Experimental Data Extrapolation by using V order Logarithmic Polynomials

In this work, the authors consider the possibility to extrapolate experimental data on fuels specific heat at constant pressure, beyond the range of temperature investigated in the experimental measurements. With a proper extrapolation it is possible to avoid the necessary but empirical linear extrapolation, often used by CFD programs. Mathematical functions obtained from fitting experimental data are very useful when computational models on ICE are implemented. To obtain reliable results from these models, a great precision is required to the mathematical functions. In this work a new polynomial, used in order to fit experimental data on gases properties at low pressure, is presented. The new mathematical function presented has the functional form of a fifth order Logarithmic Polynomial, and it is evaluated through the least squares method, on the basis of experimental thermodynamic data found in literature. This new function presents three great advantage in respect to traditional polynomials used in literature: 1) it offers a great fitting precision (correlation factor R2 greater than 0.99); 2) it is able to cover wide range of temperature with a single polynomial; 3) it gives the possibility to extrapolate data beyond experimental temperature range.