A NEW MIXING RULE CONTAINING EXCESS GIBBS ENERGY MODEL FOR CUBIC EQUATIONS OF STATE

Bian Baigui; Wang Yanru and Shi Jun(Nanjing Institute of Chemical Technology; Nanjing 210009)

您当前的位置：

首页 >

文章列表页 >

A NEW MIXING RULE CONTAINING EXCESS GIBBS ENERGY MODEL FOR CUBIC EQUATIONS OF STATE

更新时间：2025-12-16

- A NEW MIXING RULE CONTAINING EXCESS GIBBS ENERGY MODEL FOR CUBIC EQUATIONS OF STATE
- CIESC Journal Issue 3, (1993)
- 作者机构：
  
  南京化工学院化工系,南京化工学院化工系,南京化工学院化工系南京210009,南京210009,南京,210009
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Online First：25 June 1993，
  
  Published：25 June 1993
- 稿件说明：
移动端阅览
Bian Baigui, Wang Yanru and Shi Jun(Nanjing Institute of Chemical Technology, Nanjing 210009). A NEW MIXING RULE CONTAINING EXCESS GIBBS ENERGY MODEL FOR CUBIC EQUATIONS OF STATE[J]. CIESC Journal, 1993, (3).
DOI：

Bian Baigui, Wang Yanru and Shi Jun(Nanjing Institute of Chemical Technology, Nanjing 210009). A NEW MIXING RULE CONTAINING EXCESS GIBBS ENERGY MODEL FOR CUBIC EQUATIONS OF STATE[J]. CIESC Journal, 1993, (3). DOI：

摘要

提出了在参考压力下将过量自由焓(g~E)模型引入状态方程的修正Huron-Vidal混合规则

由g~E模型确定状态方程中混合物的参数

以SRK方程和Wilson模型为例

取大气压为参考压力

计算了16个体系50组汽液平衡

结果表明本文建议的混合规则可直接使用现有文献报道的常压g~E模型参数由立方型状态方程预测常压汽液平衡

并对直接外推预测高压汽液平衡作了尝试.

Abstract

A modified Huron-Vidal mixing rule is presented by introducing excess Gibbs energy(gE) models into mixing rules for cubic equations of state at a reference pressure. The Soave-Redlich-Kwong equation of state and Wilson model is used as an example by taking atmospheric pressure as reference pressure. VLE data are predicted for 50 sets of 16 typical systems. Examples are also given for high pressure VLE prediction. The results show that the mixing rule enables direct incorporation of parameters of low pressure gE model for predicting low and high pressure VLE with cubic equations of state.

关键词

Keywords

references

Views

483

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Thermodynamic study of germanium-impurity competitive deposition in GeCl4-MxCly-H2 system

Study on the residence time distribution characteristics of the TPMS-Diamond static mixer

Exothermic characteristics of energy carrier for calcium looping thermo-chemical energy storage

Recent advances in machine learning for modeling and control of crystallization processes

Mechanism and regulation of supercooling behavior in imidazolium-based ionic liquids

Related Author

No data

Related Institution

No data

⁰