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http://dx.doi.org/10.12989/cac.2017.19.4.419

Prediction models of compressive strength and UPV of recycled material cement mortar  

Wang, Chien-Chih (Department of Civil Engineering and Geomatics, Cheng Shiu University)
Wang, Her-Yung (Department of Civil Engineering, National Kaohsiung University of Applied Sciences)
Chang, Shu-Chuan (Department of Civil Engineering, National Kaohsiung University of Applied Sciences)
Publication Information
Computers and Concrete / v.19, no.4, 2017 , pp. 419-427 More about this Journal
Abstract
With the rising global environmental awareness on energy saving and carbon reduction, as well as the environmental transition and natural disasters resulted from the greenhouse effect, waste resources should be efficiently used to save environmental space and achieve environmental protection principle of "sustainable development and recycling". This study used recycled cement mortar and adopted the volumetric method for experimental design, which replaced cement (0%, 10%, 20%, 30%) with recycled materials (fly ash, slag, glass powder) to test compressive strength and ultrasonic pulse velocity (UPV). The hyperbolic function for nonlinear multivariate regression analysis was used to build prediction models, in order to study the effect of different recycled material addition levels (the function of $R_m$(F, S, G) was used and be a representative of the content of recycled materials, such as fly ash, slag and glass) on the compressive strength and UPV of cement mortar. The calculated results are in accordance with laboratory-measured data, which are the mortar compressive strength and UPV of various mix proportions. From the comparison between the prediction analysis values and test results, the coefficient of determination $R^2$ and MAPE (mean absolute percentage error) value of compressive strength are 0.970-0.988 and 5.57-8.84%, respectively. Furthermore, the $R^2$ and MAPE values for UPV are 0.960-0.987 and 1.52-1.74%, respectively. All of the $R^2$ and MAPE values are closely to 1.0 and less than 10%, respectively. Thus, the prediction models established in this study have excellent predictive ability of compressive strength and UPV for recycled materials applied in cement mortar.
Keywords
compressive strength; ultrasonic pulse velocity; prediction model; recycled materials; cement mortar;
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