The purpose of this paper is to develop a prediction model of WGCLSM （waste LCD （liquid crystal display） glass controlled low strength materials） concrete, the relationship between UPV （ultrasonic pulse velocity...The purpose of this paper is to develop a prediction model of WGCLSM （waste LCD （liquid crystal display） glass controlled low strength materials） concrete, the relationship between UPV （ultrasonic pulse velocity） and compressive strength, UPV-strength model. The power function was used to perform the nonlinear-multivariate regression analysis of UPV with water-binder ratio （w/b）, curing age （t） and waste glass content （G） in our previous study. Test results show that the compressive strength increases with UPV and approach to a linear relationship. Thus, the UPV-strength model was established by linear-multivariate regression analysis and the compressive strength evaluated by ultrasonic pulse velocity. The calculated results are in accordance with the laboratory measured data ultrasonic pulse velocity and compressive strength. In addition, the statistical analysis shows that the coefficient of determination R2 and the MAPE （mean absolute percentage error） were from 0.916 to 0.951 and 12.6% to 15.1% for the compressive strength, respectively. The proposed models are highly accurate in predicting the compressive and ultrasonic pulse velocity of WGCLSM concrete. However, with other ranges of mixture parameters, the predicted models must be further studied.展开更多
文摘The purpose of this paper is to develop a prediction model of WGCLSM （waste LCD （liquid crystal display） glass controlled low strength materials） concrete, the relationship between UPV （ultrasonic pulse velocity） and compressive strength, UPV-strength model. The power function was used to perform the nonlinear-multivariate regression analysis of UPV with water-binder ratio （w/b）, curing age （t） and waste glass content （G） in our previous study. Test results show that the compressive strength increases with UPV and approach to a linear relationship. Thus, the UPV-strength model was established by linear-multivariate regression analysis and the compressive strength evaluated by ultrasonic pulse velocity. The calculated results are in accordance with the laboratory measured data ultrasonic pulse velocity and compressive strength. In addition, the statistical analysis shows that the coefficient of determination R2 and the MAPE （mean absolute percentage error） were from 0.916 to 0.951 and 12.6% to 15.1% for the compressive strength, respectively. The proposed models are highly accurate in predicting the compressive and ultrasonic pulse velocity of WGCLSM concrete. However, with other ranges of mixture parameters, the predicted models must be further studied.
