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Laser-Driven Calorimetry and Chemometric Quantification of Standard-Reference-Material Diesel/Biodiesel Fuel Blends



Werickson Fortunato de Carvalho Rocha, Cary Presser, Shannon Bernier, Ashot Nazarian, David A. Sheen


Multivariate calibration methods were evaluated using the measured thermal signatures of 11 diesel/biodiesel fuel blends (including 4 repeated runs for each fuel blend). Two National Institute of Standards and Technology standard-reference-material (SRM) pure fuels were blended by serial dilution to produce a range of blends for volumetric fractions between (0 to 100) %. The pure fuels were SRM 2770 (a diesel fuel oil with a nominal mass fraction of 40 mg kg-1 sulfur) and SRM 2772 (B100 soy-based biodiesel). The fuel blends were evaluated for the composition and total specific energy release (heating value), using a novel laser-driven calorimetry technique, referred to as the ‘laser-driven thermal reactor’. The experimental apparatus consists of a copper sphere-shaped reactor (mounted at the center of a chamber) that is heated by a high-power continuous wave Nd:YAG laser. Prior to heating by the laser, liquid sample is injected onto a copper pan substrate that rests near the center of the reactor and is in contact with a fine-wire thermocouple. A second thermocouple is in contact with the sphere- reactor inner surface. The change in temperature with time (‘thermogram’) is measured by the thermocouple and evaluated for the thermochemical characteristic of interest. Partial-least-squares (PLS) and support-vector-machine (SVM) models were constructed and evaluated for SRM-fuel-blend quantification and determination of fuel composition and heating value. Quantification of the fuel blend thermograms by the SVM method was found to better correlate the experiment results than PLS, based on the lower values obtained for the statistical errors; i.e., root-mean-square error of calibration (RMSEC) and root-mean-square error of prediction (RMSEP), as well as higher values obtained for the Pearson correlation coefficients (i.e., values greater than 0.94). The combination of laser-driven calorimetry and multivariate calibration methods has demonstrated potential applic


Chemometric analysis, chemometric quantification, diesel fuel blends, laser-driven calorimetry, multivariate calibration methods, standard reference materials
Created July 14, 2020, Updated July 23, 2020