煤的灰熔融特性和黏温特性是气流床(EFB)气化炉能否顺利排渣的2个关键指标。EFB气化炉内的化学反应处于高温高压湍流多相反应的苛刻条件下,通过试验获取熔渣流动行为参数困难大,建立能够预测该参数的模型至关重要。在分析煤的灰熔融特性参数(灰熔融温度、全液相温度)、黏温特性参数(黏度、临界黏度温度)及影响参数因素的基础上,阐述了回归分析法、软件预测法(FactSage、LAMMPS)、数学建模法(反向传播神经网络、支持向量机)和离子势预测法4种预测方法的原理及步骤,对灰熔融特性参数和黏温特性参数构建预测模型进行了系统综述,最后归纳了4种预测煤灰流动行为方法的优缺点及应用范围。基于煤灰成分及其微观结构,结合热力学和动力学模拟软件,采用数学模型优化流动性参数,从而建立最优预测公式,对指导EFB气化过程中熔渣流动行为的准确预测具有重要意义。

The ash fusion characteristics and viscosity-temperature characteristics of coal are the two indexes parameters for the dischargeof the molten slag in the entrained flow bed (EFB). The chemical reaction in EFB gasifier is under harsh conditions of high temperature,high pressure, and turbulent with multiple phase reactions, and it is difficult to obtain the molten slag fluidity behavior parameters by experience, and establishing a model that predicts these parameters is of vital importance. Based on the analysis of ash melting characteristicparameters (ash melting temperature, full liquid phase temperature), viscosity temperature characteristic parameters (viscosity, criticalviscosity temperature) and influencing parameter factors, the prediction principles and steps of four methods: regression analysis, softwareprediction (FactSage, LAMMPS), mathematical modeling (backpropagation neural network, support vector machine) and ion potentialprediction method were expounded, and the prediction model for the construction of ash fusion characteristic parameters and viscosity-temperature characteristic parameters was systematically reviewed. Finally, the advantages, disadvantages and application scope of thefour methods for predicting coal ash flow behavior were summarized. Based on the composition of coal ash and its microstructure,combinedwith thermodynamic and kinetic simulation software, the mathematical model was used to optimize a the flow parameters. So as to establishthe optimal prediction formula, which is of great significance to guide the accurate prediction of molten slag fluidity behavior in theEFB gasification process.

0 引言

1 熔渣流动行为参数

   1.1 熔融特性参数

   1.2 黏温特性参数

2 预测模型方法

   2.1 回归分析法

   2.2 软件预测法

   2.3 数学建模法（优化）

   2.4 离子势预测模型

3 熔渣流动行为参数的预测模型

   3.1 预测熔渣熔融特性参数的模型

   3.2 预测熔渣黏温特性参数的模型

4 4种预测方法优、缺点及应用范围

5 总结与展望