Multiple regression model for prediction of vickers hardness and transition temperature of glass.

Autor: Shivam, Majumder, Arunava, Singh, Ramkishore, Sharma, Sahendra Pal, Danewalia, Satwinder Singh
Předmět:
Zdroj: AIP Conference Proceedings; 2024, Vol. 2986 Issue 1, p1-5, 5p
Abstrakt: The mechanical and thermal characteristics of the glasses are very crucial in order to select a glass for a particular application. In the present work, a mathematical model has been developed to predict the Vickers hardness (Hv) and glass transition temperature (Tg) of silicate glasses with alkali and alkaline earth oxides as network modifier. Single source data on glass properties has been used to understand their composition-property relationship. Multiple linear regression was employed to develop a model which takes selected composition of the glasses as input and gives an estimated value of Hv and Tg. Dependency of these properties of the glasses on the mol% of their constituent oxide has been explored. The formulated model was validated by obtaining the R2 value using the regression analysis between the calculated and the experimental values. Hv values of known compositions of glasses could be more reliably predicted and were close to the experimentally observed values. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index