aim is to train the model by integrating artificial neural network with genetic algorithm according to the past processing variables. The second is to predict the next sulfur content based on the training result in the first step and according to the current processing variables. Compared with only using artificial neural network model, this developed method can improve the predicted accuracy. From practical applications, it can be found the model is exact and reliable to predict the sulfur content in the pig iron of blast furnace. © (2011) Trans Tech Publications.


Chen W.,Hebei Polytechnic University | Zhang Y.Z.,Hebei Polytechnic University | Zhu L.G.,Hebei Polytechnic University | Zhang C.J.,Hebei Polytechnic University | Wang B.X.,Tangshan Heavy Plate Co.
Advanced Materials Research | Year: 2010

The high carbon chromium bearing steel, as a kind of special steel, entails high quality. The work aims to simulate the solidification process of continuous casting of high carbon chromium bearing steel, to find the cause for defect, and to optimize the secondary cooling parameters steel. A finite element model is developed to compute heat transfer and solidification in bearing continuous casting. By comparing the calculated data with the metallurgical constraints, the key factor caused the cracks on the strand can be found out. Then based on the subproblem approximation method, an optimization program is developed to search out the optimum cooling parameters. Those optimum parameters can meet all specified requirements but with a minimum expense of the operational and the design constraints and can make it possible to run the caster at its maximum productivity, minimum cost and to reduce the defects. Now, online verifying has been obtained with the cracks decreasing and the water consumption of secondary cooling zone saving. © (2010) Trans Tech Publications.

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