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Prediction of vapor-liquid equilibrium for binary systems containing HFEs by using artificial neural network

机译：用人工神经网络预测含HFEs的二元系统的气液平衡

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A method using artificial neural network (ANN) was applied to estimate the vapor-liquid equilibrium (VLE) for the binary systems containing hydrofluoroethers (HFEs) and polar compounds. Our new estimation method is composed of three steps. In the first step, the sign of logarithm of activity coefficient (gamma) is estimated for each binary system using ANN, because it had been found that the binary systems containing HFEs show different thermodynamic behaviors depending on the sign for ln(gamma). In the second step, two sets of relation between liquid mole fraction and ln(gamma) are constructed: one held for the case of positive sign and the other held for that of negative sign. In the third step. vapor-liquid composition and equilibrium temperature are calculated using the estimated activity coefficient. In order to construct this new method, the isobaric VLE data of 18 binary systems including HFEs was used. As a result, our new method could estimate VLE with reasonable accuracy. (C) 2002 Elsevier Science B.V. All rights reserved. [References: 26]
机译：应用一种使用人工神经网络（ANN）的方法来估算包含氢氟醚（HFE）和极性化合物的二元系统的气液平衡（VLE）。我们的新估算方法包括三个步骤。第一步，使用ANN为每个二元系统估计活度系数（γ）的对数符号，因为已经发现，包含HFE的二元系统根据ln（γ）的符号表现出不同的热力学行为。在第二步中，构造了液体摩尔分数与ln（γ）之间的两组关系：一组用于正号，另一组用于负号。在第三步。使用估算的活度系数计算气液组成和平衡温度。为了构建这种新方法，使用了包括HFE在内的18个二元系统的等压VLE数据。结果，我们的新方法可以合理地估计VLE。 （C）2002 Elsevier Science B.V.保留所有权利。 [参考：26]

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