ABSTRACT

A dynamic one-dimensional mathematical model was developed for predicting the thermal state of a steelmaking ladle. The model is intended to be used in process control applications, in which fast computational times are desirable alongside model accuracy. The calculation domain was discretized using the finite difference method, and time integration was performed using both the implicit Euler and Crank–Nicolson methods, the performances of which were compared. The model was implemented in Python programming language and validated using data from our own measurements and other studies available in the literature. The results indicate that the model can reproduce the measured temperature evolution of the ladles within 5°C at best. The worst performance was observed during cooling, where the model underestimates the temperature at the innermost measurement point by up to 200°C. With computation times of around 16–23 s for one hour of simulation, the model is computationally sufficiently fast for online applications.

摘要

开发了动态一维数学模型来预测炼钢钢包的热状态。该模型旨在用于过程控制应用，其中需要快速的计算时间和模型的准确性。采用有限差分法对计算域进行离散化，并采用隐式欧拉法和Crank-Nicolson法进行时间积分，并比较了两种方法的性能。该模型是用 Python 编程语言实现的，并使用我们自己的测量数据和文献中的其他研究数据进行验证。结果表明，该模型最多可以再现测量的钢包温度变化在 5°C 范围内。在冷却过程中观察到最差的性能，其中模型将最内部测量点的温度低估了 200°C。一小时的模拟计算时间约为 16-23 秒，该模型的计算速度足以满足在线应用程序的需要。