Method for determining amount of bainite ferrite formed during steel processing operation, associated monitoring or control method

Abstract

The method comprises:-s1) determining a bainite ferrite growth rate, the bainite ferrite growth rate being proportional to the activation energy of the transformation of austenite to bainite ferrite, and the bainite ferrite growth rate being proportional to an adjustment coefficient, the free enthalpy of the bainite ferrite phase being close to the free enthalpy of the austenite phase, and the free enthalpy of the austenite phase being close to the free enthalpy of the austenite phase; the adjustment coefficient is close to zero, and the free enthalpy of the austenite phase depends on the carbon content in the austenite phase; the method comprises the following steps: (1) determining a bainitic ferrite growth rate, (2) determining a cementite growth rate at least as a function of the carbon content in the austenite phase, (3) determining values of bainitic ferrite, austenite and cementite phase fractions at the next time step based on the bainitic ferrite growth rate and the cementite growth rate, and updating the carbon content in the austenite phase based on the values of the phase fractions.

Description

TECHNICAL FIELD

[0001] The technical field relates to phase transformation determination, in particular bainite ferrite formation prediction, of steel semi-finished products undergoing steel processing operations. Such predictions are particularly useful for monitoring, controlling, designing or adjusting such steel processing operations. BACKGROUND

[0002] Recent developments of steels for automotive and other applications led to considering bainitic microstructure as a good candidate to provide an alternative balance of strength and ductility. Therefore, being able to determine how much bainite forms in a steel undergoing cooling or, more generally, a heat treatment, is very useful for better controlling the bainite content of the steel finally obtained. Being able to determine the bainite growth rate in a steel is also very useful for controlling the cooling operation itself or for controlling the heat treatment. In fact, since bainite formation is exothermic, considering how much bainite forms enables a more accurate temperature control to be achieved.

[0003] With regard to bainite formation, different models have been developed in the last years to predict the Time-Temperature-Transformation (TTT) curve, or to predict bainite formation kinetics and final fraction. Some of these models perform well for so-called "carbide-free" steel grades (for "carbide-free" steel grades, no or almost no cementite forms due to high silicon or aluminum content), but are less accurate for steel grades with low silicon content. The article "Modelling Simultaneous Formation of Bainitic Ferrite and Carbide in TRIP Steels" by Fateh Fazeli and Matthias Militzer (ISIJ International, Vol. 52, No. 4, pp. 650-658, 2012, Print ISSN 0915-1559) describes a method for predicting the bainite fraction formed during cooling for high silicon content. Other models predict bainite formation well for poor-silicon steels, in which there can be significant carbide precipitation, but are less accurate for carbide-free steel grades, in particular with regard to the final bainite fraction.

[0004] In this context, there is a need for a method that enables determining how much bainite forms in a steel with low silicon content and "carbide-free" steel grades, and that has a good balance between calculation time and accuracy. B SUMMARY SUMMARY

[0005] This invention is achieved by providing a method for determining the amount of bainitic ferrite formed in a steel semi-finished product during steel processing operations, the steel semi-finished product having a chemical composition CC, the method comprising the following steps performed by an electronic device:

[0006] - Obtain the chemical composition (CC) of the steel in the semi-finished steel product.

[0007] - s1) Determine the bainitic ferrite growth rate, which is proportional to the following:

[0008] ○ Density of bainitic ferrite nucleation centers

[0009] ○ Where T is the temperature of the steel, R is the universal gas constant, and The activation energy for the transformation from austenite to bainitic ferrite, and the growth rate of said bainitic ferrite are proportional to the following:

[0010] ○ Adjustment coefficient, which is the difference between the free enthalpy of the bainitic ferrite phase and the free enthalpy of the austenitic phase. When the coefficient of adjustment approaches zero, the enthalpy of the austenitic phase depends at least on the carbon content in the austenitic phase.

[0011] - s2) Determine the cementite growth rate at least based on the steel's chemical composition (CC) and the carbon content in the austenite phase.

[0012] - s3) Based on the growth rates of bainitic ferrite and cementite, determine the phase fractions of bainitic ferrite, austenite, and cementite at the next time step, and based on the phase fractions, determine the carbon content in the austenite phase at the next time step.

[0013] The group consisting of steps s1, s2, and s3 is executed sequentially several times.

[0014] In the calculation of bainitic ferrite formation, when the free enthalpy in the bainitic ferrite phase approaches that in the austenitic phase, the adjustment coefficient used in the required method slows down this formation. This allows for obtaining a final bainitic ferrite fraction in "carbide-free" steel grades that is in good agreement with experimental results. Furthermore, at the onset of bainite formation, when the difference between the free enthalpies is large, this adjustment coefficient does not significantly alter the formation kinetics. This also allows for good consistency regarding the formation kinetics.

[0015] This adjustment factor primarily reflects the carbon content-driven balance between the bainitic ferrite and austenitic phases. For silicon-depleted steels, cementite precipitation alters the carbon content in the austenitic phase, thus changing the balance under discussion. Therefore, considering this carbon content-driven balance (through the adjustment factor) and cementite formation (if cementite precipitates) allows for a final bainitic ferrite fraction that is well-predicted and measured for both carbide-free steels and steels with lower silicon content.

[0016] Specifically, in this method, the calculation The carbon content in the bainitic ferrite phase can be the same as that in the austenitic phase to test the favorableness of the transformation from austenite to bainitic ferrite, and if not favorable, to adjust the bainitic ferrite growth rate accordingly.

[0017] The method may also include, individually or in combination, the features of any one of claims 2 to 10.

[0018] The present invention also relates to a method for monitoring or controlling steel processing equipment according to any one of claims 11 to 17. It also relates to an electronic device according to claim 18. The present invention further relates to a computer program according to claim 19 to be executed on a computer (depending on the details of the method performed by said computer, which is connected, where appropriate, to a temperature sensor, actuator, or human-machine interface of the steel processing equipment, or a production database). Attached Figure Description

[0019] The invention will now be described and illustrated in detail by way of example, without introducing limitation, with reference to the accompanying drawings:

[0020] - Figure 1 The phase fractions in steel at the initial and final times of the phase transformation are schematically shown.

[0021] - Figure 2 The phase fractions in steel at different times during other phase transformations are schematically shown.

[0022] - Figures 3 to 5 The test results of isothermal transformation and the calculation results determined according to the present invention are shown for three exemplary carbide-free bainitic steel grades.

[0023] - Figure 6 The following table shows test results plotted relative to the calculated results for some silicon-poor steel grades.

[0024] - Figure 7 The following are test results plotted relative to the calculations determined according to the present invention for these silicon-poor steel grades.

[0025] - Figure 8 andFigure 9 This paper summarizes the test results plotted relative to the calculation results for both carbide-free bainitic steel and silicon-depleted steel.

[0026] - Figure 10 The illustration schematically depicts the steps performed according to one embodiment of the invention to determine the amount of bainitic ferrite formed during steel processing operations.

[0027] - Figure 11 The steps performed, according to another embodiment, to determine the amount of bainitic ferrite formed during steel processing operations are illustrated schematically.

[0028] - Figure 12 The diagram schematically illustrates a steel processing equipment to be monitored or controlled using the method according to the invention.

[0029] - Figure 13 and Figure 14 This summarizes control methods using the control method according to the present invention or prior art. Figure 12 Production data used for production on steel processing equipment. Detailed Implementation

[0030] Bainite formation

[0031] In the method and apparatus according to the invention, the amount of bainitic ferrite formed in the steel semi-finished product during steel processing operations is determined by performing the following steps:

[0032] - Obtain the chemical composition (CC) of the steel in the semi-finished steel product.

[0033] - s1) Determine the bainitic ferrite growth rate, which is proportional to the following:

[0034] ○ Density of bainitic ferrite nucleation centers ,

[0035] ○ Where T is the temperature of the steel, R is the universal gas constant, and The activation energy for the transformation from austenite to bainitic ferrite, and

[0036] ○ Adjustment coefficient C mod When the free enthalpy of the bainitic ferrite phase α is close to that of the austenitic phase γ, the adjustment coefficient C mod Approaching zero, the enthalpy of the austenitic phase depends at least on the carbon content in the austenitic phase γ. ,

[0037] - s2) At least based on the steel's chemical composition (CC) and the carbon content in the austenitic phase. Determine the cementite growth rate.

[0038] - s3) Based on the growth rates of bainitic ferrite and cementite, determine the phase fractions of bainitic ferrite, austenite, and cementite at the next time step. , and The value, and based on the phase fraction , , The value determines the carbon content in the austenite phase at the next time step. The value of .

[0039] Steps s1, s2, and s3 are executed sequentially several times to consider the possible carbon redistribution in the three possible phases at each time step (by calculating the carbon content in the austenitic phase at each time step). The time evolution of the bainitic ferrite content in the steel during the steel processing operations under discussion was gradually determined, along with the effect of this redistribution on the growth rates of bainitic ferrite and cementite.

[0040] Figure 1 This schematically illustrates the effects of high silicon content (e.g., 1.5% by weight or more) on CFB-type (carbide-free bainitic) steels at temperatures below the bainite initiation temperature T. B (and higher than the martensite initiation temperature T) M The initial time t for a phase transition to occur at a temperature of ) o and final time t f Phase fraction in steel at initial time t. o In this simplified example, it is assumed that only austenite exists, where the initial carbon content in the austenite phase is... Then some bainitic ferrite forms until time t. f The transformation stops (because equilibrium is reached in this case). During this transformation, carbon is redistributed: it moves from the bainitic-ferrite phase α (where the carbon content is...) carbon content in the austenitic phase Compared to the negligible amount, carbon is repelled into the austenite phase γ. Therefore, the carbon content in the austenite phase... Gradually increasing.

[0041] When calculating the bainitic ferrite growth rate as described above, the adjustment coefficient C mod This allows for the slowing of bainite-ferrite formation as the carbon content in the austenite phase increases during the transformation process, thus enabling the acquisition of a final fraction of untransformed austenite that is in good agreement with experimental results (which is not zero for CFB steel).

[0042] The difference between the free enthalpy of the bainitic ferrite phase and the free enthalpy of the austenitic phase is denoted as . This represents the free enthalpy change during the diffusionless transformation from austenite to bainitic ferrite. Here, it is used to calculate... The carbon content values ​​in the bainitic ferrite phase and the carbon content in the austenitic phase The values ​​are the same. In other words, The difference between the free energy of the austenitic phase and the free energy of the bainitic ferrite phase, which is the result of a phase transformation from austenitic to bainitic ferrite without a change in carbon content during the austenitic phase transformation, is used to assess whether a transformation can occur.

[0043] Here, when When it approaches zero, the adjustment coefficient C mod and Approximately proportional (e.g., when) When less than 0.2, compared with Proportional or even equal to (within 5% or less). This makes when Approaching zero significantly slows down the formation of bainite and ferrite. Furthermore, when... When the value is high (e.g., above 2), the adjustment coefficient C mod The adjustment coefficient is constrained and limited to a constant value. This prevents the adjustment coefficient from altering the bainite formation kinetics at the onset of the transformation and allows for good agreement with experimental results regarding the formation kinetics.

[0044] To meet these criteria, the adjustment coefficient C mod For example, it is calculated as equal to .

[0045] Figure 2 The diagram schematically illustrates the initial time t of the phase transition. o Final time t f And two intermediate times t1 and t2 (where t f >t2>t1>t o The phase fraction in steel at that time. For steels with very low silicon content (e.g., less than 0.1 wt%), this transformation occurs below the bainite initiation temperature T. B (and higher than the martensite initiation temperature T) M At a temperature of ), it is highly likely that cementite (carbide) will precipitate. At the initial time t o Only the austenitic phase γ exists, with an initial carbon content of Then some bainitic ferrite α forms, and some carbon in the austenitic phase is thus repelled, where the carbon content is... Increase until the carbon content reaches the threshold for cementite precipitation (at time t1). Then the cementite phase C grows (time t2). When the carbon content C in the cementite phase... c At high concentrations (approximately 6.67% by weight), cementite formation is dependent on carbon content. It has a pumping effect and tends to significantly reduce the carbon content in the austenitic phase. Therefore, when When kept low, the adjustment coefficient C mod The austenite remains non-zero and non-negligible, and the transformation from austenite to bainitic ferrite continues until no more austenite exists (at time t). f hour).

[0046] In the methods presented above, the formation of cementite (depending on the chemical composition CC of the steel) during steel processing operations is taken into account, and the cementite formation pumps carbon from the austenite phase, making it possible to predict a sufficient final bainitic ferrite fraction for both carbide-free steels and steels with low silicon and aluminum content (for which the final retained austenite fraction is typically very low or even zero).

[0047] In step s2, depending on the steel's chemical composition CC (especially for compositions with high silicon or aluminum content), the cementite growth rate can remain zero throughout the steel processing operation. Alternatively, conversely, for compositions with low silicon and aluminum content, it can become non-zero during the transformation. Specifically, this depends on the carbon content in the austenite phase. Maintain a carbon content below the threshold for cementite precipitation mentioned above. The cementite growth rate can then be kept at zero.

[0048] Bainite is a microstructure consisting of very thin plates of ferrite that may be separated by retained austenite. It forms within austenite. In this document, the ferrite in these thin plates of ferrite is referred to as bainitic ferrite (or more simply bainite). When cementite forms, it is assumed here that it forms within austenite (and then there is a carbon pumping effect on the austenite, as mentioned above). Figure 2 (as described).

[0049] Steel machining operations that determine the amount of bainitic ferrite are those operations that may form bainite. These operations typically include:

[0050] - For the aforementioned processing operation, the steel is subjected to a high temperature for a period of time, typically above AC3, and then contains a significant fraction of austenite, for example, greater than 50% by weight or even greater than 70% by weight, with the remainder being primarily ferrite.

[0051] - Or, for the processing operation, the steel initially contains such a significant fraction of austenite (the remainder being mainly ferrite).

[0052] Then, during this processing operation, the temperature of the steel decreases and becomes below the bainite initiation temperature T. B Then bainite is formed, and its formation kinetics are determined as described above.

[0053] Phase fraction , , The stepwise calculation of time evolution begins with what is usually... , and The initial conditions, where if the steel initially contains 100% austenite (and no ferrite), then This iterative calculation can be performed step by step until the endpoint of the transition. This endpoint can correspond to the case where the phase fraction reaches a constant steady-state value (i.e., "static"), corresponding to... Figure 1 and Figure 2 The final time t f This can also correspond to the moment when the steel processing operation ends (e.g., when the steel semi-finished product is output from the steel processing equipment that processes the steel semi-finished product).

[0054] The steel processing operations discussed can be hot rolling operations, including, for example, steel cooling operations performed on the output roller table.

[0055] Steel semi-finished products can be steel strip or plate, slab, billet, broom, ingot, bar, beam, pipe or wire. More generally, steel semi-finished products are intermediate source products that are subsequently destined for the manufacture of parts, articles or buildings.

[0056] The chemical composition (CC) of steel is considered to determine the amount of bainitic ferrite that forms, and can be indicated by the weight percent (wt%) of the different alloying elements present in the steel (e.g., C, Mn, Si, Al, Cr, Cu, Mo, Ni). The content of these alloying elements is the initial content in the steel at the start of the steel processing operation. The carbon content of the chemical composition CC can be more specifically defined as the initial carbon content in austenite. This is C. o .

[0057] If a ferrite transformation occurs, the ferrite fraction will be higher than the bainitic transformation modeled in this paper before the ferrite transformation begins. Non-zero, and the initial austenite fraction Less than 1. Under such circumstances, the initial carbon content C in the austenitic phase is... o Calculated as equal to ,in The carbon content in steel before the ferrite transformation occurs (in other words, Corresponding to the average overall carbon content of steel; corresponding to its overall chemical properties.

[0058] The calculation steps described in more detail below are sufficient to calculate the amount of bainitic ferrite formed during steel processing operations (in other words, the amount of bainite). They can be combined with additional steps to further consider the possible formation of other types of phases.

[0059] In this method for determining the amount of bainitic ferrite formed during such steel processing operations, the carbon content in the austenitic, bainitic ferrite, or cementite phase can be expressed as a weight percentage (wt%), mass concentration, molar concentration, or any other amount representing the carbon density in the phase. Regarding the aforementioned phase fraction, it is hereby referred to as a volume fraction.

[0060] Step s1 : Determination of bainite ferrite growth rate

[0061] In the method described herein, the bainitic ferrite growth rate is calculated according to the following equation eqn 1:

[0062]

[0063] in

[0064] - This represents the volume fraction of bainite ferrite in steel.

[0065] - ν=kT / h=10 13 Second -1 (k is Boltzmann's constant, and h is Planck's constant).

[0066] - λ is the size of the austenite grain. A proportional autocatalytic coefficient, and

[0067] - equal , or possibly equal to .

[0068] item (For example, in the absence of cementite and ferrite (i.e., if...) In the case of ), it equals This reflects that as bainitic ferrite forms, the number of possible nucleation sites gradually decreases as the amount of austenite decreases.

[0069] The autocatalytic coefficient λ is expressed as: For the steel grades considered here (whose alloying element content is included in the range further specified below), 0.1 μm -1 Up to 0.8 μm -1 or even 0.1 μm -1 up to 0.5 μm -1 The value of "a" is sufficient.

[0070] In this model, the density of bainitic ferrite nucleation centers Calculate based on the following equation:

[0071]

[0072] in This is a quantity related to the density of defects at grain boundaries that are conducive to the growth of bainitic ferrite. It depends on the steel's chemical composition (CC) and austenite grain size. However, it does not depend on temperature T, nor on the instantaneous carbon content in the austenitic phase. . More specifically, it can be based on the following equation (where... (Expressed in meters) Determined:

[0073]

[0074] in The rate parameter for martensite formation depends on the steel's chemical composition CC, where Kst is 1.10. -9 Rice up to 100.10 -9 The constant coefficient of meters. It can be determined more specifically according to the following equation, where With K -1 express:

[0075]

[0076] Where x Mn x Ni x Cr x Mo x Si and C o The contents of manganese, nickel, chromium, molybdenum, silicon, and carbon in the chemical composition CC, expressed as % by weight, are respectively.

[0077] Activation energy for the transformation from austenite to bainitic ferrite It is calculated here as equal to or substantially equal to , and Q o K1 can depend on the chemical composition CC of the steel, but during the phase transformation of the steel, when the carbon content in the austenite phase... As Q changes over time o Keep K1 constant. "Equivalent" means within 10%, or even within 5% or 3%. The inventors have noted that this calculation... This approach leads to good agreement between model predictions and experimental observations regarding kinetics and final phase fraction. Furthermore, this formula offers the following advantages: Zhong Sui The part that changes and therefore must be recalculated at each time step (i.e. )and China is independent Part of Q o Separated. Furthermore, with The changing term and the adjustment coefficient C mod The terms in the expression are the same, and therefore due to this expression This special method requires only one calculation to determine the bainitic-ferrite growth rate. In practice, Q... o The value of K is typically between 150 kJ / mol and 200 kJ / mol. And the value of K1 is between 3 and 10, or even between 5 and 7.

[0078] Quantity Q o It depends on the chemical composition (CC) of the steel. The inventors have observed that by using Q... o The calculation is equal to or substantially equal to A + B. (TT) M (A and B are two constants, and T) M (where Q is the martensitic initiation temperature) can be conveniently considered. o Dependence on the chemical composition CC. In other words, the inventors have noted that this expression fits Q well. o The value of Q. In this expression, Q o Dependence of chemical composition CC on T M The dependence on the chemical composition CC is reflected in the data and studies available on this dependence. In practice, the value of the constant A is typically between 160 kJ / mol and 200 kJ / mol, while the value of B is typically between 100 J / (mol·K) and 150 J / (mol·K). For example, referring to the attached figure, the tests presented below were performed with A = 177 kJ / mol, B = 120 J / (mol·K), and K1 = 6.

[0079] For a given chemical composition, the martensite initiation temperature T M The value of can be determined experimentally using the expansion determination method. It can also be found in data from the literature. It can also be determined using the following equation (applicable to the further defined range of alloying element contents below), where T M In degrees Celsius (°C):

[0080]

[0081] Similarly, the bainite initiation temperature T BThe value of can be determined by expansion determination and microstructure analysis experiments, or found in data from the literature. It can also be determined using the following equation (applicable to the further defined range of alloying element contents below), where T B In °C:

[0082]

[0083] Where x Mn x Si x Cr x Ni x Mo and C o These represent the contents of manganese, silicon, chromium, nickel, molybdenum, and carbon, expressed as a percentage by weight, corresponding to the chemical composition (CC) of the steel.

[0084] Regarding austenite grain size To calculate the bainite growth rate, it can be measured from samples taken from steel semi-finished products before processing, or from samples from another group of semi-finished products (produced during the same production activity). Alternatively, grain size... It can also be calculated based on the characteristics of previous processing (before the current steel processing operation) experienced by the semi-finished steel. It can also be determined using lookup tables based on these previous process characteristics. In summary, grain size... In this technical field, the average diameter of a grain is typically defined. Geometrically, it is determined using a method known as the intercept method: numerous vertical and horizontal lines are drawn in an image of the sample; then, the grain size (width) along that line is determined whenever the line crosses a grain boundary. This yields the vertical average and the horizontal average. The average of these two averages is the grain size. .

[0085] Considering that this is used for and The expression for the bainite growth rate is written as (eqn 1a):

[0086]

[0087] In equation eqn 1a, the quantities that change or may change during the transition, and the quantities whose values ​​are updated at each time step, are:

[0088] - Bainitic ferrite phase fraction ,

[0089] - Temperature T (which may change during the transition).

[0090] - and Its changes are mainly due to the carbon content in the austenite phase. The changes were caused by [the following].

[0091] It is worth noting that the other parameters of eqn 1a remain constant during the transition.

[0092] about (Its follow) (It changes with the changes), which is calculated using the following method:

[0093] - Enthalpy of free space of a single austenitic phase, given the carbon content in that phase. And for the content of other elements, such as x Mn x Si x Mo …, given the chemical composition of the steel (CC).

[0094] - The free enthalpy of a single ferrite phase, given the elemental content (x) specified by the chemical composition CC of the steel. Mn x Si x Mo …)

[0095] - and subtract one from the other.

[0096] In the implementation described herein (which corresponds to the test results presented below), the carbon content value in the (bainitic) ferrite phase (used for calculation) ) and carbon content in the austenitic phase The values ​​are the same. In other words, when calculating the free enthalpy of the ferrite phase under discussion, it is assumed that:

[0097] - Element content (x) Mn x Si x Mo …) is the same as that in the austenitic phase.

[0098] - And the carbon content is also the same as that in the austenitic phase.

[0099] therefore It refers to the enthalpy difference between the austenitic phase γ and the (bainitic)ferrite phase, resulting from the transformation of the austenitic phase into the ferrite phase while maintaining the same carbon content and the same content of other elements (i.e., while keeping the steel composition constant); in other words, This is the enthalpy difference of the so-called "displacement" transformation from austenite to bainitic ferrite. It differs from the enthalpy difference of the so-called "quasi-equilibrium" phase transformation, for which the free enthalpy of the austenitic phase and the free enthalpy of the bainitic ferrite phase are calculated using different carbon contents of the austenitic phase and the carbon contents of the bainitic ferrite phase (and more accurately, the equilibrium carbon contents of the two phases).

[0100] It should be noted that this is only for calculating the same carbon content value for both the austenitic and bainitic ferrite phases. (For calculating transformation kinetics). In the actually formed bainitic phase α, the carbon content... Unlike the carbon content in the austenitic phase γ As described below in the description of step s3, calculate and update. and The corresponding value.

[0101] These values ​​of free enthalpy can be calculated, for example, using commercial thermodynamic calculation software such as ThermoCalc.

[0102] Step s2: Determination of cementite growth rate

[0103] As mentioned above, as long as the carbon content in the austenite phase... Below the carbon content threshold for cementite precipitation The cementite growth rate remains zero.

[0104] Carbon content in the austenitic phase Once the threshold discussed is exceeded, cementite forms in the austenite.

[0105] Carbon content threshold for cementite precipitation This can be determined from the following article: “Effect of partitioning of Mn and Si on the growth kinetics of cementite in tempered Fe–0.6 mass% C martensite”, Miyamoto, JC Oh, K. Hono, T. Furuhara and T. Maki, Acta Materialsalia, Vol. 55, No. 15, 2007, pp. 5027-5038. Specifically, Table 5 of this article provides the values ​​of the enthalpy of formation of the M3C compound (M being an alloying element present in the steel, such as Si or Cr), from which the enthalpy of formation of cementite in the austenite of the steel under consideration, ΔrG (based on the chemical composition CC and under pre-equilibrium assumptions), can be calculated. This allows for the determination of the carbon content threshold for cementite precipitation. As an example, this article... Figure 10 The carbon concentration limit for the presence of the cementite phase (θ) is provided as a function of Si or Mn content (here it will be...). Figure 10 The "PE" lines in a and b are assumed to be "quasi-equilibrium".

[0106] The cementite growth rate can be calculated from the following article: “Modelling upper and lower bainite transformation in steels”, M. Azuma, N. Fujita, M. Takahashi, T. Lung, ISIJ International, Vol. 45 (2005), No. 2, pp. 221-228, specifically as described in Sections 3.3 and 3.4 of that article. Information regarding cementite nucleation growth provided by Miyamoto in a previous article (see Table 4 and eqn 2-4 of Miyamoto's article) can also be used for cementite growth calculations.

[0107] Step s3: Determination of carbon content in austenite phase

[0108] In step s3, relative to Ignoring the carbon content in the bainitic ferrite phase At the same time, and the carbon content C in the cementite phase c Calculate the carbon content in the austenite phase under constant conditions (equal to 6.67 wt%). .

[0109] Considering the initially proposed total carbon conservation, then calculate according to the following equation :

[0110]

[0111] in , or can .

[0112] The effective range of the above calculation method (for both bainitic ferrite and cementite formation) is as follows, expressed in weight %:

[0113] - C o ≤0.5 or even ≤0.3, ≤0.25, or ≤0.2

[0114] - x Mn ≤3 or even ≤2.5, or ≤2

[0115] - x Si ≤2, or even 1.5

[0116] - x Al ≤1.5

[0117] - x Cr ≤4, or even ≤1, or ≤0.8

[0118] - x Mo ≤0.8 or even ≤0.5

[0119] - x Ni ≤2.

[0120] Within the aforementioned range, the above numerical formulas (e.g., those applicable to calculating T) B or T M The formula provides effective predictions. Furthermore, within these ranges, the overall method for determining the amount of bainite formed produces fairly accurate predictions, as illustrated by the exemplary experimental test results presented below.

[0121] Exemplary test results

[0122] Carbide free bainitic steel grades

[0123] exist Figures 3 to 5 China and still Figure 8 and Figure 9 The experiment shows the results for steel grades with high silicon or aluminum content, for which no carbide precipitation occurs (or occurs very slowly during the transformation).

[0124] The transformation under consideration is an isothermal transformation.

[0125] The chemical composition, isothermal temperature, and grain size of these steel grades are summarized in Table 1. For each composition, the remainder (besides the elements already specified in Table 1) consists of iron and unavoidable impurities produced during smelting. The carbon content specified in Table 1 is the initial carbon content C0 in austenite. No ferrite transformation occurs in the steel prior to these bainitic (isothermal) transformations. Bainitic-ferrite fraction The measurements were performed using a synchrotron.

[0126]

[0127] Table 1: Steel Grades Tested by CFB

[0128] Figure 3 , Figure 4 and Figure 5 These represent the bainite-ferrite fractions of steel grades g2, g5, and g4 in Table 1 at their respective isothermal transformation temperatures of 380℃, 550℃, and 400℃. The change over time t (in seconds).

[0129] exist Figures 3 to 5 In the diagram, measured values ​​are represented by ordinary line curves, while predicted values ​​using the method described above are represented by long dashed lines. The dotted dashed lines correspond to the predictions calculated without an adjustment factor (i.e., when 1 is used instead of the adjustment factor).

[0130] Figure 3 andFigure 4 This indicates that, compared to predictions made without considering this moderating effect, using the moderating coefficient C... mod This improves the accuracy of predictions regarding the final bainite-ferrite fraction. Figures 3 to 5 It also shows that the calculation methods presented above achieve acceptable, or even good, consistency with the formation dynamics.

[0131] Steel grades with cementite (carbide) precipitation

[0132] Figure 6 and Figure 7 The test results shown correspond to steel grades with a low silicon content of 0.01 wt% or less, which exhibit carbide precipitation during the transformation. The transformation considered is an isothermal transformation.

[0133] These steels were homogenized at 1200°C for 72 hours and then air-cooled. A ferrite-pearlite microstructure was then formed at ambient temperature, and a special treatment (double annealing, first at 890°C for 1 minute, then at 1100°C for 1 minute) was applied to remove as much of the initial microstructure as possible and form a relatively uniform microstructure with large austenite grain sizes. The temperature was then set to the isothermal test temperature used to test bainite formation. The grain sizes indicated in Table 2 are the grain sizes used for bainite transformation calculations. For these tests, the measured grain size averaged 50 micrometers, ranging from 35 to 60 micrometers.

[0134] No ferrite transformation occurs in the steel prior to the bainitic (isothermal) transformation shown below.

[0135] The chemical composition, isothermal temperature, and grain size of these steel grades are summarized in Table 2.

[0136]

[0137] Table 2: Test steel grades with potential cementite precipitation

[0138] Figure 6 and Figure 7 This represents the total fraction of austenite that has been transformed after reaching a static state during the transformation (i.e., , here equals ), expressed as %. In Figure 7 In the diagram, the measured fractions (vertical axis) are plotted relative to the fractions calculated using the method described above (horizontal axis). Figure 6 In the figures, the measured fraction (vertical axis) is plotted against the calculated fraction (horizontal axis) calculated according to the method described above but without considering possible cementite formation (i.e., without step s2). In each figure, the straight line (y=x) corresponds to the ideal, accurate prediction.

[0139] exist Figure 6 In the test results enclosed by long dashed lines, austenite actually transforms completely into bainitic ferrite and cementite during the transformation, while Figure 6 The model (which does not consider cementite formation) only predicts a partial transformation of austenite. Conversely, for the test in question, Figure 7 The model (corresponding to the calculation method detailed above) adequately predicted the complete austenitic transformation and was in good agreement with experiments, thus demonstrating the usefulness of steps s2 and the carbon redistribution calculations. More generally, Figure 7 The results show that the methods described above for determining the amount of bainitic ferrite (and cementite) formed during the transformation produce final scores that are in good agreement with experiments. For high Mn content tests (steel grade g9), the agreement is less favorable than with other tests. Therefore, for non-CFB steel grades, if high accuracy is required, the methods discussed can preferably be used for Mn contents equal to or less than 2.5% by weight, or even equal to or less than 2% by weight (rather than at x%). Mn (≤3% by weight across the entire range).

[0140] Overall results for CFB and non-CFB steel grades

[0141] Figure 8 and Figure 9 The test results of both CFB steel grades g1 to g5 and non-CFB steel grades g7 to g12 are summarized.

[0142] Figure 8 This represents the total fraction of austenite that has been transformed after reaching a static state during the transformation (i.e., ), represented by %. Similar to Figure 7 The measured score (vertical axis) is plotted relative to the score calculated using the method described above (horizontal axis).

[0143] Figure 9 This involves transformation kinetics. It represents the time t when 50% of the final fraction of austenite is reached during the transformation. 50% , expressed in seconds. The measured t 50% (Vertical axis) relative to t obtained using the above calculation method 50% Plot the values ​​(horizontal axis).

[0144] exist Figure 8 and Figure 9 In the equation, the straight line (y=x) corresponds to an ideal, accurate prediction.

[0145] Figure 8The results show that, for CFB steel grades and for steel grades with very low Si and Al contents, the above-described method for determining the amount of bainitic ferrite formed during the transformation produces a final score that is in good agreement with experiments.

[0146] Figure 9 The results show that the method predicts formation kinetics quite well for both CFB steels and steels with very low Si and Al contents, with response times spanning three orders of magnitude. Nevertheless, it was observed that the predicted kinetics are generally slower than the observed kinetics, particularly for non-CFB steels with high carbon content (0.3 wt%), namely steels g11 and g12. Therefore, for non-CFB steels, if high accuracy is required, the method discussed can preferably be used only for carbon contents equal to or less than 0.25 wt%, or even equal to or less than 0.2 wt% (rather than in C...). o (≤0.5% by weight across the entire range).

[0147] The test results for steel grade g6, which contains aluminum (1.5 wt%) instead of silicon, were also compared with the predictions of this calculation method. The test results were in good agreement with the experimental results (8% to 10% agreement for the final transformation fraction, and for t...). 50% (Time, approximately 20% to 30%).

[0148] Phase fraction and / or temperature estimation of steel semi-finished products that have undergone steel processing operations

[0149] In the methods described above for determining the amount of bainitic ferrite formed during steel processing operations, the amount formed at each time step depends on the temperature T of the steel semi-finished product, which may evolve from one time step to another (this temperature should be the local temperature at a given location in the steel semi-finished product, or the average temperature of the steel semi-finished product). In this respect, the temperature T of the steel at different time steps can be:

[0150] - Independent of phase fraction , , The known quantities, and they are obtained by the microstructure calculation module 15' which determines the time evolution of the phase fraction ( Figure 10 (For example, when a known predetermined heat path TP is applied to a steel semi-finished product during a steel processing operation, or when the temperature of the steel semi-finished product being processed is measured throughout the steel processing operation);

[0151] - Or a quantity like this: given an initial temperature Ti and the heat exchange between the steel semi-finished product and its environment, its value is calculated at time steps during the steel processing operation. Figure 11 (The situation).

[0152] Figure 10 The steps performed to determine the amount of bainitic ferrite formed in a steel semi-finished product during steel processing operations are illustrated according to the method presented above (in the section on "Bainite Formation").

[0153] like Figure 10 As shown, the microstructure calculation module 15' obtains the chemical composition CC of the steel and the size of the austenite grains in the steel. The value of the microstructure calculation module 15' also acquires data representing the thermal path TP followed by the steel semi-finished product during the steel processing operation. This data can indicate the temperature applied to the steel semi-finished product at each time step during the processing operation. Alternatively, it can indicate the initial temperature, duration, and final temperature of each successive stage constituting the thermal path TP. The data representing the thermal path TP can be acquired all at once before the steel processing operation begins, or continuously throughout the processing operation (e.g., several times consecutively during the processing operation when the temperature of the steel semi-finished product is measured online).

[0154] As described above, the microstructure calculation module 15' sequentially and iteratively executes the set of steps s1, s2, and s3 multiple times. Each time this set of steps is executed, i.e., for each new time step, the phase fraction is considered for calculation. , , The temperature T of the evolution is the temperature of the thermal path TP under the time step.

[0155] Figure 11 The diagram schematically illustrates another embodiment of the method presented above in the section on "Bainite Formation," detailing the steps performed to determine the amount of bainitic ferrite formed in the steel semi-finished product during steel processing operations. Figure 11 In the implementation scheme, the microstructure calculation module 15 obtains the chemical composition (CC) of the steel and the size of the austenite grains in the steel. The value of . The microstructure calculation module 15 also obtains the initial temperature Ti of the steel at the start of the steel processing operation (e.g., at the input of the steel processing equipment that performs the steel processing operation, or at the input of a given part of the processing equipment).

[0156] The microstructure calculation module 15 also acquires data representing the heating or cooling conditions (HCC) applied to the steel semi-finished product during the steel processing operation. This data indicates the operating conditions of the heating or cooling apparatus of the steel processing equipment, such as the heating power output by a heating element like a radiant tube, or the flow rate, velocity, and / or temperature of coolant injected, for example, by one or more nozzles. Understanding these heating or cooling conditions (HCC) allows for the determination of the heat exchange between the steel semi-finished product and its environment during the steel processing operation. The data representing the heating or cooling conditions (HCC) can be acquired all at once before the start of the steel processing operation, or continuously throughout the processing operation.

[0157] exist Figure 11 In the implementation scheme, the microstructure calculation module 15 determines the temperature T of the steel at different time steps during the steel processing operation, taking into account the following time steps:

[0158] - The initial temperature value T0, and

[0159] - Heat exchange between the steel semi-finished product and its environment, determined by HCC based on heating or cooling conditions.

[0160] Here, the phase fractions of bainitic ferrite, austenite, and cementite at each time step are also considered. , and The value of determines the time evolution of temperature T. More specifically, based on , and The current value is used to determine the heat capacity of the steel, and possibly, its thermal conductivity and / or density. Furthermore, at each new time step, the microstructure calculation module 15 performs step s4 based on the following steps: Figure 11 To determine the updated value of temperature T:

[0161] - The (constantly updated) heat capacity,

[0162] - The above heat exchange, and

[0163] - The temperature T value at the previous time step.

[0164] This arrangement allows for consideration of the evolution of the steel’s heat capacity (and possibly, thermal conductivity) during the steel processing operations caused by phase transformation.

[0165] During step s4, the updated value of temperature T can also take into account the change in phase fraction between the previous and next time steps, more accurately considering the heat absorbed or released due to these phase fraction changes. Since the transformation from austenite to bainitic ferrite is exothermic, this increases the accuracy of determining temperature T. Heat absorption / release due to cementite formation is generally negligible.

[0166] As already mentioned, the microstructure calculation module 15 sequentially and iteratively executes the group of steps s1, s2, and s3 multiple times. Figure 11 In this case, for each new time step, the microstructure calculation module performs:

[0167] - A group of steps including s1, s2, and s3.

[0168] - And simultaneously, step s4,

[0169] Then iterate again.

[0170] Nevertheless, the combination of steps s1 to s4 can be arranged differently. For example, step s4 can be performed after step s3.

[0171] During the execution of steps s1 and s2, the value of the temperature T under consideration is the value determined during the most recent execution of step s4 (or, possibly, the initial temperature Ti for the first execution of steps s1 and s2).

[0172] exist Figure 10 In the case of and in Figure 11 In both cases, the microstructure calculation modules 15' and 15 can be electronic devices including at least a processor and memory, and are configured, for example, to be programmed to perform as described above. Figure 10 or Figure 11 The above is used to determine , and (And possibly, T) the method. The microstructure calculation modules 15', 15 can also take the form of a computer program or subroutine, i.e., a set of instructions whose execution on a computer (connected to appropriate sensors and / or communication channels) causes the computer to perform the above-mentioned... Figure 10 or Figure 11 The method described.

[0173] exist Figure 10 and Figure 11 In both cases, the initial temperature Ti acquired by the electronic devices 15', 15 can (e.g., here) be the temperature measured by a temperature sensor (such as a pyrometer) of the steel processing equipment, and then the evolution of the phase fraction (and possibly, temperature T) is determined based on this measured temperature. Furthermore, data representing the thermal path TP followed by the semi-finished steel product (in...) Figure 10 In the case of), or data representing heating or cooling conditions of HCC (in Figure 11In the case of steel processing equipment, the data can also be measured by sensors (e.g., steel temperature sensors or coolant temperature sensors) and / or can be transmitted to the heating or cooling system of the equipment via its electronic control unit. Methods for determining the amount of bainitic ferrite formed during steel processing operations can therefore be considered for indirect measurement or prediction of phase fraction. , and And / or indirect measurement methods used for indirect measurement or prediction of the temperature T of steel semi-finished products. In practice, these quantities are derived from one or more additional measurements related to the steel semi-finished product (and possibly, to the processing operation).

[0174] This kind of , , Indirect measurement or prediction of and / or T can be used to monitor steel processing operations (typically, in real time), in which case at least one of the time steps is measured. , , The value of at least one of T is transmitted by the microstructure calculation modules 15, 15' to a human-machine interface, such as a display screen, for output (e.g., displayed to the operator); for example, the value predicted by the method at the end of the steel processing operation. , , The final value (or the final value of T) is displayed on the screen and is continuously updated each time a new semi-finished product is entered or each time a new section of the same steel strip enters the steel processing equipment.

[0175] The above , , Indirect measurement or prediction of T and / or T can also be used to characterize the processed steel semi-finished product. In this case, the value determined according to the method at the end of the steel processing operation... , , The final value (or the final value of T) is output by the microstructure calculation modules 15, 15' and transmitted to the production database that records it.

[0176] The above , , Indirect measurement or prediction of T and / or T can also be used to control steel processing equipment during the steel processing operation itself, as described in detail in the next section, “Process Control”.

[0177] Process control

[0178] Based on the determinations made above , , One possible control method for controlling the value of T in steel processing operations is the control method described below, in which a feedforward control is implemented. This control method includes an electronic control device comprising microstructure calculation modules 15, 15':

[0179] - Obtain the initial temperature Ti,

[0180] - Obtain planned process parameters intended for use during steel processing operations; these process parameters represent the planned thermal path TP or the planned heating or cooling conditions HCC.

[0181] - Determine the estimated final characteristics of the steel semi-finished product at the end of the steel processing operation; said characteristics are the temperature of the steel semi-finished product, its phase content (i.e., , , The value of the phase fraction (or temperature) or mechanical properties such as tensile strength or yield strength determined based on its phase content; said properties are calculated as described above in the "Phase Fraction and / or Temperature Estimation" section. , , The final value of T determines the outcome.

[0182] - Compare the estimated final characteristics with the target final characteristics expected at the end of the processing operation.

[0183] - Adjust the parameters according to the comparison process.

[0184] - Based on the adjusted process parameters, the heating or cooling devices of the steel processing equipment are controlled.

[0185] One implementation scheme of the control method (hereinafter referred to) Figure 12 In a more detailed description, the characteristics discussed are the temperature T of the steel semi-finished product (which is steel strip 1) and the process parameters discussed are the cooling conditions, which specify the operating conditions of valves 8 and 9 that control the cooling jet 21 of the output roller conveyor.

[0186] Figure 12 The hot rolling equipment for conveying hot-rolled steel strip 1 is schematically shown, including a furnace 2, a rolling mill 3, and a cooling device 4 (i.e., an output roller table) for cooling the steel strip 1. The hot rolling equipment also includes an electronic control device 5 for controlling the cooling device 4.

[0187] The strip 1 represents, for example, a steel plate with a thickness of 1 mm to 30 mm.

[0188] As the steel strip 1 exits the furnace 2 and the rolling mill 3, it moves along the running direction A. In this example, the running direction A of the strip 1 is substantially horizontal. The strip 1 then passes through the cooling device 4, where it is cooled from its initial temperature Ti to a final temperature (which is, for example, room temperature, i.e., about 20°C, but may also be higher; cooling ends once the strip is coiled). The initial temperature Ti is, for example, substantially equal to the temperature at the end of the strip rolling process. Ti is measured using a pyrometer 24 connected to the control device 5. The initial temperature Ti is, for example, greater than or equal to 600°C, significantly greater than or equal to 800°C, or even greater than 1000°C. The strip 1 passes through the cooling device 4 along the running direction A at a running speed preferably from 1 m / s to 25 m / s.

[0189] In the cooling device 4, at least one first cooling fluid jet 21 is sprayed onto the top surface of the belt 1, and at least one second cooling fluid jet is sprayed onto the bottom surface of the belt 1 opposite to its top surface. The cooling fluid (also referred to as coolant) is, for example, water. The cooling device 4 includes a top valve 8 and a bottom valve 9 configured to open or close the coolant flow in the direction of the steel belt 1.

[0190] Electronic control device 5 includes:

[0191] - Figure 11 The microstructure calculation module 15, and

[0192] - Control module 14, which is configured to control cooling device 4 based on temperature T (especially final temperature) determined by microstructure calculation module 15.

[0193] The electronic control unit 5 is configured to determine the flow rate of each valve 8, 9, and accordingly determine which valve 8, 9 needs to be opened or closed. For example, based on a given cooling mode, the location of the pyrometer 24, and the target temperature, the control module 14 determines which valve 8, 9 needs to be opened or closed to compensate for initial temperature changes and strip speed changes.

[0194] In this example, the microstructure calculation module 15 is configured such that, when determining the evolution of the strip's temperature T and phase content, the heat exchange between strip 1 and its environment is calculated according to the formulas presented in paragraphs 55 to 102 of document EP3645182A1, and more specifically in paragraphs 79, 84, 87, 90, and 93. The evolution of the strip's temperature T is based on the above-mentioned... Figure 11The phase transformation calculation proposed is determined accordingly. Therefore, it can be specifically determined according to paragraphs 55 to 102 of document EP3645182A1, but the phase transformation calculation described in paragraph 101 of EP3645182A1 is replaced with the phase transformation calculation proposed above in the "Bainite Formation" section, or possibly, the phase transformation calculation described in paragraph 101 of EP3645182A1 is completed with the bainite formation calculation discussed.

[0195] Figure 13 and Figure 14 This demonstrates the use of the control method just described (curve 13b, histogram). Figure 14 b), or use the existing control method described in EP3645182A1 (curve 13a, histogram) Figure 14 a) Production data recorded while operating cooling device 4.

[0196] Figure 13 Two comparative curves 13a and 13b are shown regarding the percentage of coil material provided within a defined tolerance for winding temperature error, indicated on the horizontal axis. The winding temperature is the final temperature at the end of the steel processing operation. Curve 13b shows the result of the method according to the invention, while curve 13a shows the result of the prior art method (EP3645182A1). The result using the method according to the invention is better than the result using the prior art method because, for any value of the defined tolerance indicated on the horizontal axis, the percentage of coil material provided by the method according to the invention within said defined tolerance is better than that provided by the prior art method.

[0197] Figure 14 Two comparative histograms are shown, illustrating the amount of roll material provided by the corresponding difference between the target take-up temperature and the measured take-up temperature. Figure 14 a, 14b, the differences are represented on the horizontal axis. Histogram Figure 14 b shows the result of the method according to the invention, while the histogram Figure 14 a shows the results of the prior art method (EP3645182A1). The results using the method according to the invention are better than the results using the prior art method because the histogram... Figure 14 b is the ratio of the square root Figure 14 a is better concentrated at zero and has a higher histogram for small difference values ​​(for difference values ​​from -20°C to +20°C). Figure 13 The value of a.

[0198] Figure 14 and Figure 13 Production data for rolls with chemical compositions (C) within the following range (in weight percent) were compiled: C o : [0.065; 0.1], x Mn=[1.3; 1.6], x Si =[0.01; 0.15], x Ni =[0.025; 0.05], x Cr : [0.02; 0.04], x Nb [0.03; 0.05].

[0199] For example, for Figure 14 and Figure 13 One of the roll materials has the following chemical composition: C o =0.1, x Mn =1.5, x Si =0.09, x Al= 0.04, x Ni =0.03, x Cr =0.04, x Nb =0.03, the rest is iron and unavoidable impurities.

[0200] In the case of other steel grades, similar observations were also made. Figure 14 and Figure 13 Those similar to, or even more than Figure 14 and Figure 10 Those higher improvements. For example, for steel grades corresponding to the following range: C o : [0.05; 0.06], x Mn =[1.4; 1.5], x Si =[0.2; 0.25], x Ni =[0.025; 0.035], x Cr : [0.3; 0.35], x Nb [0.025; 0.035].

[0201] And also for steel grades corresponding to the following range: C o : [0.05; 0.07], x Mn =[1.8; 1.9], x Si =[0.02; 0.04], x Ni =[0.025; 0.045], x Cr : [0.02; 0.028], x Nb : [0.06; 0.08], x Nb : [0.06; 0.08], x Ti [0.1; 0.15].

[0202] The method for controlling coolant injection on the output roller conveyor has just been described, in which bainite formation is considered according to the method proposed above (in the section on "Bainite Formation").

[0203] Nevertheless, according to the present invention, the method described above in the "Bainite Formation" section or in the "Phase Fraction and / or Temperature Estimation" section can be used to determine the phase fraction. , , The value of T can be used to control other steel processing operations. For example, heat treatment operations that occur after annealing and include or precede coating operations such as hot-dip coating can be controlled as described above to obtain the target fraction of bainite at the end of the operation.

[0204] Computer-aided design for steel processing operations

[0205] The method used to determine the amount of bainitic ferrite formed during steel processing operations (described in the section on “Bainite Formation”) can also be used, in a computer-aided design manner, to determine the thermal path to be followed by the steel semi-finished product in order to obtain a given target property at the end of the processing. The target property may be:

[0206] - From phase fraction , , The derived target mechanical properties, such as tensile or yield strength,

[0207] - or phase fraction , , itself.

[0208] The hot path can be determined, for example, by performing multiple executions on different candidate hot paths. Figure 10 The method involves selecting a candidate thermal path that produces the final property closest to the target property at the end of the steel processing operation. Alternatively, the thermal path can be modified gradually (performed in each iteration). ​ The method involves iteratively adjusting candidate hot paths until the final characteristics are sufficiently close to the target characteristics (i.e., within a given precision range). Other approaches can also be used to determine (or, in other words, optimize) such hot paths.

[0209] After determining the thermal path that produces the target characteristics (within a given accuracy range), steel processing operations are performed according to that thermal path.

[0210] Determining such a thermal path and then controlling the steel processing equipment accordingly can be done through electronic devices or systems configured for this purpose.

Claims

1. A method for determining the amount of bainitic ferrite formed in a steel semi-finished product (1) during steel processing operations. A method wherein the steel semi-finished product has a chemical composition CC, the method comprising the following steps performed by an electronic device: - Obtain the chemical composition (CC) of the steel in the semi-finished steel product. - s1) Determine the bainitic ferrite growth rate, which is proportional to the following: ○ Density of bainitic ferrite nucleation centers , ○ Where T is the temperature of the steel, R is the universal gas constant, and The activation energy for the transformation from austenite to bainitic ferrite, and ○ Adjustment coefficient, which is the difference between the free enthalpy of the bainitic ferrite phase and the free enthalpy of the austenitic phase. When the coefficient of adjustment approaches zero, the enthalpy of the austenitic phase depends at least on the carbon content in the austenitic phase. Used for calculation The carbon content values ​​in the bainitic ferrite phase and the carbon content in the austenitic phase The values ​​are the same. - s2) Based at least on the chemical composition CC of the steel and the carbon content in the austenitic phase. Determine the cementite growth rate. - s3) Based on the growth rate of the bainitic ferrite and the growth rate of the cementite, determine the phase fractions of bainitic ferrite, austenite, and cementite at the next time step. The value, and based on the phase fraction The value is used to determine the carbon content in the austenitic phase at the next time step. The value, The group consisting of steps s1, s2, and s3 is executed sequentially several times.

2. The method according to claim 1, wherein the adjustment coefficient is: - when When approaching zero, with proportional, and - when When it increases, it is constrained to a constant value.

3. The method according to claim 2, wherein the adjustment coefficient is equal to or substantially equal to .

4. The method according to any one of the preceding claims, wherein Equal to or substantially equal to , and Q o K1 depends on the chemical composition CC of the steel, but during the processing, when the carbon content in the austenitic phase... During the evolution, Q o K1 remains unchanged.

5. The method according to claim 4, wherein Q o Equal to or substantially equal to A + B. (TT) M A and B are two constants, and T M The temperature at which the steel begins to martensite is formed.

6. The method according to any one of the preceding claims, wherein the density of the bainitic ferrite nucleation centers is... Equal to or substantially equal to: - Overcooled T B -T, where T B The bainite initiation temperature, multiplied by - Coefficient The coefficient Depending on the chemical composition (CC) of the steel and Proportional The size of the austenite grains in the steel is given.

7. The method according to any one of the preceding claims, wherein the bainitic ferrite growth rate is calculated according to the following equation: ， in - The fraction of bainitic ferrite in the steel. - C mod The adjustment coefficient is... - The density of the bainitic ferrite nucleation centers. - ν=kT / h≈10 13 seconds -1 , - equal , or possibly equal to , The fraction of ferrite in the steel. - The fraction of austenite in the steel. - and λ is the size of the austenite grain. The autocatalytic coefficient is proportional.

8. The method according to any one of the preceding claims, wherein the carbon content in the austenitic phase is... Maintain a carbon content below the threshold for cementite precipitation. The cementite growth rate remains zero, and the cementite growth rate depends on the chemical composition (CC) of the steel.

9. The method according to any one of the preceding claims, wherein the carbon content relative to the austenitic phase... Ignore the carbon content in the bainitic ferrite phase At the same time, and in the cementite phase, the carbon content (C c Calculate the carbon content in the austenitic phase under constant conditions. .

10. The method according to any one of the preceding claims, wherein the carbon, manganese, silicon, aluminum and chromium contents in the steel are respectively denoted as C. o x Mn x Si x Al and x Cr And expressed as a percentage by weight, within the following range: C o ≤0.5; x Mn ≤3; x Si ≤2; x Al ≤1.5; x Cr ≤4.

11. A method for monitoring steel processing operations, during which steel semi-finished products (1) are processed in steel processing equipment (4), the method comprising the following steps: - At least the initial temperature (Ti) of the steel semi-finished product at the start of the steel processing operation is obtained, the temperature being measured by the sensor (24) of the steel processing equipment. - The method according to any one of claims 1 to 10, determining the amount of bainitic ferrite formed in the steel semi-finished product during the steel processing operation. The method for determining this is performed while taking into account the initial temperature (Ti) of the steel at the start of the steel processing operation, as measured by the sensor.

12. The method of claim 11, further comprising: - Obtain thermal path data representing the thermal path (TP) followed by the steel semi-finished product during the steel processing operation. And among them, When determining the amount of bainitic ferrite formed by the method according to any one of claims 1 to 10, at each time step, the evolution of the bainitic ferrite phase fraction is considered based on the temperature (T) of the steel along the thermal path.

13. The method of claim 11, further comprising: - Obtain data representing the heating or cooling conditions (HCC) applied to the steel semi-finished product (1) during the steel processing operation. And wherein, when determining the amount of bainitic ferrite formed by the method according to any one of claims 1 to 10, at each time step, the heating or cooling conditions are taken into account, and the corresponding phase fractions of bainitic ferrite, austenite, and cementite in the steel are also taken into account. To determine the updated value of the temperature (T) of the steel.

14. The method according to claim 13, wherein the heating or cooling actuator (8, 9) of the steel processing equipment (4) is controlled according to the following: - The expected temperature (T) of the steel at the end of the steel processing operation as determined by claim 13, and according to - The target temperature to be reached by the steel semi-finished product (1) at the end of the steel processing operation.

15. The method according to any one of claims 11 to 13, wherein - Taking into account the amount of bainitic ferrite formed during the steel processing operations, determine the estimated final properties of the steel semi-finished product, and - The process parameters are adjusted according to the estimated final characteristics and the target characteristics of the steel semi-finished product (1) to be obtained at the end of the steel processing operation. The adjusted process parameters are transmitted to the actuators (8, 9) of the steel processing equipment to realize the steel processing operation according to the process parameters.

16. The method according to any one of claims 11 to 15, wherein at least one value of the bainitic ferrite fraction determined during the method for determination is output using a human-machine interface or recorded in a production database.

17. A method for controlling steel processing equipment, the method comprising the following steps: - Determine the thermal path to be followed by the steel semi-finished product during the steel processing operation to obtain a given target property of the steel semi-finished product at the end of the processing, the thermal path being determined taking into account the formation of bainitic ferrite during the processing, the amount of bainitic ferrite formed during the processing being determined by the method of any one of claims 1 to 10. - Control the actuator of the steel processing equipment according to the determined thermal path to realize the steel processing operation.

18. An electronic device (15; 15'; 5) comprising at least a processor and a memory, said electronic device being configured to perform the method according to any one of claims 1 to 17.

19. A computer program comprising instructions that, when executed on a computer, cause the computer to perform the method according to any one of claims 1 to 17.

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