Prediction of the physico-chemical properties of vegetable oils using optimal non-linear polynomials

ALVISO, DARIO; AGUERRE, HORACIO; NIGRO, NORBERTO; ARTANA, GUILLERMO

FUEL

ELSEVIER SCI LTD

Año: 2023 vol. 350

0016-2361

Vegetable oils (VOs) comprise 90%–98% triglycerides (three fatty acids esters and glycerol), with trace amountsof mono-glycerides and di-glycerides. The content of glycerides in VOs can vary depending on the specifictype of oil, the processing methods used, and other factors such as the cultivar and harvest date. VOs havebeen examined for usage in different applications due to their physicochemical properties, including stationaryengines, big ships, and Diesel engines of low and medium speed. There are around 350 VOs that have thepotential to be used as fuel sources, the vast majority of which have yet to have their physicochemicalproperties investigated. Regression models based purely on VOs fatty acid content are beneficial in this context.This study conducts a regression analysis of VOs density (DE), kinematic viscosity (KV), flash point (FP),and low and high heating values (LHV and HHV) as a function of their fatty acids. Several experimentaldatabases were selected, including the values of VOs fatty acid composition and physico-chemical properties.Optimal non-linear polynomials were chosen for the regression procedure. Scheffé polynomials offer differentfitting alternatives to adjust the VOs experimental databases using their five main fatty acids: from simplelinear polynomials (including five terms) to full cubic polynomials (including 35 terms). The polynomials arevalidated by showing how well their results correspond with the experimental databases. The standard errorvalues for the proposed full polynomials concerning the databases for DE, KV, FP, LHV, and HHV are 0.70%,7.79%, 7.86%, 1.66%, and 0.19%, respectively.