The accurate online determination of the solidification of continuously cast strands is the primary condition for the effective implementation of solidification end reduction (SER) and electromagnetic stirring (MES). Thermal tracking calculations based on the finite difference method (FDM) or finite volume method (FVM) are the most popular methods for monitoring the strand solidification process. In the traditional models, the thermophysical properties of steel are determined from only temperature dependence; the calculations do not consider the effects of uneven solute distribution on the casting strand. In this study, a real-time carbon distribution-dependent thermal tracking model (CDD-TTM) was developed. The model could online calculate the solidus temperature, liquidus temperature, heat conductivity, density, and enthalpy according to the carbon segregation of continuous casting strand both on the longitude and cross-sections. Furthermore, the feedback effect of SER was considered also, which extended the contact length between rollers and slab and reduced the thickness of the strand. The calculation results were verified by infrared temperature measuring experiment, and the maximum relative error of surface temperature is 2.11 pct. Industrial application results show that the internal quality of the strand is significantly improved using the SER and EMS processes designed based on the solidification prediction results of the model.

连铸坯凝固状态的准确在线测定是有效实施凝固端部还原（SER）和电磁搅拌（MES）的首要条件。基于有限差分法 (FDM) 或有限体积法 (FVM) 的热跟踪计算是监测铸流凝固过程的最流行的方法。在传统模型中，钢的热物理性能仅由温度依赖性决定；计算没有考虑溶质分布不均匀对铸坯的影响。在这项研究中，开发了一种实时碳分布相关的热跟踪模型（CDD-TTM）。该模型可以在线计算固相线温度、液相线温度、导热系数、密度、和根据连铸坯在纵向和横截面上的碳偏析的焓。此外，还考虑了SER的反馈效应，延长了辊子与板坯的接触长度，减小了铸坯的厚度。通过红外测温实验验证了计算结果，表面温度最大相对误差为2.11%。工业应用结果表明，采用基于模型凝固预测结果设计的SER和EMS工艺，显着提高了铸坯的内部质量。延长了辊子和板坯之间的接触长度并减少了铸坯的厚度。通过红外测温实验验证了计算结果，表面温度最大相对误差为2.11%。工业应用结果表明，采用基于模型凝固预测结果设计的SER和EMS工艺，显着提高了铸坯的内部质量。延长了辊子和板坯之间的接触长度并减少了铸坯的厚度。通过红外测温实验验证了计算结果，表面温度最大相对误差为2.11%。工业应用结果表明，采用基于模型凝固预测结果设计的SER和EMS工艺，显着提高了铸坯的内部质量。