EP1289691B2 - Method for continuously casting a metal strand - Google Patents

Abstract

The invention relates to a method for continuously casting a metal strand, especially a steel strand (1). According to the method, a strand (1) is drawn out of a cooled open-ended mold (3), is supported in a strand supporting device (7, 11) located downstream from the open-ended mold (3), is cooled by a coolant, and optionally undergoes a thickness reduction. The aim of the invention is to stipulate the formation of a desired structure of the metal. To this end, the continuous casting is carried out with online calculation while using, as a basis, an arithmetic model which describes the formation of the defined structure of the metal, whereby the variables of the continuous casting method which influence the structuring, e.g. the specific amount of coolant provided for cooling the strand, are set in an online dynamic manner, i.e. during continuous casting.

Description

The invention relates to a method for continuously casting a metal strand, in particular a steel strand, wherein a strand drawn from a cooled Durchlauflcokille supported in a continuous casting mold downstream strand support means and cooled with coolant and optionally reduced in thickness and in which method values of a simulation model are constantly counted and in the sequence on-line cooling is set.

It is a known in continuous casting requirement to adjust the cooling of a continuously cast strand so that the Stangobertlächentemperatur given values that may depend on the age of a cross-sectional element of the strand as close as possible. This is of particular importance in particular for strand delays and / or strand accelerations.

From AT-B-300.238 a method for cooling a strand emerging from a continuous casting mold is known, wherein the setpoints of the amount of cooling water, depending on the chemical composition of the strand material, the solidification time and further depending on the instantaneous integral value of the casting speed during the path of the strand be set to the respective cooling zone, so that the strand surface temperature remains pre-definable.

Furthermore, it is from the DE-C - 25 42 290 It is known to predetermine a particular temperature profile corresponding to an optimum casting speed for which the coolant quantities for cooling the strand are adjusted and to compare the measured actual casting speed with the optimum casting speed during casting and deviations of the actual casting speed from the optimum casting speed to carry out a follow-up control for the coolant quantities.

From the DE-A-2 344 438 It is known during casting by integrating the speed of individual strand sections over the term and by simultaneously holding the time spent by a strand section in the cooling area time to determine the amount of coolant applied to a single section and compare with a target amount, in this way so-called "rest -Kühlmittelmengen "to determine and keep out of this provision, the residence time of individual strand sections in the entire cooling range constant.

These known methods make it possible to correct the quantities of cooling agent which depend primarily on the casting speed, that is, casting-speed-dependent controls, but disregard the actual thermodynamic state changes of the strand. Thus, the prior art only takes into account - if the actual casting speed deviates from the casting speed for which the strand cooling is adjusted - tendencies are taken into account, but without doing justice to the actual conditions.

According to the DE-A-44 17 808 thermodynamic changes in state of the strand are considered with great accuracy in further development of the above method, so that caused by such thermodynamic changes in state, for example, the disadvantages are responsible for internal cracks or edge cracks, reliably avoided.

For this purpose, thermodynamic state changes of the entire strand, such as changes in the surface temperature, the center temperature, the shell thickness, and also the mechanical state, such as the deformation behavior, etc., are constantly included in a mathematical simulation model by solving the heat equation and it is the cooling of the strand in Depending on the calculated value of at least one of the thermodynamic state variables set, for the simulation, the strand thickness and the chemical analysis of the metal and the continuously measured casting speed are taken into account.

In the direct assembly of a continuous casting plant with a rolling mill, precipitation formation and phase transformations in the cast product depend on the cooling rate, the temperature level and the deformation kinetics. It has been observed, for example, that in the case of delayed charging of slabs into an oven, e.g. due to long transport time, surface cracks (cracks) occur on the rolled product, which are due to damage along the grain boundaries. In particular, this applies to Aluminiumnitridausscheidungen, which excrete increasingly at the grain boundaries and there obstruct the mobility of the grains to each other. Hot forming produces high stresses at the grain boundaries which, in the case of such precipitates, result in cracks after rolling. The excretion of A1N in the stable γ range depends on the temperature-time history. The phase transformation of γ into α, at temperatures between 900 ° C and 720 ° C, leads to almost spontaneous precipitation of the non-equilibrium aluminum nitrides.

In order to avoid the disadvantages associated with A1N precipitations, it is known ( EP-A-0 650 790 ), the solidified strand (slab, billet, billets) in or after the continuous casting in such a way to cool with a cooling medium that the surface temperature reaches a certain value of about 500 to 550 ° C. Subsequently, the cooling is stopped and the cooled section heats up from the inside to a resulting value.

Another cause of surface cracks are segregations of trace elements, such as S, Sn, Cu, etc., at the grain boundaries. These segregations result in hot brittleness of the rolled product after rolling. The crack intensity is directly related to the starting grain size, ie, the larger the grain, the higher will be the crack intensity. In a direct composite system, the initial grain size is generally larger than cold-charged slabs which experience complete conversion of γ to α.

Also, this effect can be positively influenced by a targeted temperature-time control, in particular, a rapid cooling to about 500 ° C, the precipitation processes favorably influenced. That Concentrated precipitation of nitrides at the austenite core boundaries is suppressed and replaced by a volume uniform distribution. Depending on the steel analysis and time of the temperature treatment, a fine pearlitic or bainitic microstructure results. Despite a low global loss of strength increases the material toughness. Local softening at the primary austenite grain boundaries is avoided and thus cracking is suppressed. The effect applies to both A1N excretions and trace elements that cause hot brittleness.

The temperature control according to the prior art usually according to theoretical predictions and calculations. The amounts of water are controlled so that at different casting speeds in about the same surface temperatures are achieved on the strand. Usually, a temperature measuring device is used as the feedback, which measures the surface temperature of the cast product before and after the intensive application of water. These values are compared with those calculated and from these the optimum amount of water is determined after appropriate tests.

The water control is thus purely coupled with the casting speed. Changes that occur due to transient conditions (short changes in speed, casting start with a cold machine, casting, etc.), can not be influenced, unless one uses a permanent temperature measurement. For this purpose, measuring instruments usually have only a low accuracy of measurement and are strongly influenced in particular by scale, which is located on the surface of the cast product. The feedback is inaccurate, a uniform intensive application of water is therefore not possible.

Another disadvantage relates to the fact that with greatly varying casting speeds the optimum length of the distance in which the strand is to be intensively cooled to achieve a certain depth of influence of intensive cooling must change and it is not sufficient to change only the amount of water , If one has only inaccurate temperature signals to specify the optimum length or depth of the influence, one never reaches a desired optimum.

The article H.P. Hougrady et al .; Possibilities and limits of a simulation of material behavior, steel and iron; Bd 116, No. 4 April 1996, pages 109 to 113, gives a basic overview of models, in particular physically based models, which can be used to describe materials science processes in the processing of metals, in particular in rolling processes. This document describes the applicability of these models to the simulation of metallurgical processes and their verification with experimental laboratory work. This makes it possible to learn fundamentally about physical models for describing phase transformations and recrystallization during roll forming. A reference to an online modeling or control of phase transformations of the metal to be cast in continuous casting plants is not given in this document.

The document C. Biegus et al .; Determination of material data for microstructure simulation, steel and iron, Bd 116 No. 5, 1996, pages 43 to 49 shows methods that allow to experimentally determine material properties that are necessary for the physically based modeling of phase transformations or recrystallization.

The DE 196 12 420 A1 describes a method for achieving improved strand cooling at varying strand speed, model parameters such as mold length, strand geometry, strand velocity, melting temperature, enthalation enthalpy and cooling water volume being taken into account for different cooling models. In preferred embodiments, the thermal model is extended with the functionality of a neural network to accommodate modeling parameters. A thermal modeling of the casting process coupled with a metallurgical modeling to influence the material properties online is not addressed here.

In the DE 197 17 615 A1 a simulation approach for describing the temperature distribution during hot rolling is described; it is the application of a purely thermal model.

According to the DE 195 08 476 A1 is a flat-rate process automation for strip casting without more details about the type of process control. In a general listing of partial models, the term grain structure is mentioned, but information on modeling approaches and the use of this sub-model are not included. There is no evidence for using simulation tools to control phase transformations according to product requirements.

According to the state of the art, steel quality is not considered. This has the consequence that some (sensitive) steel grades are overcooled and unnecessarily thermally stressed. On the other hand, with some other types of steel the desired effect of phase transformation is not achieved. In particular, it is not possible to add phase proportions to a desired extent, such as e.g. For a steel strand, ensure phase fractions of ferrite, perlite, bainite and martensite, on the cast product - before or after rolling.

A method of the type described above is known from DE 44 17 808 A1 known. In this method, thermodynamic changes in the state of the strand are taken into account in that under transient casting conditions, the surface temperatures of the strand only slightly from metallurgically required setpoints differ. This happens because the values of a simulation model are constantly included in the calculation and, as a result, the coolant quantity is set as a function of the calculated value. From the essay "IDS, TEMPSIMU, CASIM - THREE WINDOW APPLICATIONS FOR CONTINUOUS CASTING OF STEEL", presented at the 12th IAS Steelmaking Seminar, November 2-5, 1999, Buenos Aires, a method of the type mentioned is known. Specifically, an off-line solidification model IDS, an off-line steady-state heat transfer model TEMPSIMU and a dynamic on-line model CASIM, eg for calculating the sump peak and for controlling the secondary cooling are shown. The coupling of the models IDS, TEMPSIMU and CASIM is shown in FIG.

The invention aims to avoid these disadvantages and difficulties and has set itself the task of further developing a continuous casting of the type described above in such a way that it is possible to pretend as the target formation of a desired microstructure of the metal, u.zw. for metals, i. Different chemical composition in steel continuous casting for all steel qualities to be cast or steel grades. In the case of continuous steel casting, it should be possible in particular to set a specific ferrite, perlite structure and / or to avoid precipitations, such as aluminum nitride precipitations, at the grain boundaries.

This object is achieved in a method of the type described above, characterized in that the formation of a desired microstructure in the cast strand, the continuous casting is carried out under on-line calculation on the basis of a formation of the desired structure of the metal descriptive computer model, wherein the noise education influential variable the continuous casting process, such as the specific coolant quantity provided for cooling the strand, being on-line dynamically, ie adjusted during ongoing casting; and that with the computational model, thermodynamic state changes of the entire strand, such as changes in surface temperature, center temperature, shell thickness by solving the equation of heat conduction and solving an equation describing the phase transformation kinetics constantly be taken into account and the cooling of the strand as a function of the calculated value of at least one of the thermodynamic Z is set for the simulation, the strand thickness and the chemical analysis of the metal and the continuously measured casting speed are taken into account;
that a continuous phase transformation model of the metal is integrated into the calculation model, in particular according to Avrami;
and that a current temperature TA calculated by the thermal calculation model is supplied on-line to the metallurgical calculation model and this continuously calculates the desired nominal temperature TS, on the basis of which the thermal calculation model calculates and automatically sets the desired amount of water QS for the individual strand cooling sections.

By coupling the computation of the temperature of the strand with the computational model involving the formation of a particular time- and temperature-dependent microstructure of the metal, it is possible to use the variables of the continuous casting process which influence the formation of the groove, e.g. to adapt the amount of coolant to be applied to the strand surface, the chemical analysis of the metal, as well as the local temperature history of the strand. In this way, a desired microstructure in the broadest sense (particle size, phase formation, precipitations) in the near-surface region of the strand can be achieved in a targeted manner.

The Avrami equation describes in its general form all diffusion-controlled transformation processes for the respective temperature under isothermal conditions. By taking this equation into account in the calculation model, ferrite, pearlite and bainite fractions can be set in a very targeted manner during steel casting, u.zw. also taking into account a holding time at a certain temperature.

Preferably, the method is characterized in that with the calculation model thermal state changes of the entire strand, such as changes in surface temperature, the center temperature, the shell thickness, by solving the heat equation and solving a the Ausscheidungskinetik, in particular non-metallic and intermetallic precipitates, describing equation are constantly included and the cooling of the strand is set as a function of the calculated value of at least one of the thermodynamic state variables, wherein the strand thickness and the chemical analysis of the metal and the continuously measured casting speed are taken into account for the simulation, wherein advantageously the precipitation kinetics due to free phase energy and nucleation and use of thermodynamic parameters , in particular Gibb's energy, and Zener's germination is integrated into the computational model.

Appropriately Gefügcmengenverhältnisse in equilibrium states according to multi-material Diagrarnmen, in particular according to Fe-C diagram, are integrated into the calculation model.

Grain growth properties, in particular taking into account recrystallization of the metal, are preferably integrated into the calculation model. Here, dynamic and / or delayed and / or post recrystallization, i. a recrystallization, which takes place later in an oven, are taken into account in the calculation model.

Preferably, a variable of the continuous casting influencing the structure formation is a on-line reduction in thickness prior to and / or after solidification of the strand in addition to the specific coolant quantity applied to the strand so that thermodynamic rolling, for example high-temperature rolling, also takes place during continuous casting. thermodynamic rolling at a surface temperature greater than A _c3 can be considered.

Furthermore, the mechanical state, such as the deformation behavior, is also always included in the calculation model by solving further model equations, in particular by solving the heat equation.

A preferred embodiment is characterized in that quantitatively defined phase fractions are set by applying on-line calculated specific strand coolant amounts before and / or after the solidification of the strand.

Furthermore, a defined microstructure is expediently set by applying an on-line calculated strand deformation before and / or after the solidification of the strand, which causes a recrystallization of the microstructure.

An advantageous variant of the method according to the invention is characterized in that the specific final strand coolant quantity calculated after continuous casting of the strand in the end region of a secondary cooling zone in a cooling zone effecting enhanced cooling is set for the final casting phase conversion with setting of a quantitatively defined phase fraction of the strand.

The invention is explained in more detail below for the steel strand casting. An application of the method according to the invention for other metals can be carried out analogously to the following statements.

The calculation model to be used in accordance with the present invention, based on a given chemical analysis of the steel, austenite size and temperature history of the strand, calculates all the transformation temperatures and data necessary to predict and describe the transformation processes for the ferrite, perlite, bainite and martensite phase fractions.

For this purpose, a carbon equivalent for the individual alloy components is first calculated. This results in analyte-dependent starting temperatures for the ferrite transformation, for the pearlite transformation, the bainite formation and the martensite formation (on the basis of the iron / carbon diagram).

worin X der Mengenanteil der umgewandelten Phase und b und n Parameter bedeuten, die abhängig sind von der Keimbildung und dem Wachstum der gebildeten Phase. Diese Parameter b und n sind analysenabhängig und können durch Dilatometer-Versuche bestimmt werden. Im Zusammenhang mit ZTU-Diagrammen lassen sich mit Hilfe der Avrami-Gleichung sowohl die Start- und die Endzeit als auch die Temperatur für die Ferrit-, Perlit- und Bainit-Umwandlung unter isothermischen Bedingungen berechnen.Based on the Avrami equation, which describes in its general form all diffusion-controlled transformation processes for the respective temperature under isothermal conditions, basic equations for the transformation curves can be determined. $$\mathrm{X}\mathrm{=}\mathrm{1}\mathrm{-}\exp \left(\mathrm{-}\mathrm{b}\mathrm{\cdot }{\mathrm{t}}^{\mathrm{n}}\right)$$

where X is the proportion of the converted phase and b and n are parameters which are dependent on the nucleation and the growth of the phase formed. These parameters b and n are analysis-dependent and can be determined by dilatometer experiments. In the context of ZTU diagrams, the Avrami equation can be used to calculate both the start and end times as well as the temperature for ferrite, perlite and bainite transformation under isothermal conditions.

wobei t_s(T) eine virtuelle Beginnzeit der Umwandlung bei einer Temperatur T in Übereinstimmung zur tatsächlich umgewandelten Menge bedeutet.In order to take into account non-isothermal transformations, that is, to fully take into account the cooling of the strand taking place in the continuous casting plant - possibly also unevenly taking place - the fraction becomes due to the ZTU graphs stored in the computer and the dependence of the temperature as a function of time converted material, u.zw. by integrating the Avrami equation over the cooling time of the strand (see TT Pham, EB Hawbolt, JK Brimacombe: "Preciding the onset of transformation under non-continuous cooling conditions.", Application of austenite-pearlite transformation, Met. Mat. Trans A, 26A, pp. 1993-2000, 1995). $$\mathrm{X}\left(\mathrm{t}\right)\mathrm{=}{\mathrm{\int }}_{\mathrm{s}\left(\mathrm{T}\right)}\left[\mathrm{1}\mathrm{-}\exp \left(\mathrm{-}\mathrm{b}\mathrm{\cdot }{\mathrm{t}}^{\mathrm{n}}\right)\right]\mathrm{\cdot }\mathrm{dt}$$

where t _s (T) means a virtual start time of the conversion at a temperature T in accordance with the actually converted amount.

wobei G⁰ _AlN die Standard Gibb'sche Energie für die Bildung von AIN, X_A1 der Molanteil von Aluminium im Austenitvolumen und X_N der Durchschnittsstickstoffgehalt bedeuten. Die Keimbildungsrate läßt sich wie folgt berechnen: $$\mathrm{I}\mathrm{=}\mathrm{S}\mathrm{\cdot }{\mathrm{D}}_{\mathrm{Al}}\mathrm{\cdot }{\mathrm{X}}_{\mathrm{Al}}\mathrm{\cdot }\exp$$

worin S die Dichte der Keimbildung im Austenit bedeutet. $${\mathrm{\Delta }\mathrm{G}}_{\mathrm{crit}}=\frac{16\cdot \pi }{3}\frac{{\sigma }^2}{{\left(\frac{{\mathrm{\Delta }G}_{\mathit{chem}}}{V_{\mathit{AlN}}}\right)}^2}$$

gibt die Bedingung für die Keimbildung wieder. Hierin ist σ die Austenit/A1N-Grenzflächenenergie. k_B ist die Boltzmannkonstante und D_A1 das Ausbreitungsvermögen von Aluminium in Austenit.For this calculation algorithm, the temperature is defined as a function of time. Since the calculated conversion or precipitation fraction according to Avrami gives no information about the actual microstructure / quantity ratios, but only shows whether and how the equilibrium state is reached, the conversion components to the equilibrium lines from the iron / carbon are used to determine the structural component Diagram and also included in the calculation model.
Nucleation events are accounted for due to the chemical Gibbs energy in the computational model (shown below for aluminum nitrides). $${\mathrm{\Delta G}}_{\mathrm{chem}}\mathrm{=}\mathrm{\Delta }{{\mathrm{G}}^{\mathrm{0}}}_{\mathrm{AlN}}\mathrm{-}\mathrm{R}\mathrm{\cdot }\mathrm{T}\mathrm{\cdot }\left(\ln {\mathrm{X}}_{\mathrm{A}\mathrm{1}}\mathrm{+}\ln {\mathrm{X}}_{\mathrm{N}}\right)$$

where G ⁰ _{AlN is} the standard Gibbs energy for the formation of AIN, X _{A1 is} the molar fraction of aluminum in the austenite volume and X _{N is} the average nitrogen content. The nucleation rate can be calculated as follows: $$\mathrm{I}\mathrm{=}\mathrm{S}\mathrm{\cdot }{\mathrm{D}}_{\mathrm{al}}\mathrm{\cdot }{\mathrm{X}}_{\mathrm{al}}\mathrm{\cdot }\exp$$

where S is the density of nucleation in austenite. $${\mathrm{\Delta }\mathrm{G}}_{\mathrm{crit}}=\frac{16\cdot \mathrm{<figure-callout\; id="3"\; label="\pi "\; filenames="imgf0001.png"\; state="\{\{state\}\}">\pi </figure-callout>}}{3}\frac{{\mathrm{<figure-callout\; id="2"\; label="\sigma "\; filenames="imgf0001.png"\; state="\{\{state\}\}">\sigma </figure-callout>}}^2}{{\left(\frac{{\mathrm{\Delta }G}_{\mathit{<figure-callout\; id="2"\; label="chem\; V\; AlN"\; filenames="imgf0001.png"\; state="\{\{state\}\}">chem\; </figure-callout>}}}{V_{\mathit{AlN}}}\right)}^2}$$

gives the condition for nucleation again. Here, σ is the austenite / A1N interface energy. k _B is the Boltzmann constant and D _{A1 is} the spreading capacity of aluminum in austenite.

Germ growth is considered according to Zener (for example, discussed in J. S. Kirkaldy, "Diffusion in the condensed state", The Universities Press, Belfast, 1985).

The calculation process is carried out in two main stages. In the first stage, the number of germs currently formed is determined and in the second stage the growth of all previously formed precipitates is calculated.

To further explain the invention, the accompanying figure is used.

According to this, a steel strand 1 is formed from a molten steel 2 having a certain chemical composition by casting in a continuous casting mold 3. The molten steel 2 is poured from a ladle 4 via an intermediate vessel 5 and a pouring tube 6 extending from the tundish 5 into the continuous casting mold 3 by means of a pouring tube 6 formed in the casting mold 3 formed in the continuous casting mold 3. Below the continuous casting mold 3 strand guide rollers 7 are provided for supporting the steel strand 1, which still has a liquid core 8 and initially only a very thin strand shell 9.

The steel strand 1 emerging from the straight-through-die with a straight axis is deflected in a bending zone 10 into an arcuate path 11 and likewise supported therein by strand guide rollers 7. In a directional zone 12 following the arcuate path 11, the steel strand 1 is again straightened and discharged via a discharge roller table or directly reduced in thickness on-line, e.g. by means of an on-line roll stand 13.

For cooling the steel strand 1, this is cooled directly or indirectly - via strand guide rollers 7 provided with an internal cooling, whereby a certain temperature can be set on its surface up to a certain depth range.

The supply of the steel strand 1 with the amount of coolant necessary for the desired structure of the steel strand 1 via a closed or open loop by means of a computer 14. In the computer 14 are machine data m, the format f of the steel strand 1, material data, such as the chemical analysis St _ch the molten steel 2, the casting state z, the casting speed v, the liquid steel temperature t _fl , with the molten steel 2 enters the Durchlglcolcille 3, and the desired microstructure α / γ and optionally a deformation w of the steel strand 1, the way the strand guide is performed. This deformation can for example also be given by the straightening of the steel strand 1 in the straightening zone 12.

In the computer 14 is calculated using a metallurgical calculation model, which takes into account the phase conversion kinetics and nucleation kinetics according to the above-mentioned computational models, and a thermal calculation model that allows the temperature analysis due to the solution of the heat equation, a target amount of water Q _s , u.zw. due to the current, already applied amount of water Q _A , which is also entered into the computer.

A solution of the heat equation by means of a process computer is state of the art and eg in the DE-C2 - 44 17 808 discussed in detail for the continuous casting. As a way to solve the heat equation equation, the finite difference method is given with Lagrangian description.

The metallurgical calculation model takes into account the current steel analysis St _ch in order to meet different material behavior. The current temperature T _A calculated by the thermal calculation model is supplied on-line to the metallurgical calculation model and this continuously calculates the desired setpoint temperature T _s , on the basis of which the thermal calculation model calculates and automatically sets the setpoint water quantity Q _s for the individual strand cooling sections.

Claims (10)

1. Method for the continuous casting of a metal strip, in particular of a steel strip (1), wherein a strip (1) is extracted from a cooled open-ended mould (3), is supported in a strip-supporting means (7, 11) arranged downstream of the open-ended mould (3) and is cooled with a coolant as well as optionally reduced in thickness and in which method values of a simulation model are permanently included in the calculation and, subsequently, cooling is adjusted on-line, characterized in that, to form a desired texture within the cast strip, continuous casting is carried out by an on-line calculation based upon an arithmetic model describing the formation of the desired texture of the metal, wherein variables of the continuous casting method affecting the formation of the texture, such as, e.g., the specific amount of coolant provided for cooling the strip, are adjusted in an on-line dynamic fashion, i.e. while casting takes place; in that thermodynamic changes of state of the entire strip such as changes in surface temperature, central temperature, shell thickness are permanently included in the calculation of the arithmetic model by solving the heat conduction equation and solving an equation describing the phase transition kinetics and the cooling of the strip is adjusted as a function of the calculated value of at least one of the thermodynamic state quantities, wherein, for simulation, the strip thickness and the chemical analysis of the metal as well as the continuously measured casting rate are taken into account; in that a continuous phase transition model of the metal is integrated in the arithmetic model, in particular in accordance with Avrami; and in that a current temperature T_A, calculated by the thermal arithmetic model, is fed online to the metallurgical arithmetic model and the latter continuously calculates the desired setpoint temperature T_S, on the basis of which the thermal arithmetic model calculates and automatically sets the setpoint amount of water Q_S for the individual strip cooling sections.
2. Method according to Claim 1, characterized in that thermal changes of state of the entire strip such as changes in surface temperature, central temperature, shell thickness are permanently included in the calculation of the arithmetic model by solving the heat conduction equation and solving an equation describing the precipitation kinetics, in particular of nonmetallic and intermetallic precipitations, and the cooling of the strip is adjusted as a function of the calculated value of at least one of the thermodynamic state quantities, wherein, for simulation, the strip thickness and the chemical analysis of the metal as well as the continuously measured casting rate are taken into account.
3. Method according to Claim 2, characterized in that the precipitation kinetics due to free phase energy and nucleus formation and the use of thermodynamic primary quantities, in particular Gibbs' energy, and the nucleus growth according to Zener are integrated in the arithmetic model.
4. Method according to one or several of Claims 1 to 3, characterized in that quantitative relations of texture in conditions of equilibrium according to diagrams of multicomponent systems, in particular according to the Fe-C diagram, are also integrated in the arithmetic model.
5. Method according to one or several of Claims 1 to 4, characterized in that grain growth characteristics, especially in consideration of the recrystallization of the metal, are integrated in the arithmetic model.
6. Method according to one or several of Claims 1 to 5, characterized in that, as a variable of continuous casting affecting the formation of the texture, a reduction in thickness occurring during the discharge of the strip is adjusted on-line prior to and/or after complete solidification of the strip in addition to the specific amount of coolant supplied to the strip.
7. Method according to one or several of Claims 1 to 6, characterized in that the mechanical state such as the deformation behaviour is also permanently included in the calculation of the arithmetic model by solving further model equations, in particular by solving the heat conduction equation.
8. Method according to one or several of Claims 1 to 7, characterized in that quantitatively defined phase portions are adjusted prior to and/or after complete solidification of the strip by applying specific amounts of strip coolant, which have been calculated on-line.
9. Method according to one or several of Claims 1 to 8, characterized in that a defined texture is adjusted prior to and/or after complete solidification of the strip by applying a strip deformation, which has been calculated on-line and causes recrystallization of the texture.
10. Method according to one or several of Claims 1 to 8, characterized in that a final phase transition, optionally in consideration of a subsequent retransition, is adjusted after complete solidification of the strip in a cooling zone causing enhanced cooling.

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