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Aging Behavior of Bitumen Based on Three-Dimensional Fluorescence Spectroscopy |
TANG Ning1, YANG Yu-li1, FANG Ting2, WANG Wen-li1, CAO Shi-yue1, PAN Wen-hao1,3* |
1. School of Materials Science and Engineering, Shenyang Jianzhu University, Shenyang 110168, China
2. Chinese Society for Composite Materials, Beijing 100083, China
3. School of Materials Science and Engineering, Northeastern University, Shenyang 110819, China |
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Abstract Bitumen is easy to age under the natural environment of light, heat and oxygen. A good deal of damages of pavement caused by bitumen aging such as crack, chap and trenches, as well as the service life of asphalt pavement are shortened. In order to improve the durability of asphalt pavement and reveal the change rule of components and structure during the bitumen aging process, the fluorescence spectroscopy technique was carried out from the phenomenon of fluorescence quenching of bitumen in this paper. There are two bitumen that were carried out by ultraviolet aging (UV) and thin-film oven test (TFOT). The properties and components of bitumen were studied before and after aging. Furthermore, fluorescence spectrogram of bitumen was obtained by fluorescence spectrophotometer, and the characteristic of spectrogram was analyzed. In addition, the coordinates of fluorescence peak were found from the spectrogram, and the shifted vector was calculated at last. The results showed that optimum concentration is 0.1 g·L-1 to avoid fluorescence quenching. After aging, softening point of bitumen increases, penetration and ductility decreases. Furthermore, its saturate is unchanged, aromatics decrease, resins and asphaltenes increase. According to the three-dimensional fluorescence spectrum, the coordinates of fluorescence peak of bitumen appear "blue shift" after aging, and the content of aromatics in the bitumen defines the shift distance of fluorescence peak. In addition, bitumen has aged badly when the norm of shift vector is higher than 36. As characteristic parameter of three-dimensional fluorescence spectra was analyzed, it is possible to evaluate the aging process of asphalt effectively, which is of great significance to improve the durability of bitumen.
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Received: 2017-09-15
Accepted: 2018-01-10
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Corresponding Authors:
PAN Wen-hao
E-mail: pwh@sjzu.edu.cn
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[1] Ministry of Transport of the People’s Republic of China(中国交通运输部). Statistical Bulletin of Transportation Industry Development of China in 2016(2016年交通运输行业发展统计公报). Beijing: China Communication Press(北京:人民交通出版社), 2017.
[2] Xiao Y, Wan M, Jenkins K J. J Mater Civil Eng., 2017, 29(10): 4.
[3] Zhu J, Birgisson B, Kringos N. Eur. Polym. J., 2014, 54: 18.
[4] Feng Y, Le Doan T V, Pomerantz A E. Energ Fuel, 2013, 27(12): 7314.
[5] Nivitha M R, Prasad E, Krishnan J M. Int. J. Pavement Eng., 2016, 17(7): 565.
[6] Weigel S, Stephan D. Fuel, 2017, 208: 655.
[7] Redelius P, Soenen H. Fuel, 2015, 140: 34.
[8] Gawel I, Czechowski F, Kosno J. Constr Build Mater, 2016, 110: 42.
[9] Filippelli L, Gentile L, Rossi C O. Ind. Eng. Chem. Res., 2012, 51(50): 16346.
[10] Szerb E I, Nicotera I, Teltayev B. Road Mater Pavement, 2018, 19(5): 1192.
[11] Craddock P R, Le Doan T V, Bake K. Energ Fuel, 2015, 29(4): 2197.
[12] Makowska M, Hartikainen A, Pellinen T. Mater Struct, 2017, 50(3): 189.
[13] TANG Jie-qiong, MA Qing-feng, SHI Jing-tao(唐洁琼,马庆丰,时敬涛). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2016, 36(3): 672.
[14] Grossegger D, Grothe H, Hofko B. Road Mater Pavement, 2018, 19(4): 992.
[15] Xiao Y, Van De Ven M F C, Molenaar A A A. Mater Struct, 2011, 44(3): 611. |
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