Publication Date:
2016-08-26
Description:
Specification of CO 2 and brine phase behaviour plays a vital role in CO 2 sequestration and CO 2 reduction from atmosphere to deep saline aquifers. Because CO 2 solubility in brines determine how much carbon can be stored in deep saline aquifers. To tackle the referred issue, high precise model with low uncertainty parameters called ‘least square support vector machine (LS-SVM)’ was executed to predict CO 2 –brine solubility. The proposed intelligent-based approach is examined by using extensive experimental data reported in open literature. Results obtained from the proposed numerical solution model were compared with the relevant experimental CO 2 –brine solubility data. The average relative absolute deviation between the model predictions and the relevant experimental data was found to be 〈0.1% for LS-SVM model.
Keywords:
Hydrogen generation, storage and carbon capture
Print ISSN:
1748-1317
Electronic ISSN:
1748-1325
Topics:
Energy, Environment Protection, Nuclear Power Engineering
,
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Permalink
