Gibbs-Duhem方程与前传网的集成方法及其在汽液相平衡中的应用

提出了以Gibbs-Duhem方程为基架，引入前传网，由此将机理方程与神经网络这两种不同类的方法相集成，用以求解化工热力学的汽液相平衡问题，以克服经典的机理方法或单一神经元方法的欠缺与不足。将这种集成方法应用于恒温、恒压二元体系，由液相组成确定汽相组成，效果良好。应用实例表明该法计算简便，预测精度高，且稳定性好，显示出胜于两种单一方法的优越性。

Integration of Gibbs-Duhem Equation and its Application in Liquid-Vapor Equilibrium

A hybrid model (GD-FFN) that combines Gibbs-Duhem equation (GD) and artificial neural networks (FFN) for vapor liquid equilibrium (VLE) calculation was presented. In which a simple expression for vapor composition was deduced and FFN was included in the expression to compensate inaccuracy of first principles. The model's predictions are restricted by GD, the deficiency, i.e. VLE calculation using pure FFN is independent on thermodynamics mechanism, is avoided. So the model has better universality and stability. Otherwise the model has simpler form and easier computation compared with traditional UNIQUAC method. The vapor compositions of the selected isobaric (isothermal) VLE binary systems were predicted by using GD-FFN. The results indicate the GD-FFN model can produce more accurate and consistent predictions, and can provide more reliable extrapolation than pure FFN or UNIQUAC method.