CN-121983199-A - Composition prediction and length calculation method for dissimilar steel continuous casting mixed casting blank

CN121983199ACN 121983199 ACN121983199 ACN 121983199ACN-121983199-A

Abstract

The application discloses a composition prediction and length calculation method for a heterogeneous steel continuous casting mixed casting blank, which comprises the steps of establishing and verifying a tundish multiphase flow mathematical model and a casting blank solidification and mass transfer coupling model, simulating a heterogeneous steel continuous casting process under different process parameter combinations to obtain new steel grade concentration change data at an outlet of a tundish, analyzing the influence of process parameters on the mixed casting behavior in the tundish, analyzing the influence of key process parameters in the processes of lowering and rising the liquid level on the exposure of molten steel, the distribution of a slag layer and the risk of slag coiling in a pouring area, taking the new steel grade concentration change data at the outlet of the tundish as the input boundary condition of a casting blank solidification and mass transfer coupling model, simulating and predicting the distribution of key elements in the mixed casting blank, calculating the mixed casting blank length, and synthesizing the mixed casting blank length and the analysis result of molten steel cleanliness risk to determine the optimal process control parameters aiming at shortening the mixed casting blank length. The application has the advantages of accurately predicting the distribution and the length of the components of the mixed casting blank, optimizing the process control parameters and the like.

Inventors

YIN YANBIN
ZHANG JIONGMING
LIU ZHENYU

Assignees

北京科技大学

Dates

Publication Date: 20260505
Application Date: 20260122

Claims (8)

1. The method for predicting the composition and calculating the length of the dissimilar steel continuous casting mixed casting blank is characterized by comprising the following steps of: S1, establishing a tundish multiphase flow mathematical model for simulating flow, mass transfer and interface behaviors of molten steel, covering agent and air in the continuous casting process of different steel grades; s2, establishing a casting blank solidification and mass transfer coupling model for simulating the flow, solidification, heat transfer and key element transmission of the casting blank in the continuous casting process; s3, verifying the tundish multiphase flow mathematical model and the casting blank solidification and mass transfer coupling model by adopting physical simulation and industrial test data; s4, simulating different steel continuous casting processes under different process parameter combinations based on the verified multiphase flow mathematical model of the tundish, obtaining new steel concentration change data at the outlet of the tundish, and analyzing the influence of the process parameters on the mixed casting behavior in the tundish; S5, analyzing the influence of key process parameters in the liquid level lowering and rising processes on the molten steel exposure, slag layer distribution and slag reeling risk of the injection zone based on the multiphase flow simulation result of the tundish multiphase flow mathematical model; S6, taking the new steel grade concentration change data at the outlet of the tundish as an input boundary condition of the casting blank solidification and mass transfer coupling model, simulating and predicting the distribution of key elements in the mixed casting blank, and calculating the length of the mixed casting blank; and S7, combining the mixed casting blank length and the molten steel cleanliness risk analysis result, and determining the optimal process control parameters aiming at shortening the mixed casting blank length.
2. The method of claim 1, wherein the control equations of the tundish multiphase flow mathematical model include continuity equations, conservation of momentum equations, turbulence model equations, component transport equations, and VOF multiphase flow equations; In the boundary condition of the tundish multiphase flow mathematical model, the inlet boundary adopts the mass flow which dynamically changes according to the continuous casting stage, and the outlet boundary adopts the mass flow which changes according to the pulling speed.
3. The method of claim 1 wherein the control equations for the casting bloom solidification and mass transfer coupling model include continuity equations, conservation of momentum equations, turbulence model equations, component transport equations, and conservation of energy equations including latent heat of solidification processing; In the boundary condition of the casting blank solidification and mass transfer coupling model, a crystallizer region adopts a heat flow density boundary which changes along with the position, and a secondary cooling region adopts a convection heat exchange boundary.
4. The method of claim 1, wherein the different combinations of process parameters include different amounts of tundish remaining steel, different continuous casting pull rates, and different new steel grade packing flows.
5. The method according to claim 4, characterized in that the influence of the process parameters on the pouring behavior in the tundish is analyzed and the following law is determined: The residual steel quantity of the tundish is a dominant factor influencing the replacement speed of new and old steel types, and the smaller the residual steel quantity is, the faster the replacement speed is; The continuous casting pulling speed slightly affects the mixed casting process after the filling period is finished, and the higher the pulling speed is, the faster the concentration of new steel grade in the later mixed casting period is increased; The new steel grade filling flow mainly accelerates the mixing of new and old steel grades in the filling period, and has limited influence on the whole mixing casting process after the filling is finished.
6. The method according to claim 1, characterized in that the influence of key process parameters on the risk of molten steel cleanliness is analyzed, and the following rules are determined: the smaller the amount of the residual steel in the tundish is, the larger the exposed area of molten steel in the ladle filling stage is and the longer the time is; The smaller the new steel type filling flow is, the smaller the exposed area of molten steel is in the filling stage.
7. The method of claim 1, wherein the key element is a carbon element; The method for calculating the length of the mixed casting blank comprises the steps of setting a judging section according to the internal control standard of the new and old steel types on carbon elements, and calculating the length of a casting blank section with the mass fraction of the carbon elements outside the judging section of the new and old steel types as the length of the mixed casting blank.
8. The method of claim 1, wherein the optimal process control parameters are determined by minimizing the amount of steel remaining in the tundish while ensuring that the steel level is above the pilot hole and not below the minimum safe level.

Description

Composition prediction and length calculation method for dissimilar steel continuous casting mixed casting blank Technical Field The invention relates to the technical field of ferrous metallurgy continuous casting, in particular to a component prediction and length calculation method for a dissimilar steel continuous casting mixed casting blank. Background In the steel production process, dissimilar steel continuous casting technology is widely applied to improving production efficiency and reducing production cost. However, in the dissimilar steel continuous casting process, due to the alternation of new and old steel types, a mixed casting area is formed in the tundish, the crystallizer and the liquid phase pit, so that mixed casting blanks are generated. The mixed casting blank refers to a casting blank at the junction of new and old steel types, the chemical components of the mixed casting blank do not meet the standard requirements of any steel type, and degradation or scrapping treatment is usually required, so that resource waste and production cost are increased. At present, steel enterprises mainly rely on experience to control the dissimilar steel continuous casting process, and lack an accurate prediction method for the component distribution and the length of a mixed casting blank. In actual production, operators usually set process parameters such as the amount of residual steel in a tundish, the continuous casting drawing speed, the filling flow of new steel types and the like according to historical data and field experience. However, due to the complexity of molten steel flow, mass transfer and interface behavior in the tundish, and the transmission characteristics of key elements in the casting blank solidification process, it is difficult to accurately predict the composition distribution and length of the mixed casting blank only empirically. The tundish is used as key equipment in the continuous casting process, and the internal flow field of the tundish has important influence on the mixed casting process. In the heterogeneous steel continuous casting process, complex multiphase flow and mass transfer phenomena exist among molten steel, covering agent and air in the tundish. Particularly, in the processes of lowering the liquid level and raising the liquid level, fluctuation of the liquid level of the steel can lead to the exposure of molten steel in a pouring area, uneven slag layer distribution and increased slag reeling risk, thereby affecting the cleanliness of the molten steel. In addition, the transmission behavior of key elements in the solidification process of the casting blank can influence the component distribution of the mixed casting blank. In the prior art, although some researches analyze the dissimilar steel continuous casting process through physical simulation and numerical simulation, the methods usually only pay attention to a single link of a tundish or a casting blank, and lack systematic researches on the whole continuous casting process. Meanwhile, the existing model is generally difficult to accurately reflect complex working conditions in actual production, such as dynamically-changed process parameters, multiphase interface behaviors and the like, so that a prediction result has larger deviation from an actual situation. In the aspect of process parameter optimization, the prior art mainly relies on a trial and error method to determine the optimal process conditions, which is time-consuming and labor-consuming, and difficult to comprehensively consider the interaction among various process parameters. For example, the length of the mixed casting blank can be shortened by reducing the residual steel amount of the tundish, but the excessive low residual steel amount can cause the problem of vortex slag generation caused by the excessively low liquid level of the steel, the mixing of new and old steel types can be accelerated by improving the filling flow, but the exposure of molten steel can be aggravated by the excessive filling flow, and the secondary oxidation risk is increased. Therefore, how to determine the optimal process control parameters on the premise of ensuring the cleanliness of molten steel is an important challenge facing the current technology. In view of the above, there is a need in the art for improvements. Disclosure of Invention In view of the above, the invention provides a method for predicting the components and calculating the length of a dissimilar steel continuous casting mixed casting blank, which has the advantages of accurately predicting the distribution and the length of the components of the mixed casting blank, optimizing process control parameters, reducing resource waste and production cost and improving production efficiency. The invention provides a composition prediction and length calculation method for a dissimilar steel continuous casting mixed casting blank, which comprises the following steps: s1, establishing a tu