Evaluation of different surfactants' performance in varying coal dust concentration through logistic regression analysis

Le résumé fourni par la source

Coal dust causes a range of diseases and health problems worldwide, such as Coal Workers’ Pneumoconiosis. Numbers of static studies showed that surfactants could increase the coal dust wettability effectively in water spraying. However, coal dust does not remain in a static state in underground mines. Therefore, studies should be conducted in a dynamic state where coal dust and surfactant droplets will get a shorter contact time. In this study, wind tunnel tests have been conducted to capture the dynamic process. Logistic regression modelling has been done to evaluate the suppression performance in terms of efficiency and quantity of dust suppressed with respect to three dependent variables: surfactant types, surfactant quantity, and coal dust concentration. The results showed that at low coal dust concentrations, the suppression efficiency is greater compared to high dust concentrations. Moreover, the surfactant quantity of 0.05 % to 0.20 % is more efficient than above. Although the surfactant type did not emerge as significant when low and high dust concentrations were combined, it becomes significant at low dust concentrations where SDS and CTAB are more efficient than SDBS and TX100. The results will help in selecting surfactants with the appropriate quantity in different coal dust concentrations.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.