| Titre : | Estimating Sulfur Content of Hydrog Sulfide at elevated temperatures and Pressures using an Atificial Neural Network Algorithm (2008) |
| Auteurs : | Amir H. Mohammadi, Auteur ; Dominique Richon, Auteur |
| Type de document : | Article : texte imprimé |
| Dans : | Industrial & engineering chemistry research (Vol. 47 n°21, Novembre 2008) |
| Article en page(s) : | p. 8499–8504 |
| Note générale : | chemical engineering |
| Langues : | Anglais |
| Résumé : | In this communication, we report an artificial neural network algorithm for estimating sulfur content of hydrogen sulfide at elevated temperatures and pressures. This model eliminates any need for characterization parameters, due to the tendency of sulfurs to react, required in thermodynamic models. To develop this algorithm, reliable experimental data reported in the literature on sulfur content of hydrogen sulfide are used. The developed model is then used to predict independent experimental data (not used in developing the model). It is shown that artificial neural network algorithm can be used as an efficient tool to estimate sulfur content of hydrogen sulfide. |
| En ligne : | http://pubs.acs.org/doi/abs/10.1021/ie8004463 |
