New mathematical models for predicting the lifetime of EPDM insulators: Effect of elongation at break on the kinetic degradation of EPDM insulators subjected to thermo-oxidation

Ethylene propylene diene monomer (EPDM) is an important polymer extensively exploited in plasturgy. However, relatively few studies have been carried out to predict the lifetime of EPDM in different climatic conditions particularly, thermo-oxidation. Based on this realization, the aim of the present work was to develop mathematical models for predicting the lifetime of EPDM elastomers, used for insulation of electric cables. The kinetic degradation of EPDM insulators, by monitoring change in a physical property (elongation at break test “ℇr”), was studied by following its thermo-oxidative aging (70, 90, 110 and 130 ° C in air circulating oven). The multiple linear regression analysis (MLRA), solved by the Cholesky method, was the mathematical approach developed in the modeling of the kinetic degradation. In this study, we used two insulators materials when the first insulator contained an amorphous EPDM and the second contained a semi-crystalline EPDM. The results showed that the polynomial models developed to predict elongation at break were reliable for both insulators under thermo-oxidation. The half-life times predicted by the mathematical models was found to be statistically significant (p< 0.05). In conclusion, the mathematical models developed in our study could be used confidently to predict the lifetime of EPDM elastomers

Kinetyczna degradacja folii LDPE poddanych działaniu agresywnych środowisk

The effect of natural and thermo-oxidative aging on the structure and physicochemical properties of LDPE films stabilized with hindered amine light stabilizers (HALS) was investigated. Based on multiple linear regression analysis (MLRA) mathematical models to predict the lifetime of the LDPE were developed. Four statistical criteria were used to evaluate the developed models: residual variance, coefficient of determination, Student’s test and the Fisher-Snedecor test. The half-life times predicted by the mathematical models were found to be statistically significant (p < 0.05).Zbadano wpływ starzenia w warunkach naturalnych i starzenia termooksydacyjnego na strukturę i właściwości fizykochemiczne folii LDPE stabilizowanych aminowymi fotostabilizatorami z zawadą przestrzenną (HALS). W oparciu o wielokrotną analizę regresji liniowej (MLRA) opracowano modele matematyczne do przewidywania czasu życia folii LDPE. Do oceny opracowanych modeli stosowano cztery kryteria statystyczne: wariancję szczątkową, współczynnik determinacji, test Studenta i test Fishera-Snedecora. Stwierdzono, że okresy półtrwania przewidywane przez modele matematyczne są istotne statystycznie (p < 0,05)

Modeling of the soybean oil bleaching and optimization of its conditions in the refining process for environmental interest

In this work, we propose mathematical models describing the soybean oil bleaching process as a function of its parameters (temperature: 80 – 120 °C, clay dosage: 0.25 – 2 %, contact time: 10 – 30 min). The crude soybean oil visible spectrum shows three values of maximum wavelength (λmax). A value at 426 nm corresponding to the chlorophyll-a, the values at 451 and at 479 nm were assigned to β-carotene pigment. The models were developed using multiple linear regression analysis (MLRA) and were performed with Matlab programming language. The input variables are the temperature (X1), the clay dosage (X2) and the contact time (X3). The output parameter is the bleaching capacity (Y in % uptake). Statistical analysis methods were used to analyze and to confirm the reliability of the selected models. The optimal bleaching conditions for the soybean oil were: temperature 100 °C; clay dosage 2 % w/w and contact time 30 min. The highest bleaching capacity was found to be 81.04 % at 426 nm, 90.60 % at 451 nm and 93.66 % at 479 nm. The developed models allowed predicting the bleaching capacity representing the removal of the β-carotene and chlorophyll-a pigments present in the crude soybean oil at each λmax. Also they allowed a better control of the most influencing parameters on the bleaching step and contribute to the optimization of the spent bleaching clay rejects by optimizing the amount of bleaching clay used in the refining process; consequently, to reduce risks of pollution