Outlier and Normality Testing of the Residuals from the Carreau-Yasuda Model in Fitting the Rheological Behavior of the Non-Newtonian fluid TF2N

Abstract

Non-Newtonian fluids include a variety of regularly encountered substances such as custard, honey, toothpaste, starch suspensions (including starch from corn starch), paint, blood, melted butter, and hairspray. For decades, scientists have investigated non-Newtonian fluid behavior and produced models to aid in the characterization of non-Newtonian fluid behavior. In addition to data interpolation and extrapolation, the outputs of these models may be utilized for material classification based on model parameters and aid with the simulation of computational fluid dynamics. The Carreau-Yasuda model fitted to the rheological behavior of the non-Newtonian fluid1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide ([emim][TF2N]) was checked for its conformation to the normal distribution of its residual using the normality tests , which was found not to pass all of the test. After checking for the presence of an outlier using the Grubbs ‘test, no outlier was detected. The ROUT method was then applied to detect the presence of outliers and three outliers were found and removed. The normality checks performed on the cleaned residues gave acceptable results in terms of normality tests and visual conformation of the residual, Q-Q plot and overlaid normality curve to the histogram, indicating that the model is now appropriate for the data.

Test of the Randomness of Residuals and Detection of Potential Outliers for the Modified Gompertz Model Used in the Fitting of the Growth of Shigella flexneri

“…Both of these methodologies are usually referred to as the ESD-test [18] are recommended [31]. Of the two, the ROUT method, which combines robust regression and outlier removal is increasingly being employed in removal of multiple outliers [24,[32][33][34][35] The runs test found that there were 5 total runs, although the randomness assumption predicted 7.46 runs (Table 3). This implies that the residuals collection only includes runs that are marginally relevant.…”

Test of the Randomness of Residuals and Detection of Potential Outliers for the Morgan-Mercer-Flodin Used in the Fitting of the Prediction of Cumulative Death Cases in Nigeria Due to COVID-19

“…In cases when there are several outliers or the precise number of outliers cannot be determined, Rosner's generalised Extreme Studentized Deviate, often known as the ESD-test, or the ROUT technique [3] are recommended [17]. Of the two, the ROUT method, which combines robust regression and outlier removal is increasingly being employed in removal of multiple outliers [9,[18][19][20][21].…”

Test of the Randomness of Residuals and Detection of Potential Outliers for the Modified Logistics Used in the Fitting of the Growth Curve of Immobilized Pseudomonas putida on Phenol

“…Both of these methodologies are usually referred to as the ESDtest [18] are recommended [31]. Of the two, the ROUT method, which combines robust regression and outlier removal is increasingly being employed in removal of multiple outliers [24,[32][33][34][35] The runs test discovered that there were 8 total runs, but the assumption of randomness led to the prediction of 7 runs (Table 3). This suggests that the collection of residuals is appropriate.…”