CN104384469B - The prognoses system of initial set shell thickness and method in a kind of steel continuous casting crystallizer - Google Patents

Abstract

The prognoses system of initial set shell thickness and a method in steel continuous casting crystallizer, this system comprises information acquisition module, steel grade thermal physical property parameter computing module, crystallizer initial set shell growth prediction module and result output module; The method comprises: bleed-out base shell microcosmic solidified structure detects; Gather initial information: the step calculating interdendritic solute segregation and solidification path and then acquisition steel grade thermal physical property parameter in solidification of molten steel process; Solve crystallizer molten steel flow field, mould temperature field and crystallizer solute field, and macroscopic transport process in crystallizer is developed behavior with microcosmic solidified structure in crystallizer be coupled, prediction continuous cast mold internal high temperature solidification of molten steel process shell growth behavior further; Export by the initial set shell thickness at diverse location place in Solidification Microstructure Morphology in the crystallizer of prediction and crystallizer and with the comparative result of initial set base shell actual (real) thickness and show.The present invention can solidify behavior by the microcosmic of initial set base shell in accurately predicting crystallizer.

Description

The prognoses system of initial set shell thickness and method in a kind of steel continuous casting crystallizer

Technical field

The invention belongs to metallurgical process production technical field, be specifically related to prognoses system and the method for initial set shell thickness in a kind of steel continuous casting crystallizer.

Background technology

Continuous cast mold, as the parts of most critical in conticaster, is called as " heart " of conticaster.High-temperature molten steel flow into crystallizer by submersed nozzle, under the effect of crystallizer cooling water, forms the nascent solidified shell of definite shape.In crystallizer, nascent solidified shell uniformity plays decisive role to surface quality of continuously cast slab and continuous irrigatation castability, and thickness of solidified slab shell in secondary is related to strand intensity, to initial set base shell opposing strand internal steel hydrostatic pressure, prevents bleed-out most important.For this reason, in continuous cast mold, initial set base shell not only requires that shell thickness is even, and requires that shell thickness is enough thick, thus ensures the security that cc billet surface quality and continuous casting are produced.

Based on the importance of crystallizer initial set base shell, its thickness of accurate characterization and uniformity, for optimization continuous cast mold technology and equipment, improve continuous casting billet quality and continuous casting productivity ratio very important.But; because the growth of solidified shell in crystallizer is by multifactor joint effects such as crystallizer intensity of cooling, tapering, covering slag performance and molten steel flows; it is very complicated opaque pyroprocess that Mold solidifies; being difficult to use physical method on-line checkingi, therefore can only be predict shell thickness.At present, predict that the method for shell thickness is mainly divided into test mensuration and the large class of Method for Numerical two.

Test mensuration mainly comprises bleed-out base shell macroscopic measurement method, method of powder actuated shot, tracer method, punching fluid-discharge therapy.Bleed-out base shell macroscopic measurement method (the document Sequencing and analysis of solidified shell " in the continuous casting crystallizer for plate billet ", Special Processes of Metal Castings and non-ferrous alloy, 1998, (3): the 7-9. document measuring and analysis of bleed-out shell thickness " in the continuous casting crystallizer for plate billet ", University Of Science and Technology of the Inner Mongol's journal, 2012, 30 (2): 104-106. etc.) slide measure or ruler is adopted to measure thickness of solidified slab shell in secondary, obtain and distribute along crystallizer diverse location place shell thickness, but because the molten steel residuing in solidified shell surface in bleed-out process can continue to solidify, make the actual shell thickness of measured value bigger than normal.Method of powder actuated shot (document " thickness of application Nail-shooting Technique in Measuring Solidified Slab Shell ", Anshan iron and steel plant technology, 2005, (6): 36-39. document " application practice of Nail-shooting Technique in Measuring Solidified Slab Shell thickness ", continuous casting, 2011, (3): 28-30. patent CN101992281B, Deng) adopt and the steel nail containing FeS is injected strand, the distribution of steel nail fusing situation and S according to strand sufur printing, determine shell thickness.The method can at the direct nailing determination in secondary cooling area for continuous casting and air cooling zone casting blank solidification shell thickness, but cannot directly measure crystallizer solidified shell, can only adopt and return coagulation factor and Mathematical Modeling and determine, cannot initial set shell thickness in actual response crystallizer.Tracer method (document " Applicationofisotopesinindustryandmetallurgy ", BulletinoftheNationalInstituteofSciencesofIndia, 1959:13-15. document " Estimationofshellthicknessinacontinuouslycaststeelbillet usingradiotracers ", IsotopesandRadiationTechnologyinindustry. etc.) employing adds relevant radio isotope in crystallizer, dissect steel billet, measurement isotope distributes, and determines shell thickness.The method produces radioactive pollution, and comparatively large to human injury, poor operability at the scene, is not used widely.Punching fluid-discharge therapy belongs to destructive testing, and the party's ratio juris and bleed-out base shell macroscopic measurement method are similar, there is the shortcoming that base shell measured value is bigger than normal equally, and the method also exists that impact is normal produces, and the shortcomings such as experimentation cost height, so adopt hardly.

Numerical Simulation Prediction method is based on crystallizer solidification and heat transfer mechanism; consider the impact of the factors such as Mold flowing, cooling condition, covering slag performance; set up solidified shell growth Mathematical Modeling in crystallizer; thus according to the physical parameter of different steel grade, casting machine parameter and casting parameters; prediction Mold process of setting, determines initial set shell thickness.The method is comparatively tested mensuration and is had that cost is low, efficiency is high, analyze the advantages such as comprehensive, but existing crystallizer thickness of solidified slab shell in secondary forecast model is all the macroscopic transport phenomenon based on delivered heat, MOMENTUM TRANSMISSION and mass transport, ignore forming core and the dendritic growth process of Mold process of setting, inherently cannot describe the growth course of solidified shell, thus crystallizer initial set shell thickness cannot be determined exactly.Macroscopical solid-liquid phase line temperature can only be adopted simply to characterize solidification front position, and then macroscopically determining thickness of solidified slab shell in secondary roughly.In addition, steel grade thermal physical property parameter (solid-liquid phase line temperature, thermal conductivity factor, density, specific heat and latent heat of solidification) is treated to constant or simple empirical regression formula by existing model usually, cannot characterize solidification of molten steel process solute segregation and phase transformation to the impact of steel grade thermal physical property parameter.Therefore, the steel grade thermal physical property parameter computing formula that the accuracy of model is selected affects comparatively large, and error calculated is larger.Moreover existing model all adopts Thermocouple temperature data or bleed-out shell thickness two class checking means.Thermocouple temperature data is copper plate temperature data, there is complicated covering slag and air gap distribution, drastically influence the heat transfer between copper plate of crystallizer and solidified shell between copper plate of crystallizer and solidified shell.Adopt Thermocouple data can only verify the copper plate temperature of mathematical model prediction, and directly cannot verify the accuracy of shell thickness.Therefore the checking of Thermocouple temperature data belongs to indirect verification, and modelling verification accuracy leaves a question open.The checking of bleed-out shell thickness belongs to direct checking, but all adopts macroscopical determination method due to existing bleed-out shell thickness measurement means, and measured value is bigger than normal compared with base shell actual value, thus makes Mathematical Modeling calibration value bigger than normal.Therefore, the Mathematical Modeling adopting traditional bleed-out shell thickness mensuration to demarcate equally cannot Accurate Prediction crystallizer concreting thickness.

Summary of the invention

For the deficiency that above-mentioned prior art exists, the invention provides prognoses system and the method for initial set shell thickness in a kind of steel continuous casting crystallizer.

Technical scheme of the present invention is:

A prognoses system for initial set shell thickness in steel continuous casting crystallizer, comprising:

Information acquisition module: be used for gathering casting steel grades, crystallizer physical dimension, submersed nozzle physical dimension, continuous casting process condition and along the thickness of solidified slab shell in secondary measured value at crystallizer diverse location place and dendrite interval measured value; Described crystallizer physical dimension, comprises width of plate slab, slab thickness, crystallizer height, copper plate thickness, the tank degree of depth, sink thicknesses and nickel layer thickness; Described continuous casting process condition, comprises meniscus position, casting speed, inlet water temperature, wide exports water temperature, leptoprosopy exports water temperature, wide cooling water flow and leptoprosopy cooling water flow; Described submersed nozzle physical dimension, comprises submersed nozzle immersion depth and submersed nozzle side opening inclination angle;

Steel grade thermal physical property parameter computing module: the casting steel grades collected according to information acquisition module and dendrite interval measured value, calculate interdendritic solute segregation and solidification path in solidification of molten steel process, and then obtain steel grade thermal physical property parameter and reached crystallizer initial set shell growth prediction module; Described steel grade thermal physical property parameter, comprises solid-liquid phase line temperature, thermal conductivity factor, density, specific heat and latent heat of solidification;

Crystallizer initial set shell growth prediction module: by delivered heat in crystallizer, MOMENTUM TRANSMISSION and mass transport are at interior macroscopic transport process and copper plate of crystallizer surface forming core, the inner forming core of molten steel and grain growth develop behavior at interior microcosmic solidified structure and are coupled, and according to the crystallizer physical dimension that information acquisition module collects, submersed nozzle physical dimension and continuous casting process condition and the steel grade thermal physical property parameter received from steel grade thermal physical property parameter computing module, prediction casting process crystallizer internal high temperature solidification of molten steel process shell growth behavior is also reached result output module,

Result output module: the crystallizer solidified inside tissue topography of image conversion ground display prediction, i.e. initial set shell growth process, and quantification ground display crystallizer initial set shell thickness predicted value, the solidified shell measured value of the crystallizer of this initial set shell thickness predicted value and information acquisition module collection is compared, and this comparative result of output display.

In the steel continuous casting crystallizer adopting the prognoses system of initial set shell thickness in described steel continuous casting crystallizer, the Forecasting Methodology of initial set shell thickness, comprises the steps:

Step 1: get bleed-out base shell sample, carries out bleed-out base shell microcosmic solidified structure and detects, obtain the initial set shell thickness measured value along crystallizer diverse location place and dendrite interval measured value;

The method that described bleed-out base shell microcosmic solidified structure detects is: dissect bleed-out base shell, get bleed-out base shell sample; Adopt certain corrosive agent to carry out corrosion to bleed-out base shell sample and obtain bleed-out base shell solidification features; Observe the microstructure morphology after the corrosion of bleed-out base shell sample, changed the microcosmic solidified structure change caused by cooling condition before and after comparison bleed-out, determine the initial set shell thickness measured value along crystallizer diverse location place and dendrite interval measured value; Described corrosive agent is the nital of 6% ~ 10%; The time that described employing corrosive agent corrodes bleed-out base shell sample is 30 ~ 40s;

Step 2: gather initial information;

Comprise casting steel grades, crystallizer physical dimension, submersed nozzle physical dimension, continuous casting process condition and along the thickness of solidified slab shell in secondary measured value at crystallizer diverse location place and dendrite interval measured value; Described crystallizer physical dimension, comprises width of plate slab, slab thickness, crystallizer height, copper plate thickness, the tank degree of depth, sink thicknesses and nickel layer thickness; Described continuous casting process condition, comprises meniscus position, casting speed, inlet water temperature, wide exports water temperature, leptoprosopy exports water temperature, wide cooling water flow and leptoprosopy cooling water flow; Described submersed nozzle physical dimension, comprises submersed nozzle immersion depth and submersed nozzle side opening inclination angle;

Step 3: the dendrite interval measured value gathered according to step 2 and casting steel grades, calculate interdendritic solute segregation and solidification path in solidification of molten steel process, and then obtain steel grade thermal physical property parameter, comprise solid-liquid phase line temperature, thermal conductivity factor, density, specific heat and latent heat of solidification;

Step 3.1: according to the pick-up behavior of interdendritic solute conservation principle and solutes accumulation principle and field trash MnS, set up solute microsegregation Mathematical Modeling, calculate interdendritic solute segregation and solidification path in solidification of molten steel process, obtain the functional relation of each phase fraction and temperature;

Step 3.2: each phase fraction obtained according to step 3.1 and the functional relation of temperature, calculates steel grade thermal physical property parameter, comprises solid-liquid phase line temperature, thermal conductivity factor, density, specific heat and latent heat of solidification;

Step 4: the crystallizer physical dimension, submersed nozzle physical dimension and the continuous casting process condition that collect according to information acquisition module and the steel grade thermal physical property parameter received from steel grade thermal physical property parameter computing module, solve crystallizer molten steel flow field, mould temperature field and crystallizer solute field, and macroscopic transport process in crystallizer is developed behavior with microcosmic solidified structure in crystallizer be coupled, prediction continuous cast mold internal high temperature solidification of molten steel process shell growth behavior further;

Step 5: export and the initial set shell thickness at diverse location place in Solidification Microstructure Morphology and crystallizer in the crystallizer showing prediction, and compare with the initial set base shell actual (real) thickness that step 1 obtains, and by comparative result output display.

According to the Forecasting Methodology of initial set shell thickness in described continuous cast mold, described step 3.1 comprises following content:

Solute microsegregation Mathematical Modeling is:

$\frac{\∂C_{s,i}}{\∂t}=\frac{\∂}{\∂x}\left(D_{s,i}\right(T\left)\frac{\∂C_{s,i}}{\∂x}\right)---\left(1\right)$

Wherein, primary condition is: as t=0, boundary condition is: when x=0 and x=λ/2, λ is dendrite interval, m; c _l,iand C _s,ibe respectively solute concentration in liquid phase l of the initial concentration of solute element i in molten steel, solute element i and the solute concentration of solute element i in solid phase s, wt%; D _s,i(T) be the diffusion coefficient of solute element i in solid phase, m ²/ s; T is the time, second; for solute element i solid liquid interface equilibrium distribution coefficient; Described solid phase comprises ferritic phase δ and austenite phase γ;

Molten steel liquidus temperature T is depended in phase transformation in solidification of molten steel process _ltemperature is started with δ/γ phase in version

$T_l=1536-\underset{i}{\Σ}{m}_i\·C_{l,i}^0---\left(2\right)$

$T_{{\mathrm{Ar}}_4}=1392-\underset{i}{\Σ}{n}_i\·k_{i,0}^{\mathrm{\δ}/1}\·C_{1,i}^{\mathrm{\δ}}---\left(3\right)$

In formula, for the concentration of solute element i in δ/γ boundary place liquid phase; m _iand n _ibe respectively liquidus curve and Ar in pseudo-binary Fe-i phasor ₄line slope; for solute element i is at δ/γ interface equilibrium distribution coefficient;

In addition, the pick-up behavior of field trash MnS calculates by the chemical balance that [Mn]+[S]=(MnS) reacts, and its standard Gibbs free energy becomes Δ G ^Θemploying following formula calculates:

In liquid phase: Δ G ^Θ=-165248.81+90.90T (4)

Now, forward position, s/l interface residue solute element concentration is equilibrium concentration:

$C_{l,Mn}^t\·f_{Mn}\·C_{l,S}^t\·f_S=1/K_{l,MnS}---\left(5\right)$

${\mathrm{Cin}}_{Mn}^t\·M_S={\mathrm{Cin}}_S^t\·M_{Mn}---\left(6\right)$

In formula, K _{l, MnS}for the equilibrium constant of MnS evolution reaction; with be respectively the mass fraction of solute element Mn and S in t molten steel, wt%; with being respectively t due to MnS separates out the amount of solute element Mn and S consumed respectively, wt%; M _sand M _mnbe respectively the molal weight of solute element Mn and S, g/mol; f _mnand f _sbe respectively the activity coefficient of solute element Mn, S in molten steel.

According to the Forecasting Methodology of initial set shell thickness in described steel continuous casting crystallizer, described step 4 comprises the steps:

Step 4.1: according to delivered heat, MOMENTUM TRANSMISSION and mass transport process in crystallizer, solve crystallizer molten steel flow field, mould temperature field and crystallizer solute field;

Step 4.1.1: calculate crystallizer molten steel flow field;

Crystallizer molten steel flow field is calculated according to following equation;

Continuity equation:

$\frac{\∂\left(\mathrm{\ρ}u\right)}{\∂x}+\frac{\∂\left(\mathrm{\ρ}v\right)}{\∂y}+\frac{\∂\left(\mathrm{\ρ}w\right)}{\∂z}=0---\left(15\right)$

Wherein, u, v and w are respectively the component of velocity field u (u, v, w) along three dimensional space coordinate direction of principal axis x, y and z, m/s;

MOMENTUM TRANSMISSION equation: the equation of momentum is in the x-direction shown below, along the equation of momentum in other direction and following formula similar;

$\begin{array}{c}\frac{\∂\left(\mathrm{\ρ}u\right)}{\∂t}+\frac{\∂\left(\mathrm{\ρ}uu\right)}{\∂x}+\frac{\∂\left(\mathrm{\ρ}uv\right)}{\∂y}+\frac{\∂\left(\mathrm{\ρ}uw\right)}{\∂z}=\frac{\∂}{\∂x}\[{\mathrm{\μ}}_{eff}(\frac{\∂u}{\∂x}+\frac{\∂u}{\∂x})\]+\frac{\∂}{\∂y}\[{\mathrm{\μ}}_{eff}(\frac{\∂u}{\∂y}+\frac{\∂v}{\∂x})\]+\\ \frac{\∂}{\∂x}\[{\mathrm{\μ}}_{eff}(\frac{\∂u}{\∂z}+\frac{\∂w}{\∂x})\]-\frac{\∂p}{\∂x}+{\mathrm{\ρg}}_x\end{array}---\left(16\right)$

Wherein μ _efffor virtual viscosity coefficient, Pas is laminar flow viscosity μ _lwith turbulent viscosity μ _tsum, namely c _μfor constant; P is pressure, Pa; g _xfor gravity component in the x-direction; K is tubulence energy; ε is dissipative shock wave;

Tubulence energy equation and the unification of dissipative shock wave equation are shown below:

$\frac{\∂\left(\mathrm{\ρ}u\mathrm{\Φ}\right)}{\∂x}+\frac{\∂\left(\mathrm{\ρ}v\mathrm{\Φ}\right)}{\∂y}+\frac{\∂\left(\mathrm{\ρ}w\mathrm{\Φ}\right)}{\∂z}=\frac{\∂}{\∂x}\[\mathrm{\Ω}\frac{\∂k}{\∂x}\]+\frac{\∂}{\∂y}\[\mathrm{\Ω}\frac{\∂k}{\∂y}\]+\frac{\∂}{\∂z}\[\mathrm{\Ω}\frac{\∂k}{\∂z}\]+S^0---\left(17\right)$

For tubulence energy k, Φ=k, s ⁰=G-ρ ε;

For dissipative shock wave ε, Φ=ε, $\mathrm{\Ω}={\mathrm{\μ}}_l+\frac{{\mathrm{\μ}}_t}{{\mathrm{\σ}}_{\mathrm{\ϵ}}},S^0=\frac{C_{1}G\mathrm{\ϵ}-C_2{\mathrm{\ρ\ϵ}}^2}{k};$

C in formula ₁, C ₂, σ _kand σ _εbe constant; Symbol G can represent with formula (18);

$G={\mathrm{\μ}}_t(2{\left(\frac{\∂u}{\∂x}\right)}^2+2{\left(\frac{\∂v}{\∂y}\right)}^2+2{\left(\frac{\∂w}{\∂z}\right)}^2+{\left(\frac{\∂u}{\∂y}+\frac{\∂v}{\∂x}\right)}^2+{\left(\frac{\∂u}{\∂z}+\frac{\∂w}{\∂x}\right)}^2+{\left(\frac{\∂v}{\∂z}+\frac{\∂w}{\∂y}\right)}^2)---\left(18\right)$

Step 4.1.2: calculate mould temperature field

Calculate according to delivered heat equation, as shown in the formula:

$\frac{\∂}{\∂t}\left(\mathrm{\ρ}H\right)+\▿\·\left(\mathrm{\ρ}uH\right)=\▿\·\left(\right(k_{steel}+c\frac{{\mathrm{\μ}}_t}{{\mathrm{\σ}}_t})\▿T)---\left(19\right)$

Wherein k _steelfor the thermal conductivity factor of steel, W/ (m DEG C); σ _tfor constant, value 0.9 ~ 1.0;

Step 4.2: the dendritic growth that the grain growth controlled according to copper plate of crystallizer surface forming core, the inner forming core of molten steel and thermal diffusion and solutes accumulation control develops behavior at interior microcosmic solidified structure, the growth behavior of crystal grain and dendrite in prediction solidification of molten steel process;

Step 4.2.1: rule of thumb forming core parameter, prediction solidification of molten steel nucleation process;

Nucleation Model:

$n\left(\mathrm{\Δ}T\right)=\frac{n_{max}}{\sqrt{2\mathrm{\π}}{\mathrm{\ΔT}}_{\mathrm{\σ}}}{\∫}_0^{\mathrm{\Δ}T}\exp \[-\frac{1}{2}\left(\frac{{\mathrm{\ΔT}}^{\′}-{\mathrm{\ΔT}}_n}{{\mathrm{\ΔT}}_{\mathrm{\σ}}}\right)\]d\left({\mathrm{\ΔT}}^{\′}\right)---\left(20\right)$

In formula, n (Δ T) is grain density; Δ T is degree of supercooling, K; n _maxfor initial forming core substrate number, Δ T _n, Δ T _σbe respectively average forming core degree of supercooling and standard variance degree of supercooling; Δ T' is degree of supercooling integration variable, K;

Step 4.2.2: calculate solute field distribution in solidification of molten steel process;

The crystallizer molten steel flow field result obtained by step 4.1.1 brings following mass transmission equation into:

$\frac{\∂C}{\∂t}+\▿\·\left(\mathrm{\ξ}uC\right)=\▿\·(D\▿C)---\left(21\right)$

In formula, C is solute concentration, wt%; D is solutes accumulation coefficient, m ²/ s; ξ is cellular state parameter;

Step 4.2.3: the relation setting up temperature field, solid liquid interface place and solute field, obtains the equilibrium concentration at solid liquid interface place;

The available following formula of relation of temperature field, solid liquid interface place and solute field represents:

In formula, T ^*for solid liquid interface place temperature, K; m ₀for liquidous slopes; C ₀for alloy initial concentration, for solid liquid interface place liquid phase solute concentration, Γ is Gibbs-Thomson coefficient, and κ is average solid liquid interface curvature, for anisotropy of interface energy function, θ is dendrite preferential growth angle, for the angle of solid liquid interface method phase and x-axis.

Solid liquid interface curvature is determined by interface solid rate gradient, can formulae discovery as follows:

$\mathrm{\κ}=\frac{2{\left(f_s\right)}_x{\left(f_s\right)}_y{\left(f_s\right)}_{xy}-{\left(f_s\right)}_x^2{\left(f_s\right)}_{yy}-{\left(f_s\right)}_y^2{\left(f_s\right)}_{xx}}{{\[{\left(f_s\right)}_x^2+{\left(f_s\right)}_y^2\]}^{3/2}}---\left(23\right)$

The anisotropy of interfacial tension can by following formulae discovery:

In formula, (f _s) _x(f _s) _yfor the single order local derviation of solid rate, (f _s) _xx, (f _s) _xy(f _s) _yyfor the second order local derviation of solid rate, σ is Interface Anisotropy parameter;

Step 4.2.4: according to the relation of the solute element equilibrium concentration at solid liquid interface place and the solute element concentration in forward position, interface, i.e. forward position, interface solute concentration gradient, determines solid liquid interface rate travel;

The dentrite tip speed of growth controls by interface solute concentration, can by following formulae discovery:

$v_n{C}_l^{*}(1-k_0)=D_s\frac{\∂C_s}{\∂n}{|}^{*}-D_l\frac{\∂C_l}{\∂n}{|}^{*}---\left(26\right)$

In formula, v _nfor interface method phase shift speed, m/s; k ₀for solute balance distribution coefficient; D _lfor solute element diffusion coefficient in the liquid phase, m ²/ s; C _sand C _lbe respectively solid phase and liquid concentration, wt%;

Beneficial effect of the present invention: the present invention compared with prior art has following advantage:

1. the present invention can by delivered heat in crystallizer, MOMENTUM TRANSMISSION and mass transport are at interior macroscopic transport process and copper plate of crystallizer surface forming core, the inner forming core of molten steel and grain growth develop behavior at interior microcosmic solidified structure and are coupled, directly calculate to a nicety according to process conditions the growth behavior of initial set base shell in steel continuous casting crystallizer, comprise solute segregation behavior in continuous casting steel billet process of setting, grain size distribution, the distribution of initial set base shell dendrite interval and the direction of growth, thus the microcosmic of initial set base shell solidifies the initial set shell thickness at diverse location place in behavior and crystallizer in the crystallizer that can calculate to a nicety,

2. the bleed-out base shell microcosmic solidified structure detection method that the present invention proposes can detect the actual thickness of initial set base shell in crystallizer, avoids the shortcoming that traditional macro base shell detection technique error is large;

3. the present invention can according to steel grade process of setting phase transformation law, Accurate Prediction steel grade thermal physical property parameter changes, the impact of process of setting solute segregation on solidus temperature can be considered simultaneously, abandon the error that Traditional calculating methods adopts constant coefficient process steel grade thermal physical property parameter to bring.

Accompanying drawing explanation

Fig. 1 is the prognoses system structural representation of initial set shell thickness in one embodiment of the present invention steel continuous casting crystallizer;

Fig. 2 be one embodiment of the present invention steel continuous casting crystallizer in the Forecasting Methodology flow chart of initial set shell thickness;

The Crystallizer bleed-out initial set base shell solidified structure that Fig. 3 (a) is one embodiment of the present invention and shell thickness detect schematic diagram, and (b) is the sample schematic diagram of (a); C () is the grain structure pattern metallographic schematic diagram of (b);

Fig. 4 be one embodiment of the present invention crystallizer in initial set base shell measured result figure;

Fig. 5 be one embodiment of the present invention crystallizer in dendrite interval measured result figure;

The total view of the dendrite morphology that Fig. 6 (a) is one embodiment of the present invention, (b) is the viewgraph of cross-section of (a); The computational fields of (c) solute microsegregation Mathematical Modeling;

Fig. 7 be the prediction of one embodiment of the present invention steel continuous casting crystallizer in initial set shell growth behavior schematic diagram;

Fig. 8 be one embodiment of the present invention steel continuous casting crystallizer in the predicting the outcome and measured result comparison diagram of initial set shell thickness;

Fig. 9 be one embodiment of the present invention steel continuous casting crystallizer in the predicting the outcome and measured result comparison diagram of initial set base shell dendrite interval.

Detailed description of the invention

Below in conjunction with accompanying drawing, the prognoses system of initial set shell thickness in steel continuous casting crystallizer of the present invention and the detailed description of the invention of method are elaborated.

The prognoses system of initial set shell thickness in the steel continuous casting crystallizer that present embodiment is applied to industry spot, comprises as shown in Figure 1: information acquisition module is used for gathering casting steel grades, crystallizer physical dimension, submersed nozzle physical dimension, continuous casting process condition and along the thickness of solidified slab shell in secondary measured value at crystallizer diverse location place and dendrite interval measured value, described crystallizer physical dimension, comprises width of plate slab, slab thickness, crystallizer height, copper plate thickness, the tank degree of depth, sink thicknesses and nickel layer thickness, described continuous casting process condition, comprises meniscus position, casting speed, inlet water temperature, wide exports water temperature, leptoprosopy exports water temperature, wide cooling water flow and leptoprosopy cooling water flow, described submersed nozzle physical dimension, comprises submersed nozzle immersion depth and submersed nozzle side opening inclination angle, steel grade thermal physical property parameter computing module is used for the casting steel grades that collects according to information acquisition module and dendrite interval measured value, calculate interdendritic solute segregation and solidification path in solidification of molten steel process, and then obtain steel grade thermal physical property parameter and reached crystallizer initial set shell growth prediction module, described steel grade thermal physical property parameter, comprises solid-liquid phase line temperature, thermal conductivity factor, density, specific heat and latent heat of solidification, crystallizer initial set shell growth prediction module is used for delivered heat in crystallizer, MOMENTUM TRANSMISSION and mass transport are at interior macroscopic transport process and copper plate of crystallizer surface forming core, the inner forming core of molten steel and grain growth develop behavior at interior microcosmic solidified structure and are coupled, and according to the crystallizer physical dimension that information acquisition module collects, submersed nozzle physical dimension and continuous casting process condition and the steel grade thermal physical property parameter received from steel grade thermal physical property parameter computing module, prediction casting process crystallizer internal high temperature solidification of molten steel process shell growth behavior is also reached result output module, result output module is used for image conversion ground display crystallizer solidified inside tissue topography, i.e. initial set shell growth process, and quantification ground display crystallizer initial set shell thickness predicted value, the solidified shell measured value of the crystallizer of this initial set shell thickness predicted value and information acquisition module collection is compared, and this comparative result of output display.

Present embodiment produces the Forecasting Methodology of initial set shell thickness in the continuous cast mold of Q345 structural alloy steel detailed description employing system shown in Figure 1 for certain steel mill's continuous casting, and method flow as shown in Figure 2.The slab cross dimensions of the Q345 structural alloy steel that this steel mill's continuous casting is produced is 1830mm × 230mm, and the crystallizer total height of employing and effective depth are respectively 900mm and 800mm.Q345 steel grades is as shown in table 1.This factory continuous casting produce Q345 steel continuous casting crystallizer technique and appointed condition as shown in table 2.

Table 1Q345 steel grades, wt%

C	Si	Mn	P	S
					0.18	0.23	0.88	0.0178	0.0089

The physical dimension of table 2 crystallizer and submersed nozzle and continuous casting process condition

First bleed-out base shell is dissected by experiment, and prepare along crystallizer height and width the bleed-out base shell sample that cross section is 4cm × 1cm, as shown in Fig. 3 (a) He Fig. 3 (b), and according to a definite sequence, bleed-out base shell sample is numbered, then adopt the nital corrosion bleed-out base shell sample 30 ~ 40s of 6% ~ 10%, obtain bleed-out base shell solidification features.Observe the microstructure morphology figure after the corrosion of bleed-out base shell sample under an optical microscope, the microcosmic solidified structure change caused is changed by cooling condition before and after comparison bleed-out, determine the initial set base shell actual (real) thickness along crystallizer diverse location place, thus reject when bleed-out occurs and stick macroscopic measurement shell thickness caused by molten steel shortcoming bigger than normal.As Fig. 3 (c) is depicted as typical solidified shell grain structure, the intermediate zone having a black can be obviously found out in metallograph from figure, intermediate zone is larger-size equi-axed crystal district near crystallizer side, intermediate zone is formed the equiax crystal district that size is relatively little.From microcosmic angle analysis, when bleed-out occurs, be rough and crystalline in branch near the initial solidification base shell edge of molten steel side, interdendritic will the not solidified molten steel of residual fraction, because molten steel has stickiness, during bleed-out, in crystallizer, not solidified molten steel also can continue to be attached on base shell and grows.Now, interdendritic molten steel and the molten steel be attached on base shell will solidify in opposite directions, and its process of setting constantly squeezes solute, occur the black intermediate zone of a soluterich after making to corrode, the edge of solidified shell when being bleed-out, as shown in white arrow in Fig. 3 (c).By measuring the distance of sample between crystallizer side to this boundary place, determine the actual thickness of base shell, as shown in Figure 4.The dendrite interval along the distribution of crystallizer short transverse on slab wide Central Symmetry face is measured, as shown in Figure 5 by the metallograph shown in Fig. 3 (c).

Dendrite interval measured value further according to Fig. 5 and the Q345 alloy structure steel grade composition shown in table 1, calculate interdendritic solute segregation and solidification path in solidification of molten steel process, and then obtain steel grade thermal physical property parameter, comprise solid-liquid phase line temperature, thermal conductivity factor, density, specific heat and latent heat of solidification; Comprise the steps:

S100: according to the pick-up behavior of interdendritic solute conservation principle and solutes accumulation principle and field trash MnS, set up solute microsegregation Mathematical Modeling, calculate interdendritic solute segregation and solidification path in solidification of molten steel process, obtain the functional relation of each phase fraction and temperature; Present embodiment supposition dendrite morphology is regular hexagon, and according to its symmetry, its general principle as shown in Figure 6, is chosen a wherein equilateral delta-shaped region and implemented microsegregation calculated with mathematical model process as computational fields;

Solute microsegregation Mathematical Modeling is:

$\frac{\∂C_{s,i}}{\∂t}=\frac{\∂}{\∂x}\left(D_{s,i}\right(T\left)\frac{\∂C_{s,i}}{\∂x}\right)---\left(1\right)$

Wherein, primary condition is: as t=0, boundary condition is: when x=0 and λ/2, λ is dendrite interval, m; c _l,iand C _s,ibe respectively solute concentration in liquid phase l of the initial concentration of solute element i in molten steel, solute element i and the solute concentration of solute element i in solid phase s, wt%; D _s,i(T) be the diffusion coefficient of solute element i in solid phase, m ²/ s; T is the time, second; for solute element i solid liquid interface equilibrium distribution coefficient; Described solid phase comprises ferritic phase δ and austenite phase γ;

Molten steel liquidus temperature T is depended in phase transformation in solidification of molten steel process _ltemperature is started with δ/γ phase in version

$T_l=1536-\underset{i}{\Σ}{m}_i\·C_{l,i}^0---\left(2\right)$

$T_{{\mathrm{Ar}}_4}=1392-\underset{i}{\Σ}{n}_i\·k_{i,0}^{\mathrm{\δ}/l}\·C_{l,i}^{\mathrm{\δ}}---\left(3\right)$

In formula, for the concentration of solute element i in δ/γ boundary place liquid phase; for solute element i is at δ/γ interface equilibrium distribution coefficient; m _iand n _ibe respectively liquidus curve and Ar in pseudo-binary Fe-i phasor ₄line slope, specifically as shown in table 3.

The equilibrium distribution coefficient of table 3 solute element i and diffusion coefficient

Note: R=1.987cal/molK, T are kelvin degree.

In addition, the pick-up behavior of field trash MnS calculates by the chemical balance that [Mn]+[S]=(MnS) reacts, and its standard Gibbs free energy becomes Δ G ^Θemploying following formula calculates:

In liquid phase: Δ G ^Θ=-165248.81+90.90T (4)

Now, forward position, s/l interface residue solute element concentration is equilibrium concentration:

$C_{l,Mn}^t\·f_{Mn}\·C_{l,S}^t\·f_S=1/K_{l,MnS}---\left(5\right)$

${\mathrm{Cin}}_{Mn}^t\·M_S={\mathrm{Cin}}_S^t\·M_{Mn}---\left(6\right)$

In formula, K _{l, MnS}for the equilibrium constant of MnS evolution reaction; with be respectively the mass fraction of solute element Mn and S in t molten steel, wt%; with being respectively t due to MnS separates out the amount of solute element Mn and S consumed respectively, wt%; M _sand M _mnbe respectively the molal weight of solute element Mn and S, g/mol; f _mnand f _sthe activity coefficient being respectively solute element Mn, S in molten steel can calculate gained by following formula:

$\lg f_i=e_i^i\left({\mathrm{\%C}}_{l,i}\right)+\underset{i\≠j}{\Σ}{e}_i^j\left({\mathrm{\%C}}_{l,j}\right)---\left(7\right)$

In formula: e _i ⁱ, e _i ^jfor activity interaction coefficient, as shown in table 4.

Activity interaction coefficient during table 41873K ^[79]

e i j	C	Si	Mn	P	S	Cr
							Mn	-0.0538	-0.0327	0	-0.06	-0.048	0.0036
S	0.112	0.063	-0.026	0.29	-0.028	-0.011

S200: each phase fraction obtained according to step S100 and the functional relation of temperature, calculates steel grade thermal physical property parameter, comprises following concrete steps:

S201: calculate solidus temperature; Temperature computation solidus temperature when be liquid phase fraction being 0 according to solidus temperature;

S202: calculation of thermal conductivity; Steel thermal conductivity factor and temperature, the following relational expression between carbon content and phase fraction:

k _steel＝k _δf _δ+k _γf _γ+k _lf _l(8)

Wherein, k _steelfor the thermal conductivity factor of steel, W/ (m DEG C); f _δ, f _γand f _lbe respectively point rate shared by ferritic phase δ, austenite phase γ and liquid phase l; T is temperature, DEG C; w _cfor carbon content, wt%; k _γ=21.6-8.3510 ^-3t; k _l=39.0; a ₁=0.425-4.38510 ^-4t; a ₂=0.209+1.0910 ^-3t;

S203: bulk density; Steel density adopts following formulae discovery:

ρ＝ρ _γf _γ+ρ _δf _δ+ρ _lf _l(9)

${\mathrm{\ρ}}_{\mathrm{\γ}}=\frac{100(8106-0.51T)}{(100-w_C)(1+0.008{\left(w_C^{\mathrm{\γ}}\right)}^3)}---\left(10\right)$

${\mathrm{\ρ}}_{\mathrm{\δ}}=\frac{100(8111-0.47T)}{(100-w_C)(1+0.013{\left(w_C^{\mathrm{\δ}}\right)}^3)}---\left(11\right)$

ρ _l＝7100-73w _C-(0.8-0.09w _C)(T-1550)(12)

In formula, ρ is the density of steel, kg/m ³;

S204: calculate specific heat; Following relational expression is met between phase composition in specific heat and steel in steel process of setting:

c＝c _δf _δ+c _γf _γ+c _lf _l(13)

In formula: c is the specific heat capacity of steel, J/ (kg DEG C); c _δ=441.3942+0.17744236T; c _γ=429.8495+0.1497802T; c _l=824.6157;

S205: calculate latent heat of solidification; Adopt Enthalpy method to calculate the release of latent heat in process of setting, heat content H is decomposed into sensible heat and latent heat Δ H=f _lΔ H _f, namely heat content is:

$H=h_{ref}+{\∫}_{T_{ref}}^{T}cdT+f_l{\mathrm{\ΔH}}_f---\left(14\right)$

In formula, h _reffor reference heat content, J/kg; Δ H _fmelting heat, J/kg; T _reffor reference temperature, K;

S300: the crystallizer physical dimension, submersed nozzle physical dimension and the continuous casting process condition that collect according to information acquisition module further and the steel grade thermal physical property parameter received from steel grade thermal physical property parameter computing module, solve crystallizer molten steel flow field, mould temperature field and crystallizer solute field, and macroscopic transport process in crystallizer is developed behavior with microcosmic solidified structure in crystallizer be coupled, prediction continuous cast mold internal high temperature solidification of molten steel process shell growth behavior further; Comprise the steps:

S301: according to delivered heat, MOMENTUM TRANSMISSION and mass transport process in crystallizer, solve crystallizer molten steel flow field, mould temperature field and crystallizer solute field, specifically comprise the steps:

S3011: calculate crystallizer molten steel flow field; Crystallizer molten steel flow field is calculated according to following equation;

Continuity equation:

$\frac{\∂\left(\mathrm{\ρ}u\right)}{\∂x}+\frac{\∂\left(\mathrm{\ρ}v\right)}{\∂y}+\frac{\∂\left(\mathrm{\ρ}w\right)}{\∂z}=0---\left(15\right)$

Wherein, u, v and w are respectively the component of velocity field u (u, v, w) along three dimensional space coordinate direction of principal axis x, y and z, m/s;

MOMENTUM TRANSMISSION equation: the equation of momentum is in the x-direction shown below, along the equation of momentum in other direction and following formula similar;

$\begin{array}{c}\frac{\∂\left(\mathrm{\ρ}u\right)}{\∂t}+\frac{\∂\left(\mathrm{\ρ}uu\right)}{\∂x}+\frac{\∂\left(\mathrm{\ρ}uv\right)}{\∂y}+\frac{\∂\left(\mathrm{\ρ}uw\right)}{\∂z}=\frac{\∂}{\∂x}\[{\mathrm{\μ}}_{eff}(\frac{\∂u}{\∂x}+\frac{\∂u}{\∂x})\]+\frac{\∂}{\∂y}\[{\mathrm{\μ}}_{eff}(\frac{\∂u}{\∂y}+\frac{\∂v}{\∂x})\]+\\ \frac{\∂}{\∂x}\[{\mathrm{\μ}}_{eff}(\frac{\∂u}{\∂z}+\frac{\∂w}{\∂x})\]-\frac{\∂p}{\∂x}+{\mathrm{\ρg}}_x\end{array}---\left(16\right)$

Wherein μ _efffor virtual viscosity coefficient, Pas is laminar flow viscosity μ _lwith turbulent viscosity μ _tsum, namely c _μfor constant; P is pressure, Pa; g _xfor gravity component in the x-direction; K is tubulence energy; ε is dissipative shock wave;

Tubulence energy equation and the unification of dissipative shock wave equation are shown below:

$\frac{\∂\left(\mathrm{\ρ}u\mathrm{\Φ}\right)}{\∂x}+\frac{\∂\left(\mathrm{\ρ}v\mathrm{\Φ}\right)}{\∂y}+\frac{\∂\left(\mathrm{\ρ}w\mathrm{\Φ}\right)}{\∂z}=\frac{\∂}{\∂x}\[\mathrm{\Ω}\frac{\∂k}{\∂x}\]+\frac{\∂}{\∂y}\[\mathrm{\Ω}\frac{\∂k}{\∂y}\]+\frac{\∂}{\∂z}\[\mathrm{\Ω}\frac{\∂k}{\∂z}\]+S^0---\left(17\right)$

For tubulence energy k, Φ=k, s ⁰=G-ρ ε;

For dissipative shock wave ε, Φ=ε, $\mathrm{\Ω}={\mathrm{\μ}}_l+\frac{{\mathrm{\μ}}_t}{{\mathrm{\σ}}_{\mathrm{\ϵ}}},S^0=\frac{C_{1}G\mathrm{\ϵ}-C_2{\mathrm{\ρ\ϵ}}^2}{k};$

C in formula ₁, C ₂, σ _kand σ _εbe constant; Symbol G can represent with formula (18);

$G={\mathrm{\μ}}_t(2{\left(\frac{\∂u}{\∂x}\right)}^2+2{\left(\frac{\∂v}{\∂y}\right)}^2+2{\left(\frac{\∂w}{\∂z}\right)}^2+{\left(\frac{\∂u}{\∂y}+\frac{\∂v}{\∂x}\right)}^2+{\left(\frac{\∂u}{\∂z}+\frac{\∂w}{\∂x}\right)}^2+{\left(\frac{\∂v}{\∂z}+\frac{\∂w}{\∂y}\right)}^2)---\left(18\right)$

S3012: calculate mould temperature field; Delivered heat equation is as follows:

$\frac{\∂}{\∂t}\left(\mathrm{\ρ}H\right)+\▿\·\left(\mathrm{\ρ}uH\right)=\▿\·\left(\right(k_{steel}+c\frac{{\mathrm{\μ}}_t}{{\mathrm{\σ}}_t})\▿T)---\left(19\right)$

Wherein k _steelfor the thermal conductivity factor of steel, W/ (m DEG C); σ _tfor constant, value 0.9 ~ 1.0;

S302: develop behavior according to copper plate of crystallizer surface forming core, the inner forming core of molten steel and grain growth at interior microcosmic solidified structure further, in prediction solidification of molten steel process, the growth behavior of crystal grain and dendrite, specifically comprises the steps

S3021: rule of thumb forming core parameter, prediction solidification of molten steel nucleation process;

Nucleation Model:

$n\left(\mathrm{\Δ}T\right)=\frac{n_{max}}{\sqrt{2\mathrm{\π}}{\mathrm{\ΔT}}_{\mathrm{\σ}}}{\∫}_0^{\mathrm{\Δ}T}\exp \[-\frac{1}{2}\left(\frac{{\mathrm{\ΔT}}^{\′}-{\mathrm{\ΔT}}_n}{{\mathrm{\ΔT}}_{\mathrm{\σ}}}\right)\]d\left({\mathrm{\ΔT}}^{\′}\right)---\left(20\right)$

In formula, n (Δ T) is grain density; Δ T is degree of supercooling, K; n _maxfor initial forming core substrate number, Δ T _n, Δ T _σbe respectively average forming core degree of supercooling and standard variance degree of supercooling; Δ T' is degree of supercooling integration variable, K; Molten steel forming core parameter empirical value is in table 5.

Table 5 experience molten steel forming core parameter

S3022: calculate solute field distribution in solidification of molten steel process;

Bring the crystallizer molten steel flow field result that step S3011 calculates into following mass transmission equation:

$\frac{\∂C}{\∂t}+\▿\·\left(\mathrm{\ξ}uC\right)=\▿\·(D\▿C)---\left(21\right)$

In formula, C is solute concentration, wt%; D is solutes accumulation coefficient, m ²/ s; ξ is cellular state parameter;

S3023: the relation setting up temperature field, solid liquid interface place and solute field, obtains the equilibrium concentration at solid liquid interface place;

The available following formula of relation of temperature field, solid liquid interface place and solute field represents:

In formula, T ^*for solid liquid interface place temperature, K; m ₀for liquidous slopes; C ₀for alloy initial concentration, for solid liquid interface place liquid phase solute concentration, Γ is Gibbs-Thomson coefficient, and κ is average solid liquid interface curvature, for anisotropy of interface energy function, θ is dendrite preferential growth angle, for the angle of solid liquid interface method phase and x-axis.

Solid liquid interface curvature is determined by interface solid rate gradient, can formulae discovery as follows:

$\mathrm{\κ}=\frac{2{\left(f_s\right)}_x{\left(f_s\right)}_y{\left(f_s\right)}_{xy}-{\left(f_s\right)}_x^2{\left(f_s\right)}_{yy}-{\left(f_s\right)}_y^2{\left(f_s\right)}_{xx}}{{\[{\left(f_s\right)}_x^2+{\left(f_s\right)}_y^2\]}^{3/2}}---\left(23\right)$

The anisotropy of interfacial tension can by following formulae discovery:

In formula, (f _s) _x(f _s) _yfor the single order local derviation of solid rate, (f _s) _xx, (f _s) _xy(f _s) _yyfor the second order local derviation of solid rate, σ is Interface Anisotropy parameter;

S3024: according to the relation of the solute element equilibrium concentration at solid liquid interface place and the solute element concentration in forward position, interface, i.e. forward position, interface solute concentration gradient, determines solid liquid interface rate travel;

The dentrite tip speed of growth controls by interface solute concentration, can by following formulae discovery:

$v_n{C}_1^{*}(1-k_0)=D_s\frac{\∂C_s}{\∂n}{|}^{*}-D_1\frac{\∂C_1}{\∂n}{|}^{*}---\left(26\right)$

In formula, v _nfor interface method phase shift speed, m/s; k ₀for solute balance distribution coefficient; D _lfor solute element diffusion coefficient in the liquid phase, m ²/ s; C _sand C _lbe respectively solid phase and liquid concentration, wt%;

S400: initial set shell growth behavior in the crystallizer of output display prediction graphically, as shown in Figure 7.Initial set shell growth behavior in the crystallizer shown in Fig. 7, clearly can find out the solidified shell microscopic informations such as crystallizer differing heights place thickness of solidified slab shell in secondary, grain morphology, thus provides intuitive and reliable information for optimizing continuous cast mold process conditions.By the comparative result of the dendrite interval predicted value shown in the predicted value of initial set shell thickness in the crystallizer shown in Fig. 8 and the comparative result of initial set base shell actual (real) thickness and Fig. 9 and dendrite interval measured value, can find out that the initial set shell thickness that the present invention predicts and dendrite interval can coincide well with measured value.

Claims (7)

1. the prognoses system of initial set shell thickness in steel continuous casting crystallizer, is characterized in that: comprising:

Information acquisition module: be used for gathering casting steel grades, crystallizer physical dimension, submersed nozzle physical dimension, continuous casting process condition and along the initial set shell thickness measured value at crystallizer diverse location place and dendrite interval measured value; Described crystallizer physical dimension, comprises width of plate slab, slab thickness, crystallizer height, copper plate thickness, the tank degree of depth, sink thicknesses and nickel layer thickness; Described continuous casting process condition, comprises meniscus position, casting speed, inlet water temperature, wide exports water temperature, leptoprosopy exports water temperature, wide cooling water flow and leptoprosopy cooling water flow; Described submersed nozzle physical dimension, comprises submersed nozzle immersion depth and submersed nozzle side opening inclination angle;

Steel grade thermal physical property parameter computing module: the casting steel grades collected according to information acquisition module and dendrite interval measured value, calculate interdendritic solute segregation and solidification path in solidification of molten steel process, and then obtain steel grade thermal physical property parameter and reached crystallizer initial set shell growth prediction module; Described steel grade thermal physical property parameter, comprises solid-liquid phase line temperature, thermal conductivity factor, density, specific heat and latent heat of solidification;

Crystallizer initial set shell growth prediction module: by delivered heat in crystallizer, MOMENTUM TRANSMISSION and mass transport are at interior macroscopic transport process and copper plate of crystallizer surface forming core, the inner forming core of molten steel and grain growth develop behavior at interior microcosmic solidified structure and are coupled, and according to the crystallizer physical dimension that information acquisition module collects, submersed nozzle physical dimension and continuous casting process condition and the steel grade thermal physical property parameter received from steel grade thermal physical property parameter computing module, prediction casting process crystallizer internal high temperature solidification of molten steel process shell growth behavior is also reached result output module,

Result output module: the crystallizer solidified inside tissue topography of image conversion ground display prediction, i.e. initial set shell growth process, and quantification ground display crystallizer initial set shell thickness predicted value, the initial set base shell measured value of the crystallizer of this initial set shell thickness predicted value and information acquisition module collection is compared, and this comparative result of output display.

2. in the steel continuous casting crystallizer adopting system described in claim 1, the Forecasting Methodology of initial set shell thickness, is characterized in that: comprise the steps:

Step 1: get bleed-out base shell sample, carries out bleed-out base shell microcosmic solidified structure and detects, obtain the initial set shell thickness measured value along crystallizer diverse location place and dendrite interval measured value;

Step 2: gather initial information;

Comprise casting steel grades, crystallizer physical dimension, submersed nozzle physical dimension, continuous casting process condition and along the initial set shell thickness measured value at crystallizer diverse location place and dendrite interval measured value; Described crystallizer physical dimension, comprises width of plate slab, slab thickness, crystallizer height, copper plate thickness, the tank degree of depth, sink thicknesses and nickel layer thickness; Described continuous casting process condition, comprises meniscus position, casting speed, inlet water temperature, wide exports water temperature, leptoprosopy exports water temperature, wide cooling water flow and leptoprosopy cooling water flow; Described submersed nozzle physical dimension, comprises submersed nozzle immersion depth and submersed nozzle side opening inclination angle;

Step 3: the dendrite interval measured value gathered according to step 2 and casting steel grades, calculate interdendritic solute segregation and solidification path in solidification of molten steel process, and then obtain steel grade thermal physical property parameter, comprise solid-liquid phase line temperature, thermal conductivity factor, density, specific heat and latent heat of solidification;

Step 3.1: according to the pick-up behavior of interdendritic solute conservation principle and solutes accumulation principle and field trash MnS, set up solute microsegregation Mathematical Modeling, calculate interdendritic solute segregation and solidification path in solidification of molten steel process, obtain the functional relation of each phase fraction and temperature;

Step 3.2: each phase fraction obtained according to step 3.1 and the functional relation of temperature, calculates steel grade thermal physical property parameter, comprises solid-liquid phase line temperature, thermal conductivity factor, density, specific heat and latent heat of solidification;

Step 4: the crystallizer physical dimension, submersed nozzle physical dimension and the continuous casting process condition that collect according to information acquisition module and the steel grade thermal physical property parameter received from steel grade thermal physical property parameter computing module, solve crystallizer molten steel flow field, mould temperature field and crystallizer solute field, and macroscopic transport process in crystallizer is developed behavior with microcosmic solidified structure in crystallizer be coupled, prediction continuous cast mold internal high temperature solidification of molten steel process shell growth behavior further;

Step 5: export and the initial set shell thickness at diverse location place in Solidification Microstructure Morphology and crystallizer in the crystallizer showing prediction, and compare with the initial set shell thickness measured value that step 1 gathers, and by comparative result output display.

3. the Forecasting Methodology of initial set shell thickness in steel continuous casting crystallizer according to claim 2, is characterized in that: described step 3.1 specifically comprises following content:

Solute microsegregation Mathematical Modeling is:

$\frac{\∂C_{s,i}}{\∂t}=\frac{\∂}{\∂x}\left(D_{s,i}\right(T\left)\frac{\∂C_{s,i}}{\∂x}\right)---\left(1\right)$

Wherein, primary condition is: as t=0, boundary condition is: when x=0 and λ/2, λ is dendrite interval, m; c _l,iand C _s,ibe respectively solute concentration in liquid phase l of the initial concentration of solute element i in molten steel, solute element i and the solute concentration of solute element i in solid phase s, wt%; D _s,i(T) be the diffusion coefficient of solute element i in solid phase, m ²/ s; T is the time, second; for solute element i solid liquid interface equilibrium distribution coefficient; Described solid phase comprises ferritic phase δ and austenite phase γ;

Molten steel liquidus temperature T is depended in phase transformation in solidification of molten steel process _ltemperature is started with δ/γ phase in version

$T_l=1536-\underset{i}{\Σ}{m}_i\·C_{l,i}^0---\left(2\right)$

$T_{{\mathrm{Ar}}_4}=1392-\underset{i}{\Σ}{n}_i\·k_{i,0}^{\mathrm{\δ}/1}\·C_{1,i}^{\mathrm{\δ}}---\left(3\right)$

In formula, for the concentration of solute element i in δ/γ boundary place liquid phase; m _iand n _ibe respectively liquidus curve and Ar in pseudo-binary Fe-i phasor ₄line slope; for solute element i is at δ/γ interface equilibrium distribution coefficient;

In addition, the pick-up behavior of field trash MnS calculates by the chemical balance that [Mn]+[S]=(MnS) reacts, and its standard Gibbs free energy becomes Δ G ^Θemploying following formula calculates:

In liquid phase: Δ G ^Θ=-165248.81+90.90T (4)

Now, forward position, s/l interface residue solute element concentration is equilibrium concentration:

$C_{l,Mn}^t\·f_{Mn}\·C_{l,S}^t\·f_S=1/K_{l,MnS}---\left(5\right)$

${\mathrm{Cin}}_{Mn}^t\·M_S={\mathrm{Cin}}_S^t\·M_{Mn}---\left(6\right)$

In formula, K _{l, MnS}for the equilibrium constant of MnS evolution reaction; with be respectively the mass fraction of solute element Mn and S in t molten steel, wt%; with being respectively t due to MnS separates out the amount of solute element Mn and S consumed respectively, wt%; M _sand M _mnbe respectively the molal weight of solute element Mn and S, g/mol; f _mnand f _sbe respectively the activity coefficient of solute element Mn and S in molten steel.

4. the Forecasting Methodology of initial set shell thickness in steel continuous casting crystallizer according to claim 2, is characterized in that: described step 4 comprises the steps:

Step 4.1: according to delivered heat, MOMENTUM TRANSMISSION and mass transport process in crystallizer, solve crystallizer molten steel flow field, mould temperature field and crystallizer solute field;

Step 4.1.1: calculate crystallizer molten steel flow field;

Crystallizer molten steel flow field is calculated according to following equation;

Continuity equation:

$\frac{\∂\left(\mathrm{\ρ}u\right)}{\∂x}+\frac{\∂\left(\mathrm{\ρ}v\right)}{\∂y}+\frac{\∂\left(\mathrm{\ρ}w\right)}{\∂z}=0---\left(15\right)$

Wherein, u, v and w are respectively the component of velocity field u (u, v, w) along three dimensional space coordinate direction of principal axis x, y and z, m/s; MOMENTUM TRANSMISSION equation: the equation of momentum is in the x-direction shown below, along the equation of momentum in other direction and following formula similar;

$\begin{array}{c}\frac{\∂\left(\mathrm{\ρ}u\right)}{\∂t}+\frac{\∂\left(\mathrm{\ρ}uu\right)}{\∂x}+\frac{\∂\left(\mathrm{\ρ}uv\right)}{\∂y}+\frac{\∂\left(\mathrm{\ρ}uw\right)}{\∂z}=\frac{\∂}{\∂x}\[{\mathrm{\μ}}_{eff}\left(\frac{\∂u}{\∂x}+\frac{\∂u}{\∂x}\right)\]+\frac{\∂}{\∂y}\[{\mathrm{\μ}}_{eff}\left(\frac{\∂u}{\∂y}+\frac{\∂v}{\∂x}\right)\]+\\ \frac{\∂}{\∂x}\[{\mathrm{\μ}}_{eff}\left(\frac{\∂u}{\∂z}+\frac{\∂w}{\∂x}\right)\]-\frac{\∂p}{\∂x}{\mathrm{\ρg}}_x\end{array}---\left(16\right)$

Wherein μ _efffor virtual viscosity coefficient, Pas is laminar flow viscosity μ _lwith turbulent viscosity μ _tsum, namely c _μfor constant; P is pressure, Pa; g _xfor gravity component in the x-direction; K is tubulence energy; ε is dissipative shock wave;

Tubulence energy equation and the unification of dissipative shock wave equation are shown below:

$\frac{\∂\left(\mathrm{\ρ}u\mathrm{\Φ}\right)}{\∂x}+\frac{\∂\left(\mathrm{\ρ}v\mathrm{\Φ}\right)}{\∂y}+\frac{\∂\left(\mathrm{\ρ}w\mathrm{\Φ}\right)}{\∂z}=\frac{\∂}{\∂x}\[\mathrm{\Ω}\frac{\∂k}{\∂x}\]+\frac{\∂}{\∂y}\[\mathrm{\Ω}\frac{\∂k}{\∂y}\]+\frac{\∂}{\∂z}\[\mathrm{\Ω}\frac{\∂k}{\∂z}\]+S^0---\left(17\right)$

For tubulence energy k, Φ=k, s ⁰=G-ρ ε;

For dissipative shock wave ε, Φ=ε, $\mathrm{\Ω}={\mathrm{\μ}}_l+\frac{{\mathrm{\μ}}_t}{{\mathrm{\σ}}_{\mathrm{\ϵ}}},S^0=\frac{C_{1}G\mathrm{\ϵ}-C_2{\mathrm{\ρ\ϵ}}^2}{k};$

C in formula ₁, C ₂, σ _kand σ _εbe constant; Symbol G can represent with formula (18);

$G={\mathrm{\μ}}_t(2{\left(\frac{\∂u}{\∂x}\right)}^2+2{\left(\frac{\∂v}{\∂y}\right)}^2+2{\left(\frac{\∂w}{\∂z}\right)}^2+{\left(\frac{\∂u}{\∂y}+\frac{\∂v}{\∂x}\right)}^2+{\left(\frac{\∂u}{\∂z}+\frac{\∂w}{\∂x}\right)}^2+{\left(\frac{\∂v}{\∂z}+\frac{\∂w}{\∂y}\right)}^2)---\left(18\right)$

Step 4.1.2: calculate mould temperature field

Calculate according to delivered heat equation, as shown in the formula:

$\frac{\∂}{\∂t}\left(\mathrm{\ρ}H\right)+\▿\·\left(\mathrm{\ρ}uH\right)=\▿\·\left(\right(k_{steel}+c\frac{{\mathrm{\μ}}_t}{{\mathrm{\σ}}_t})\▿T)---\left(19\right)$ Wherein k _steelfor the thermal conductivity factor of steel, W/ (m DEG C); σ _tfor constant, value 0.9 ~ 1.0;

Step 4.2: the dendritic growth that the grain growth controlled according to copper plate of crystallizer surface forming core, the inner forming core of molten steel and thermal diffusion and solutes accumulation control develops behavior at interior microcosmic solidified structure, the growth behavior of crystal grain and dendrite in prediction solidification of molten steel process;

Step 4.2.1: rule of thumb forming core parameter, prediction solidification of molten steel nucleation process;

Nucleation Model is:

$n\left(\mathrm{\Δ}T\right)=\frac{n_{max}}{\sqrt{2\mathrm{\π}}{\mathrm{\ΔT}}_{\mathrm{\σ}}}{\∫}_0^{\mathrm{\Δ}T}\exp \[-\frac{1}{2}\left(\frac{{\mathrm{\ΔT}}^{\′}-{\mathrm{\ΔT}}_n}{{\mathrm{\ΔT}}_{\mathrm{\σ}}}\right)\]d\left({\mathrm{\ΔT}}^{\′}\right)---\left(20\right)$

In formula, n (Δ T) is grain density; Δ T is degree of supercooling, K; n _maxfor initial forming core substrate number, Δ T _n, Δ T _σbe respectively average forming core degree of supercooling and standard variance degree of supercooling; Δ T' is degree of supercooling integration variable, K;

Step 4.2.2: calculate solute field distribution in solidification of molten steel process;

The crystallizer molten steel flow field result obtained by step 4.1.1 brings following mass transmission equation into:

$\frac{\∂C}{\∂t}+\▿\·\left(\mathrm{\ξ}uC\right)=\▿\·(D\▿C)---\left(21\right)$ In formula, C is solute concentration, wt%; D is solutes accumulation coefficient, m ²/ s; ξ is cellular state parameter;

Step 4.2.3: the relation setting up temperature field, solid liquid interface place and solute field, obtains the equilibrium concentration at solid liquid interface place;

The available following formula of relation of temperature field, solid liquid interface place and solute field represents:

in formula, T ^*for solid liquid interface place temperature, K; m ₀for liquidous slopes; C ₀for alloy initial concentration, for solid liquid interface place liquid phase solute concentration, Γ is Gibbs-Thomson coefficient, and κ is average solid liquid interface curvature, for anisotropy of interface energy function, θ is dendrite preferential growth angle, for the angle of solid liquid interface method phase and x-axis;

Solid liquid interface curvature is determined by interface solid rate gradient, can formulae discovery as follows:

$\mathrm{\κ}=\frac{2{\left(f_s\right)}_x{\left(f_s\right)}_y{\left(f_s\right)}_{xy}-{\left(f_s\right)}_x^2{\left(f_s\right)}_{yy}-{\left(f_s\right)}_y^2{\left(f_s\right)}_{xx}}{{\[{\left(f_s\right)}_x^2+{\left(f_s\right)}_y^2\]}^{3/2}}---\left(23\right)$

The anisotropy of interfacial tension can by following formulae discovery:

In formula, (f _s) _x(f _s) _yfor the single order local derviation of solid rate, (f _s) _xx, (f _s) _xy(f _s) _yyfor the second order local derviation of solid rate, σ is Interface Anisotropy parameter;

Step 4.2.4: according to the relation of the solute element equilibrium concentration at solid liquid interface place and the solute element concentration in forward position, interface, i.e. forward position, interface solute concentration gradient, determines solid liquid interface rate travel;

The dentrite tip speed of growth controls by interface solute concentration, can by following formulae discovery:

$v_n{C}_l^{*}(1-k_0)=D_s\frac{\∂C_s}{\∂n}{|}^{*}-D_l\frac{\∂C_l}{\∂n}{|}^{*}---\left(26\right)$ In formula, v _nfor interface method phase shift speed, m/s; k ₀for solute balance distribution coefficient; D _lfor solute element diffusion coefficient in the liquid phase, m ²/ s; C _sand C _lbe respectively solid phase and liquid concentration, wt%.

5. a bleed-out base shell microcosmic solidified structure detection method, detects for bleed-out base shell microcosmic solidified structure in step 1 according to claim 2, it is characterized in that: the method is:

Bleed-out base shell is dissected, gets bleed-out base shell sample; Adopt corrosive agent to carry out corrosion to bleed-out base shell sample and obtain bleed-out base shell solidification features; Observe the microstructure morphology after the corrosion of bleed-out base shell sample, changed the microcosmic solidified structure change caused by cooling condition before and after comparison bleed-out, determine the initial set shell thickness measured value along crystallizer diverse location place and dendrite interval measured value.

6. bleed-out base shell microcosmic solidified structure detection method according to claim 5, is characterized in that: described corrosive agent is the nital of 6% ~ 10%.

7. bleed-out base shell microcosmic solidified structure detection method according to claim 6, is characterized in that: the time that described employing corrosive agent corrodes bleed-out base shell sample is 30 ~ 40s.