**4. Results and discussion**

8 Multivariate Analysis in Management, Engineering and the Sciences

**Figure 2.** CFR engine for MON octane (WAUKESHA, 2012)

done in similar engines to those used for testing in MON octane.

index (I), defined by Equation 1:

The octane number of a gasoline is an important characteristic which is related to their ability to burn in spark-ignition engines. It is determined by comparing its tendency to detonate with the reference fuel with octane known under standard operating conditions.

When it comes to defining the octane required by engines, many countries use anti-knock

MON + RON I =

where MON is the Motor Octane Number and RON is the Research Octane Number. The method MON measures the resistance to detonation when gasoline is being burned in the most demanding operating conditions and at higher rotations. The test is done in motors CFR (Cooperative Fuel Research), single-cylinder with variable compression ratio equipped

The RON method evaluates the resistance of the gasoline to detonation under milder conditions and work in less rotation than that measured by octane number MON. The test is

It takes two hours and half to run the test MON and it is spent the same time for the test RON.

with the necessary instrumentation in a stationary base, as shown in Figure 2.

2 (1)

Samples of gasoline, diesel and jet fuel, collected during 1 year, were subjected to laboratory tests, to determine the input variables, Xi, which are the infrared radiation absorbed, and the response variables, Yi, that are physicochemical properties. The physicochemical properties will be predicted by PLS models.

The Table 1 summarizes the validation results of each model for products gasoline, diesel and jet fuel, where RMSEP (Root Mean Square Error of Prediction) corresponds to the standard deviation of the residuals (differences between measured and predicted values by the model).

The Figures 3-6 illustrate that the residues of models follow normal distribution, since in all cases the p-value was greater than 0.05.


**Table 1.** Summary of results of modeling and validation.

**Figure 3.** Normality Test for the property MON

Contributions of Multivariate Statistics in Oil and Gas Industry 11

Mean -5,32907E-17 StDev 1 N 25 AD 0,371 P-Value 0,395

**Figure 6.** Normality Test for the property viscosity (jet fuel)

products gasoline, diesel and jet fuel.

The following conclusions can be drawn from the results of this study:


**Standardize Residuals**

property along with the computational time does not exceed three minutes.

predictions have precision equivalent to the reference methods.

Ana Paula Barbosa Rodrigues de Freitas and Messias Borges Silva

It was possible to model mathematically the properties octane number and viscosity of the

**Viscosity (Jet Fuel)** Normal

The developed models were externally validated according to ASTM D-6122 and their

The results were used in an oil refinery and contributed immensely to speed up the decision-making in blendings systems. Unlike the laboratory trials, the response time of a

**5. Conclusions** 

1

99

**Percent**

**Author details** 

Leandro Valim de Freitas

*Petróleo Brasileiro SA (PETROBRAS), Brazil São Paulo State University (UNESP), Brazil* 

*São Paulo State University (UNESP), Brazil University of São Paulo (USP), Brazil*

**Figure 4.** Normality Test for the property RON

**Figure 5.** Normality Test for the property viscosity (diesel)

**Figure 6.** Normality Test for the property viscosity (jet fuel)
