| dc.description.abstract | This study is the next step of ongoing research at University of South-eastern Norway (USN) to enable multivariate analysis for industrial scale capture process.
This study has been done in collaboration with Technology Centre Mongstad (TCM) as one of the largest post-combustion capture test centers in the world. In 2015 and 2017, TCM operated two comprehensive test campaigns using the benchmark aqueous 30 wt% Monoethanolamine (MEA) solvent.
Through collaboration with TCM, USN has been provided with the laboratory test results of the collected samples and analytical data including Fourier Transform Infrared (FTIR) spectra from these two campaigns.
The received FTIR spectra as a multivariate data source contains the plenty of important chemical information of the samples. To extract these information, partial least square regression (PLSR) method has been used in this study.
The PLSR models of Total Inorganic Carbon (TIC) and Total Alkalinity (Tot-Alk) which have been prepared by using FTIR spectra from these campaigns are presented. From this study, it is evident that online monitoring integrated with spectroscopic analysis is an appropriate method for CO2 capture plant online monitoring. Through this, it is possible to reduce the time consuming and expensive conventional laboratory analyses of samples from CO2 capture plants.
Finally, the predictability of PLSR models for preparation of two campaigns was is tested and error of predictions were studied. | |
