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• W2762854402 abstract "The heat generated from dark color asphalt, which is low in surface reflectance mainly contributes to the environmental problem called as urban heat island. Low reflectance at high energy wavelength of sunlight, such as visible light and infrared region will cause the pavement to have high surface temperature, due to high energy absorption from solar radiation. This paper presents the optimization result of cool pavement coating material based on selected tiles aggregate to achieve high near infrared region (NIR) reflectance. Three types of waste tiles were used in this study which are Full Body Porcelain (FBP), Monoporosa (MP) and Porcelain Glaze (PG). All the tiles were prepared in the form of aggregates. A linear model was formed as a function of mix tiles fraction and the analysis of ANOVA suggest that the linear term used for this model is significant. Diagnostics of the model was evaluated using box-cox plot, normal plot of residuals and optimized to predict the mix of the different type of tiles to produce the highest surface NIR reflectance value. The first solution suggests that 100% of MP tile can provide NIR reflectance of 0.53, whereas the second solution suggest that the combination of 50% FBP and 50% of MP tile aggregates could give NIR reflectance value of about 0.51. Experimental work on measuring surface temperature found that optimized samples, M1 and M2 with high NIR reflectance could significantly reduce surface temperature of asphalt pavement at range of 4.1 °C–9.6 °C. In conclusion, the results of optimization is reliable and this method able to provide significant information on optimizing mix of tiles material as to achieve high NIR reflectance value for coating materials of cool-pavement." @default.
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• W2762854402 date "2018-01-01" @default.
• W2762854402 modified "2023-09-29" @default.
• W2762854402 title "Optimizing of near infrared region reflectance of mix-waste tile aggregate as coating material for cool pavement with surface temperature measurement" @default.
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• W2762854402 doi "https://doi.org/10.1016/j.enbuild.2017.10.001" @default.
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