Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10272197 | Fuel | 2014 | 4 Pages |
Abstract
This study evaluated the use of partial-least-squares (PLS) regression models to quantify soybean biodiesels in diesel blends. The study was carried out by taking into account the entire mid-infrared spectral range and according to the ASTM E1655 standard. The PLS models provided low root-mean-squared errors of prediction (RMSEP) of 0.0792% (v/v) and 0.1050% (v/v) for the models containing methyl and ethyl soybean biodiesels, respectively. In addition, an excellent correlation was observed in the prediction set (RÂ =Â 0.9999), and no systematic errors were present according to the ASTM E1655 standard. When the models were compared against the requirements of the ABNT NBR 15568 standard, both models exhibited adequate accuracy both the concentration ranges from 0% to 8% and 8 to 30% (v/v). Therefore, the proposed models for the entire spectral region allow the determination of both methyl and ethyl soybean biodiesels in diesel using only the concentration range between 1.00% and 30.00% (v/v).
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Chemical Engineering (General)
Authors
Lucas Caixeta Gontijo, Eloiza Guimarães, Hery Mitsutake, Felipe Bachion de Santana, Douglas Queiroz Santos, Waldomiro Borges Neto,