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| Impact of EGR Rate on Soot Nanostructure from a Diesel Engine Fueled with Biodiesel |
| WANG Zhong, YANG Fang-ling, ZHANG Jian, ZHAO Yang, QU Lei |
| School of Automobile and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China |
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Abstract A specific nanostructure analysis was performed on the soot derived from diesel engine fueled with biodiesel under different rate of exhaust gas. The experimental instruments used in this study included an 186FA engine bench, a full-flow dilution constant volume sampling system, and a laser Raman spectrometer. In the engine bench test, biodiesel soot under several EGR rates were collected from the exhaust gas with the Micro-Orifice Uniform Deposit Impactor (MOUDI). Then, a laser Raman spectrometer was utilized in order to explore the nanostructure of biodiesel soot. The first-order Raman spectra have been analyzed by curve fit with five band combination and the obtained spectral parameters were discussed. The results revealed that 30% EGR rate had the widest FWHM representing strongest chemical heterogeneity and most material types in biodiesel soot, next was 15% EGR rate, and no EGR was the last. While EGR rate climbed from 0 to 30%, ID/IG gradually increased, which suggested that ordered graphitic structure reduce and the degree of graphitization decreased. In addition, ID1/ID2 were located about from 8 of 0% EGR to 4 of 15% and 30% EGR, suggesting a general transformation from vacancy defect to defect at graphene layer edges. Furthermore, crystallite dimension reduced when EGR rate raised. However, C—C bond length seemed no fluctuation. Besides, there was no obvious difference of C—C bond length between biodiesel soot and typical carbon graphite. In summary, the nanostructure of biodiesel soot under high EGR rate tended to have low degree of graphitization and high oxidative reactivity.
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Received: 2016-03-15
Accepted: 2016-07-28
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[1] Juhun Song, Mahabubul Alam, Andre L Boehman, et al. Combustion and Flame, 2006，146: 589.
[2] Rosen H, Novakov T. Atmospheric Environment, 1978, 923.
[3] Steffen W, Julian N B, Sven K. Applied Catalysis B-Environmental, 2014, 147: 1000.
[4] Magin L, Francisco J M, Jose M H. Journal of Aerosol Science, 2007, 38(4): 455.
[5] Vander Wal R L, Tomasek A J. Combustion and Flame, 2003, 134(1/2): 1.
[6] Agudelo J R, Alvarez A, Armas O. Combustion and Flame, 2014, 161(11): 2904.
[7] Li Xinling, Xu Zhen, Guan Chun, et al. Applied Thermal Engineering, 2014，68: 100.
[8] Tuinstra F, Koenig J L. J. Chem. Phys., 1970, 53: 1126.
[9] Knight D S, White W B. J. Mater. Res., 1989, 4: 385.
[10] Ferrari A C. J. Robertson, Phys. Rev. B, 2000, 61: 14095.
[11] Sadezky A, Muckenhuber H, Grothe H, et al. Carbon, 2005, 43(8): 1731.
[12] Zhu Jinyu, Kyeong Ook Lee, Ahmet Yozgatligil，et al. Proceedings of the Combustion Institute, 2005，30: 2781.
[13] Vander Wal R L, Tomasek A J, Street K, et al. Applied Spectroscopy, 2004, 58(2): 230.
[14] Zhu Changji, Liu Zhongchang, Xu Yun. Transactions of CSICE, 2006, 24(3)：276.
[15] Zhao Yang, Wang Yucheng, Wang Zhong, et al. Research of Environmental Sciences, 2014, 27(12): 1472.
[16] Yehliu K, Armas O, Wal R, et al. Combust. Flame, 2013, 160: 682.
[17] Yoshida A, Kaburagi Y, Hishiyama Y. Carbon, 2006, 44(11): 2333.
[18] John R Agudelo, Arnaldo Alvarez, Octavio Armas. Combustion and Flame, 2014(161): 2904.
[19] Irenak, Laurat, Elenacf, et al. Spectrochimica Acta, 2012, 91: 67.
[20] Tuinstra F, Koeing J L. The Journal of Chemical Physics, 1970, 53(3): 1126.
[21] Fitzer E, Rozploch F. High Temperatures. High Pressures, 1988, 20(4): 449. |
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