Novel approaches for the prediction of density of glycol solutions |
| |
Authors: | A Bahadori Y Hajizadeh H B Vuthaluru M O Tade S Mokhatab |
| |
Institution: | [1]Department of Chemical Engineering, Curtin University of Technolog3; GPO Box U1987, Perth, WA 6845, Australia [2]Institute of Petroleum Engineering, Heriot-Watt University, Edinburgh, UK [3]Department of Chemical Engineering, Curtin University of Technology, GPO Box U1987. Perth, WA 6845. Australia [4]Process Technology Department, Tehran Raymand Consulting Engineers, Tehran, Iran |
| |
Abstract: | Two new approaches for the accurate prediction of densities of the commonly used glycol solutions in the gas processing industry are presented in the article.The frst approach is based on developing a simple-to-use polynomial corre lation for an appropriate prediction of density of glycol solutions as a function of temperature and weight percent of glycols in water,where the obtained results show very good agreement with the reported experimental data.The second approach,however.is based on the artificial neural networks(ANN)methodology,wherein the results demonstrate the ability of the in troduced method to predict reasonably accurate densities of glycols under operating conditions.Comparisons of the two novel approaches indicated that the simple-to-use correlation appears to be superior owing to its simplicity and clear numerical back ground,wherein the relevant coefficients can be retuned if new and more accurate data are available in the future.The average deviation of the new proposed polynomial correlation results from reported data iS 0.64 kg/m3 whereas the average deviation of artificial neural networks (ANN)methodology from reported data iS 1.1 kg/m3. |
| |
Keywords: | glycols density polynomial correlation artificial neural networks gas processing |
本文献已被 维普 万方数据 等数据库收录! |
| 点击此处可从《天然气化学杂志》浏览原始摘要信息 |
| 点击此处可从《天然气化学杂志》下载免费的PDF全文 |
|