Method and system for predicting molten iron temperature in KR molten iron pretreatment process

Abstract

The invention discloses a method and system for predicting the temperature of molten iron in the KR molten iron pretreatment process. The method comprises the steps that the temperature and weight of molten iron, the physical size of a ladle and the physical size parameters of a stirring paddle in the current KR molten iron stirring pretreatment process are obtained; obtaining a quantitative influence relational expression of the rotating speed of the stirring paddle on molten iron flow characteristic variables; a current ladle masonry refractory arrangement mode and refractory heat transfer physical attribute parameters are obtained; obtaining a molten iron temperature drop rate and molten iron flow characteristic variable change relational expression; obtaining a relational expression that the molten iron temperature changes along with stirring time; and calculating the temperature of the molten iron under the target working condition and time. By adopting the technical scheme, the temperature of the molten iron in the KR stirring molten iron pretreatment process can be quantitatively predicted, and a reference basis is provided for reducing temperature drop and improving desulfurization efficiency.

Description

Technical Field

[0001] The present invention belongs to the technical field of steelmaking in the metallurgical industry, and particularly relates to a method and system for predicting the temperature of hot metal during the KR hot metal pretreatment process. Background Art

[0002] Most domestic steel enterprises use KR stirring desulfurization in the hot metal pretreatment process of steelmaking, that is, the mechanical rotation of stirring is used to improve the reaction efficiency between hot metal and desulfurizer, and achieve the efficient removal of sulfur content in hot metal. The vortex formed at the top of the hot metal ladle during the KR stirring process exacerbates the rate of hot metal temperature, and at the same time, the heat transfer rate between hot metal and the refractory on the wall of the hot metal ladle also increases accordingly. The above factors lead to a decrease in hot metal temperature, thereby reducing the speed of the desulfurization reaction, and the lower hot metal temperature is not conducive to the melting of the desulfurizer and destroys the kinetic conditions of the desulfurization reaction. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method and system for predicting the temperature of hot metal during the KR hot metal pretreatment process, which can quantitatively predict the magnitude of the hot metal temperature under the target working conditions and stirring time by obtaining the comprehensive influence of process parameters on the flow and heat transfer of hot metal.

[0004] To achieve the above object, the present invention adopts the following technical solutions:

[0005] A method for predicting the temperature of hot metal during the KR hot metal pretreatment process includes:

[0006] Step S1, obtaining the hot metal temperature, weight, physical dimensions of the hot metal ladle, and physical dimensions of the stirring paddle parameters during the current KR stirring hot metal pretreatment process;

[0007] Step S2, establishing a three-dimensional flow model of hot metal during the KR stirring process according to the hot metal temperature, weight, physical dimensions of the hot metal ladle, and physical dimensions of the stirring paddle parameters during the current KR stirring hot metal pretreatment process;

[0008] Step S3, obtaining hot metal flow data according to the three-dimensional flow model of hot metal during the KR stirring process;

[0009] Step S4, obtaining a quantitative influence relationship between the stirring paddle speed and the hot metal flow characteristic variables according to the flow data;

[0010] Step S5, obtaining the current layout method of the refractory lining in the hot metal ladle and the physical property parameters of the refractory heat transfer;

[0011] Step S6, establishing a heat transfer model of hot metal during the KR stirring process according to the layout method of the refractory lining in the hot metal ladle and the physical property parameters of the refractory heat transfer;

[0012] Step S7, obtaining hot metal temperature distribution data according to the heat transfer model of hot metal during the KR stirring process;

[0013] Step S8: Obtain the relationship between the molten iron temperature drop rate and the change of molten iron flow characteristic variables according to the molten iron temperature distribution data;

[0014] Step S9: Obtain the relationship between the molten iron temperature and the stirring time according to the quantitative influence relationship between the stirring paddle rotation speed and the molten iron flow characteristic variables and the relationship between the molten iron temperature drop rate and the change of molten iron flow characteristic variables;

[0015] Step S10: Obtain the temperature of the molten iron under the target working conditions and time through the relationship between the molten iron temperature and the stirring time.

[0016] Preferably, the quantitative influence relationship between the stirring paddle rotation speed and the molten iron flow characteristic variables is:

[0017] ε = C1·n 3

[0018] where ε is the turbulent kinetic energy dissipation rate; n is the rotation speed; C1 is a constant.

[0019] Preferably, the relationship between the molten iron temperature drop rate and the change of molten iron flow characteristic variables is:

[0020] k Tem = C2 + C3·ε

[0021] where k Tem is the molten iron temperature drop rate; ε is the turbulent kinetic energy dissipation rate; C2 and C3 are constants.

[0022] Preferably, the relationship between the molten iron temperature and the stirring time is:

[0023] T = T0 - (C2 + C1C3n 3 )t

[0024] where T0 is the initial temperature of the molten iron; n is the rotation speed; t is the stirring time.

[0025] The present invention also provides a prediction system for the molten iron temperature in the KR molten iron pretreatment process, including:

[0026] The first processing module is used to obtain the molten iron temperature, weight, physical dimensions of the ladle, and physical dimensions of the stirring paddle parameters in the current KR stirring molten iron pretreatment process;

[0027] The second processing module is used to establish a three-dimensional molten iron flow model in the KR stirring process according to the molten iron temperature, weight, physical dimensions of the ladle, and physical dimensions of the stirring paddle parameters in the current KR stirring molten iron pretreatment process;

[0028] The third processing module is used to obtain the molten iron flow data according to the three-dimensional molten iron flow model in the KR stirring process;

[0029] The fourth processing module is used to obtain a quantitative influence relationship between the rotational speed of the stirring paddle and the molten iron flow characteristic variables according to the flow data;

[0030] The fifth processing module is used to obtain the current refractory layout mode of the molten iron ladle and the physical property parameters of refractory heat transfer;

[0031] The sixth processing module is used to establish a molten iron heat transfer model during the KR stirring process according to the previous refractory layout mode of the molten iron ladle and the physical property parameters of refractory heat transfer;

[0032] The seventh processing module is used to obtain the molten iron temperature distribution data according to the molten iron heat transfer model during the KR stirring process;

[0033] The eighth processing module is used to obtain a change relationship between the molten iron temperature drop rate and the molten iron flow characteristic variables according to the molten iron temperature distribution data;

[0034] The ninth processing module is used to obtain a relationship between the molten iron temperature and the stirring time according to the quantitative influence relationship between the rotational speed of the stirring paddle and the molten iron flow characteristic variables and the change relationship between the molten iron temperature drop rate and the molten iron flow characteristic variables;

[0035] The tenth processing module is used to obtain the temperature of the molten iron under the target working conditions and time through the relationship between the molten iron temperature and the stirring time.

[0036] Preferably, the quantitative influence relationship between the rotational speed of the stirring paddle and the molten iron flow characteristic variables is:

[0037] ε = C1·n 3

[0038] Where ε is the turbulent kinetic energy dissipation rate; n is the rotational speed; C1 is a constant.

[0039] Preferably, the change relationship between the molten iron temperature drop rate and the molten iron flow characteristic variables is:

[0040] k Tem = C2 + C3·ε

[0041] Where k Tem is the molten iron temperature drop rate; ε is the turbulent kinetic energy dissipation rate; C2 and C3 are constants.

[0042] Preferably, the relationship between the molten iron temperature and the stirring time is:

[0043] T = T0 - (C2 + C1C3n 3 )t

[0044] Where T0 is the initial temperature of the molten iron; n is the rotational speed; t is the stirring time.

[0045] The present invention obtains the parameters of the molten iron temperature, weight, physical dimensions of the ladle, and physical dimensions of the stirring paddle during the KR stirring pretreatment process of molten iron; establishes a three-dimensional flow mathematical model of molten iron during the KR stirring process based on the above parameters; processes and analyzes the three-dimensional flow data of molten iron to obtain a quantitative influence relationship between the stirring paddle speed and the characteristic variables of molten iron flow; obtains the layout method of the refractory lining in the current ladle and the physical property parameters of refractory heat transfer; establishes a heat transfer mathematical model of molten iron during the KR stirring process based on the above parameters, and calculates the temperature distribution of molten iron; processes the temperature distribution data of molten iron to obtain a change relationship between the molten iron temperature drop rate and the characteristic variables of molten iron flow; obtains a change relationship between the molten iron temperature and the stirring time through the above relationships, and calculates the temperature of molten iron under the target working conditions and time. The present invention can quantitatively predict the temperature of molten iron during the KR stirring pretreatment process of molten iron, providing a reference basis for reducing temperature drop and improving desulfurization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on the provided drawings.

[0047] Figure 1 It is a flowchart of the method for predicting the temperature of molten iron during the KR molten iron pretreatment process in the embodiment of the present invention;

[0048] Figure 2 It is a schematic diagram showing the change of the characteristic variables of molten iron flow with the stirring paddle speed in the embodiment of the present invention;

[0049] Figure 3 It is a schematic diagram showing the layout of the refractory lining in the ladle in the embodiment of the present invention;

[0050] Figure 4 It is a schematic diagram showing the temperature distribution of molten iron in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0052] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the drawings and specific embodiments.

[0053] Example 1:

[0054] As Figure 1 shown, an embodiment of the present invention provides a method for predicting the temperature of hot metal in the KR hot metal pretreatment process, including:

[0055] Step S1, obtain the hot metal temperature, weight, physical dimensions of the hot metal ladle, and physical dimensions of the stirring paddle in the current KR stirring hot metal pretreatment process;

[0056] Step S2, obtain the hot metal temperature, weight, physical dimensions of the hot metal ladle, and physical dimensions of the stirring paddle in the current KR stirring hot metal pretreatment process, and establish a three-dimensional physical model of KR stirring based on the physical dimension parameters;

[0057] Step S3, set the fluid calculation domain according to the three-dimensional physical model of KR stirring, and numerically calculate the hot metal flow data by using the hot metal-air multiphase VOF model and the hot metal flow k-ε model;

[0058] Step S4, obtain the quantitative influence relationship between the stirring paddle speed and the hot metal flow characteristic variables according to the flow data;

[0059] Step S5, obtain the current layout method of the refractory lining in the hot metal ladle and the physical property parameters of the refractory heat transfer;

[0060] Step S6, set the heat transfer calculation domain of the refractory and hot metal during the KR stirring process according to the current layout method of the refractory lining in the hot metal ladle, the physical property parameters of the refractory heat transfer, and the three-dimensional physical model of KR stirring, and establish a hot metal heat transfer model during the KR stirring process;

[0061] Step S7, numerically calculate the temperature distributions of the refractory and hot metal according to the hot metal heat transfer model during the KR stirring process; further calculate the hot metal temperature distributions at different stirring paddle speeds to obtain the hot metal temperature distribution data under different stirring paddle speed conditions;

[0062] Step S8, obtain the relationship between the hot metal temperature drop rate and the change of the hot metal flow characteristic variables according to the hot metal temperature distribution data;

[0063] Step S9, obtain the relationship between the hot metal temperature and the stirring time according to the quantitative influence relationship between the stirring paddle speed and the hot metal flow characteristic variables and the relationship between the hot metal temperature drop rate and the change of the hot metal flow characteristic variables;

[0064] Step S10, obtain the initial temperature of the hot metal and the stirring paddle speed in the current KR hot metal pretreatment process, substitute them into the relationship between the hot metal temperature and the stirring time, and calculate the result of the hot metal temperature changing with time; determine the temperature of the hot metal at the target time according to the target stirring time of the current hot metal pretreatment.

[0065] As an implementation manner of an embodiment of the present invention, the quantitative influence relationship between the stirring paddle rotation speed and the molten iron flow characteristic variables is:

[0066] ε = C1·n 3

[0067] Wherein, ε is the turbulent kinetic energy dissipation rate; n is the rotation speed; C1 is a constant.

[0068] As an implementation manner of an embodiment of the present invention, the change relationship between the molten iron temperature drop rate and the molten iron flow characteristic variables is:

[0069] k Tem = C2 + C3·ε

[0070] Wherein, k Tem is the molten iron temperature drop rate; ε is the turbulent kinetic energy dissipation rate; C2 and C3 are constants.

[0071] As an implementation manner of an embodiment of the present invention, the relationship between the molten iron temperature and the stirring time is:

[0072] T = T0 - (C2 + C1C3n 3 )t

[0073] Wherein, T0 is the initial temperature of the molten iron; n is the rotation speed; t is the stirring time.

[0074] In this embodiment, the initial temperature of the molten iron is 1630K, the weight of the molten iron is 250 tons, and the diameters of the upper top and the lower bottom of the ladle are 4066mm and 3738mm respectively. The height and thickness of the cross paddle of the stirring paddle are 950mm and 480mm respectively, its rotation radius is 700mm, and the immersion depth is 1500mm. According to the above parameters, a three-dimensional flow mathematical model of molten iron in the KR stirring process is established to calculate the molten iron velocity magnitude, the molten iron-air phase interface distribution, and the rotation of the stirring paddle. As Figure 2 described, the magnitude of the constant C1 in the quantitative influence relationship between the stirring paddle rotation speed and the molten iron flow characteristic variables is 9.01×10 -7 . As Figure 3 shown, further obtain the current refractory layout method of the ladle and the physical property parameters of refractory heat transfer; the refractory materials include aluminum silicon carbide brick 2, clay brick 2, composite insulation board 3, aluminous castable 4, and steel shell 5, and the specific physical property parameters are shown in Table 1. According to the above parameters, a heat transfer mathematical model of molten iron in the KR stirring process including the heat transfer between the steel shell and the refractory, between the refractories, between the refractory and the molten iron, and between the molten iron and the air is established to calculate the molten iron temperature distribution, as Figure 4As shown. By processing the molten iron temperature distribution data, the constants C2 and C3 in the relational expression between the temperature drop rate of molten iron and the change of molten iron flow characteristic variables are determined to be 0.2236 and 1.4116 respectively. Through the above relational expressions, the relational expression of the molten iron temperature changing with the stirring time is determined, and the temperature of the molten iron after stirring for 10 minutes at the target working condition speed of 90 rpm is calculated to be 1618.5 K.

[0075] Table 1

[0076]

[0077] In this embodiment, the comprehensive influence of parameters such as the molten iron temperature, weight, physical size of the ladle, physical size of the stirring paddle, layout method of the refractory lining in the ladle, and heat transfer physical properties of the refractory on the change of the molten iron temperature during the KR molten iron pretreatment process is calculated. Based on the determination conditions of the present invention, the temperature of the molten iron during the KR stirring molten iron pretreatment process can be quantitatively predicted, providing a reference basis for reducing the temperature drop and improving the desulfurization efficiency.

[0078] Example 2:

[0079] The embodiment of the present invention also provides a prediction system for the molten iron temperature during the KR molten iron pretreatment process, including:

[0080] The first processing module is used to obtain the molten iron temperature, weight, physical size of the ladle, and physical size of the stirring paddle parameters during the current KR stirring molten iron pretreatment process;

[0081] The second processing module is used to establish a three-dimensional molten iron flow model during the KR stirring process according to the molten iron temperature, weight, physical size of the ladle, and physical size of the stirring paddle parameters during the current KR stirring molten iron pretreatment process;

[0082] The third processing module is used to obtain the molten iron flow data according to the three-dimensional molten iron flow model during the KR stirring process;

[0083] The fourth processing module is used to obtain the quantitative influence relational expression of the stirring paddle speed on the molten iron flow characteristic variables according to the flow data;

[0084] The fifth processing module is used to obtain the layout method of the refractory lining in the current ladle and the heat transfer physical property parameters of the refractory;

[0085] The sixth processing module is used to establish a molten iron heat transfer model during the KR stirring process according to the layout method of the refractory lining in the previous ladle and the heat transfer physical property parameters of the refractory;

[0086] The seventh processing module is used to obtain the molten iron temperature distribution data according to the molten iron heat transfer model during the KR stirring process;

[0087] The eighth processing module is configured to obtain a relationship between the molten iron temperature drop rate and the change of the molten iron flow characteristic variables according to the molten iron temperature distribution data;

[0088] The ninth processing module is configured to obtain a relationship between the molten iron temperature and the stirring time according to the quantitative influence relationship between the stirring paddle rotation speed and the molten iron flow characteristic variables and the relationship between the molten iron temperature drop rate and the change of the molten iron flow characteristic variables;

[0089] The tenth processing module is configured to obtain the temperature of the molten iron under the target working condition and time through the relationship between the molten iron temperature and the stirring time.

[0090] As an implementation manner of the embodiment of the present invention, the quantitative influence relationship between the stirring paddle rotation speed and the molten iron flow characteristic variables is:

[0091] ε = C1·n 3

[0092] Wherein, ε is the turbulent kinetic energy dissipation rate; n is the rotation speed; C1 is a constant.

[0093] As an implementation manner of the embodiment of the present invention, the relationship between the molten iron temperature drop rate and the change of the molten iron flow characteristic variables is:

[0094] k Tem = C2 + C3·ε

[0095] Wherein, k Tem is the molten iron temperature drop rate; ε is the turbulent kinetic energy dissipation rate; C2 and C3 are constants.

[0096] As an implementation manner of the embodiment of the present invention, the relationship between the molten iron temperature and the stirring time is:

[0097] T = T0 - (C2 + C1C3n 3 )t

[0098] Wherein, T0 is the initial temperature of the molten iron; n is the rotation speed; t is the stirring time.

[0099] The above-described embodiments are only descriptions of the preferred embodiments of the present invention, and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for predicting the temperature of hot metal in the KR hot metal pretreatment process, characterized in that, including: Step S1, obtaining the molten iron temperature, weight, physical dimensions of the ladle, and physical dimensions of the stirring paddle during the current KR stirring pretreatment process of molten iron; Step S2, establishing a three-dimensional flow model of molten iron during the KR stirring process according to the molten iron temperature, weight, physical dimensions of the ladle, and physical dimensions of the stirring paddle during the current KR stirring pretreatment process of molten iron; Step S3, obtaining molten iron flow data according to the three-dimensional flow model of molten iron during the KR stirring process; Step S4, obtaining a quantitative influence relationship between the stirring paddle rotation speed and the molten iron flow characteristic variables according to the flow data; Step S5, obtaining the current layout of the refractory lining in the ladle and the physical property parameters of refractory heat transfer; Step S6, establishing a heat transfer model of molten iron during the KR stirring process according to the previous layout of the refractory lining in the ladle and the physical property parameters of refractory heat transfer; Step S7, obtaining molten iron temperature distribution data according to the heat transfer model of molten iron during the KR stirring process; Step S8, obtaining a relationship between the molten iron temperature drop rate and the change of molten iron flow characteristic variables according to the molten iron temperature distribution data; Step S9, obtaining a relationship for determining the change of molten iron temperature with stirring time according to the quantitative influence relationship between the stirring paddle rotation speed and the molten iron flow characteristic variables and the relationship between the molten iron temperature drop rate and the change of molten iron flow characteristic variables; Step S10, obtaining the temperature value of molten iron under the target working conditions and time through the relationship for the change of molten iron temperature with stirring time.

2. The method for predicting the molten iron temperature in the KR hot metal pretreatment process according to claim 1, characterized in that The quantitative influence relationship between the stirring paddle rotation speed and the molten iron flow characteristic variables is: ε = C1·n 3 where ε is the turbulent kinetic energy dissipation rate; n is the rotation speed; C1 is a constant.

3. The method for predicting the molten iron temperature in the KR hot metal pretreatment process according to claim 2, characterized in that, The relationship between the molten iron temperature drop rate and the change of molten iron flow characteristic variables is: k Tem = C2 + C3·ε Among them, k Tem is the temperature drop rate of molten iron; ε is the turbulent kinetic energy dissipation rate; C2 and C3 are constants.

4. The method for predicting the molten iron temperature in the KR hot metal pretreatment process according to claim 3, characterized in that, The relationship for the change of molten iron temperature with stirring time is: T = T0 - (C2 + C1C3n 3 )t where T0 is the initial temperature of molten iron; n is the rotation speed; t is the stirring time.

5. A prediction system for the molten iron temperature in the KR hot metal pretreatment process, characterized in that, including: The first processing module is used to obtain the molten iron temperature, weight, physical dimensions of the ladle, and physical dimensions of the stirring paddle during the current KR stirring pretreatment process of molten iron; The second processing module is used to establish a three-dimensional flow model of molten iron during the KR stirring process according to the molten iron temperature, weight, physical dimensions of the ladle, and physical dimensions of the stirring paddle during the current KR stirring pretreatment process of molten iron; The third processing module is used to obtain molten iron flow data according to the three-dimensional flow model of molten iron during the KR stirring process; The fourth processing module is used to obtain a quantitative influence relationship between the stirring paddle rotation speed and the molten iron flow characteristic variables according to the flow data; The fifth processing module is used to obtain the current layout of the refractory lining in the ladle and the physical property parameters of refractory heat transfer; The sixth processing module is used to establish a heat transfer model of molten iron during the KR stirring process according to the previous layout of the refractory lining in the ladle and the physical property parameters of refractory heat transfer; The seventh processing module is used to obtain molten iron temperature distribution data according to the heat transfer model of molten iron during the KR stirring process; The eighth processing module is used to obtain a relationship between the molten iron temperature drop rate and the change of molten iron flow characteristic variables according to the molten iron temperature distribution data; The ninth processing module is used to obtain a relationship for determining the change of molten iron temperature with stirring time according to the quantitative influence relationship between the stirring paddle rotation speed and the molten iron flow characteristic variables and the relationship between the molten iron temperature drop rate and the change of molten iron flow characteristic variables; The tenth processing module is used to obtain the temperature of the molten iron under the target working conditions and time through the relational expression of the change of the molten iron temperature with the stirring time.

6. The prediction system for the molten iron temperature in the KR hot metal pretreatment process according to claim 5, characterized in that, The quantitative influence relational expression of the stirring paddle rotation speed on the molten iron flow characteristic variables is: ε = C1·n 3 Where, ε is the turbulent kinetic energy dissipation rate; n is the rotation speed; C1 is a constant.

7. The prediction system for the molten iron temperature in the KR hot metal pretreatment process according to claim 6, characterized in that, The relational expression of the molten iron temperature drop rate and the change of the molten iron flow characteristic variables is: k Tem = C2 + C3·ε where k Tem is the temperature drop rate of molten iron; ε is the dissipation rate of turbulent kinetic energy; C2 and C3 are constants.

8. The prediction system for the molten iron temperature in the KR hot metal pretreatment process according to claim 7, characterized in that, The relational expression of the molten iron temperature changing with the stirring time is: T = T0 - (C2 + C1C3n 3 )t Where, T0 is the initial temperature of the molten iron; n is the rotation speed; t is the stirring time.

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