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含氟连铸保护渣黏度检测与预测模型

赵忠宇 赵俊学 谭泽馨 屈波樵 崔雅茹

赵忠宇, 赵俊学, 谭泽馨, 屈波樵, 崔雅茹. 含氟连铸保护渣黏度检测与预测模型[J]. 工程科学学报, 2021, 43(4): 529-536. doi: 10.13374/j.issn2095-9389.2020.05.03.002
引用本文: 赵忠宇, 赵俊学, 谭泽馨, 屈波樵, 崔雅茹. 含氟连铸保护渣黏度检测与预测模型[J]. 工程科学学报, 2021, 43(4): 529-536. doi: 10.13374/j.issn2095-9389.2020.05.03.002
ZHAO Zhong-yu, ZHAO Jun-xue, TAN Ze-xin, QU Bo-qiao, CUI Ya-ru. Viscosity detection and the estimation model of fluorine-containing mold flux for continuous casting[J]. Chinese Journal of Engineering, 2021, 43(4): 529-536. doi: 10.13374/j.issn2095-9389.2020.05.03.002
Citation: ZHAO Zhong-yu, ZHAO Jun-xue, TAN Ze-xin, QU Bo-qiao, CUI Ya-ru. Viscosity detection and the estimation model of fluorine-containing mold flux for continuous casting[J]. Chinese Journal of Engineering, 2021, 43(4): 529-536. doi: 10.13374/j.issn2095-9389.2020.05.03.002

含氟连铸保护渣黏度检测与预测模型

doi: 10.13374/j.issn2095-9389.2020.05.03.002
基金项目: 国家自然科学基金资助项目(51674185,51674186)
详细信息
    通讯作者:

    E-mail:zhaojunxue1962@126.com

  • 中图分类号: F407.3

Viscosity detection and the estimation model of fluorine-containing mold flux for continuous casting

More Information
  • 摘要: 采用旋转柱体法对不同类型的含氟连铸保护渣黏度进行检测,并基于Arrhenius方程通过非线性回归分析建立了新的黏度预测模型,分析了组分变化对黏度的影响。结合模型计算和实验检测,建立了CaF2‒Na2O‒Al2O3‒CaO‒SiO2‒MgO渣系的等黏度图。结果表明,与传统的含氟连铸保护渣黏度预测模型相比,该模型计算的偏差在10%以内,当渣中w(CaF2)超过20%时,偏差逐渐增大,主要由于氟化物挥发造成炉渣成分变化,最终黏度实测值与炉渣初始成分不符,造成模型无法对黏度有效预测。此外,研究发现,CaF2的增加能显著降低炉渣黏度,而Al2O3和Na2O对黏度的影响受CaF2含量的限制。当w(CaF2)>17%,炉渣黏度随Al2O3含量增加而减小,当w(CaF2)<17%,Al2O3的增加使炉渣黏度显著增大;当w(CaF2)>11.5%,炉渣黏度随Na2O含量增加显著下降,当w(CaF2)<11.5%,Na2O含量变化对黏度的影响并不明显。此外,该等黏度图表明低黏度区w(CaF2)接近14%。通过调整等黏度图中各组分比例,可以改善保护渣的黏度和流动性,供钢铁工业应用。
  • 图  1  黏度−温度线性分析

    Figure  1.  Linear analysis of lnη to 1/T

    图  2  黏度参数拟合数值变化。(a)lnA;(b)B

    Figure  2.  Viscosity parameter fitting value: (a) lnA; (b) B

    图  3  含氟保护渣黏度预测值与检测值对比。(a)Riboud模型;(b)Iida模型;(c)Mills模型;(d)本研究模型

    Figure  3.  Estimated and measured viscosities of fluorine-containing mold flux: (a) Riboud model; (b) Iida model; (c) Mills model; (d) studied model

    图  4  CaF2‒CaO‒SiO2三元渣黏度预测值与检测值对比。(a)Mills模型;(b)本研究模型

    Figure  4.  Estimated and measured viscosities of CaF2‒CaO‒SiO2: (a) Mills model; (b) studied model

    图  5  CaF2,Na2O和Al2O3成分变化对保护渣黏度影响

    Figure  5.  Effect of CaF2, Na2O, and Al2O3 on the viscosity of mold flux

    图  6  CaF2‒Na2O‒Al2O3‒CaO‒SiO2‒MgO等黏度图(M=0.9, w(MgO)=6.5%,1500 ℃)

    Figure  6.  CaF2–Na2O–Al2O3–CaO–SiO2–MgO iso-viscosity diagram (M=0.9, w(MgO)=6.5%, 1500 °C)

    表  1  含氟保护渣成分范围(质量分数)

    Table  1.   Composition of fluorine-containing mold flux %

    CaF2MNa2OAl2O3MgO
    4–200.6–1.23–122–120–12
    下载: 导出CSV

    表  2  连铸保护渣组成(质量分数)

    Table  2.   Components of mold fluxes for continuous casting %

    SlagCaOSiO2Al2O3CaF2Na2OMgOMSlagCaOSiO2Al2O3CaF2Na2OMgOM
    C124.622.311.21911.711.21.1C2433.737.47.212.43.16.20.9
    C234.030.910.517.84.72.11.1C2527.630.77.6138.1130.9
    C335.132.011.27.811.72.21.1C2633.837.57.6138.100.9
    C435.131.910.57.34.710.51.1C2730.734.17.6138.16.50.9
    C532.829.84.51911.72.21.1M123.438.36.212.918.80.50.6
    C632.929.94.217.84.710.51.1M217.540.05.214.521.51.30.4
    C733.930.94.57.811.711.21.1M320.134.44.814.326.400.6
    C842.838.94.27.34.72.11.1M419.436.618.017.28.800.5
    C923.032.911.21911.72.20.7M532.631.25.38.022.901.0
    C1023.333.210.517.84.710.50.7M622.542.210.410.713.01.30.5
    C1123.934.211.27.811.711.20.7M721.533.23.715.425.70.50.6
    C1231.044.410.57.34.72.10.7M822.738.66.313.518.900.6
    C1322.131.54.51911.711.20.7M922.335.08.916.517.300.6
    C1429.341.94.217.84.72.10.7M1020.434.04.317.923.400.6
    C1530.443.44.57.811.72.20.7M1113.832.03.520.227.13.50.4
    C1630.243.14.27.34.710.50.7P139390138.41.61.0
    C1735.329.57.6138.16.51.2P239390133.66.41.0
    C1824.340.57.6138.16.50.6P341410133.61.61.0
    C1928.131.313138.16.50.9P43939078.46.41.0
    C2033.336.92.2138.16.50.9P54242078.41.61.0
    C2126.629.67.621.68.16.50.9P64242073.66.41.0
    C2234.838.77.64.38.16.50.9P74444073.61.61.0
    C2327.530.58.013.613.66.80.9P830420138.46.40.7
    P93448133.61.60.7S133.553.013.50.6
    P10344115640.85S232.947.819.30.7
    P113541101040.85S333.146.920.00.7
    P12394510600.85S430.837.831.40.8
    P13354110680.85S527.030.442.60.9
    P14374310640.85S633.039.627.40.8
    P15423810641.1S733.238.628.20.9
    下载: 导出CSV

    表  3  黏度参数分析

    Table  3.   Viscosity controlling parameters

    SlaglnABSlaglnABSlaglnAB
    C1−12.116616750.76C10−11.166315523.76C19−11.641916899.20
    C2−11.152115331.25C11−11.406916399.51C20−10.573614696.67
    C3−11.482716323.80C12−11.904519019.28C21−9.2606311473.14
    C4−11.233816106.31C13−10.711413670.59C22−11.338818048.45
    C5−10.966613904.19C14−11.189615932.56C23−10.481413697.65
    C6−11.180614859.89C15−11.439117000.89C24−17.236225991.79
    C7−11.352215328.48C16−11.131216491.46C25−10.581214320.87
    C8−11.363516421.96C17−14.961021103.44C26−13.068218316.60
    C9−10.999214722.03C18−12.897219711.71C27−10.782813602.93
    下载: 导出CSV
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  • 收稿日期:  2020-05-03
  • 网络出版日期:  2021-03-15
  • 刊出日期:  2021-03-31

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