To improve energy efficiency and to recover energy, various mathematical models, such as pinch analysis, entropy analysis, exergy analysis, and entransy analysis, have been established to analyze heat transfer networks. In this study, these methods were applied to analyze the energy-saving effect of the epichlorohydrin unit in a certain enterprise. The results showed that when the minimum heat transfer temperature difference (ΔTmin) was 10K, 15K, and 20K, the efficiencies of the second law of thermodynamics calculated by entropy analysis were 88.02%, 93.52%, and 99.49%, respectively. The analytical method calculated an efficiency of 61.01%, 59.28%, and 57.27%, respectively, with public works’ savings of 16.59%, 14.86%, and 12.02%. The pinch analysis method achieved public works’ savings of 22.80%, 21.50%, and 19.35%. The entransy analysis method calculated an entransy transfer efficiency of 42.81%, 42.13%, and 41.00%, respectively, with public works’ savings of 19.41%, 18.01%, and 15.70%. Based on the results, entropy analysis was found to be contrary to the principle of minimum entropy production. Exergy analysis was not able to establish a heat transfer network. The pinch analysis method was not suitable for determining the thermal efficiency of a heat transfer network as the criterion for evaluating energy saving. On the other hand, the entransy analysis method was able to establish a heat transfer network and evaluate the heat utilization of the network by entransy transfer efficiency. Overall, the data analysis was reasonable.
A new Group Contribution Method based on elements and chemical bonds was proposed to predict the enthalpy of evaporation of organic compounds at their normal boiling points. A prediction model was built using 1266 experimental data points, and the accuracy of the model estimations was evaluated using 16 experimental data points. The new method has only 42 groups, a simple way of group splitting, and a wide range of predictions with an average relative error of 5.84%. Furthermore, the inclusion of silicon elements and their chemical bonds in the group library enables the effective prediction of silicon-containing compounds with an average relative error of 2.71%. By analyzing and comparing the other three commonly used methods, it can be concluded that the new method provides accurate and reliable estimation results and has a more comprehensive application range.
A new element- and chemical bond-dependent GE-EoS model(SRK-UNICAC) is proposed to consider the deviation of the vapor and liquid phases from the ideal state. The SRK-UNICAC model combines the UNICAC model and the SRK cubic equation of state. It uses the original interaction parameters of the UNICAC model and uses this model to calculate the GE. The SRK-UNICAC model predicted vapor-liquid equilibria for 87 binary systems under low- and medium-pressure conditions, 12 binary systems under high-pressure conditions, and 14 ternary systems; a comparison of the predictions with five other activity coefficient models were also made. The new model predicted the vapor-phase fraction and bubble-point pressure, and temperature for the binary system at high pressure, with a mean relative error of 3.75% and 6.58%, respectively. The mean relative errors of vapor-phase fraction and bubble-point temperature or bubble-point pressure for ternary vapor–liquid phase equilibrium were 6.50%, 4.76%, and 2.25%. The SRK-UNICAC model is more accurate in predicting the vapor–liquid phase equilibrium of high-pressure, non-polar, and polar mixtures and has a simpler and wider range of prediction processes. It can therefore be applied to the prediction of vapor–liquid equilibrium.
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