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Volumn 45, Issue 1, 2006, Pages 346-351

Detailed composition-based model for predicting the cetane number of diesel fuels

Author keywords

[No Author keywords available]

Indexed keywords

COMMERCIAL BLENDS; SUPERCRITICAL FLUID CHROMATOGRAPHY;

EID: 30444445523     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie0508132     Document Type: Article
Times cited : (140)

References (15)
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  • 3
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    • Prediction of cetane number by group additivity and carbon-13 nuclear magnetic resonance
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    • (1987) Ind. Eng. Chem. Res. , vol.26 , pp. 188
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  • 7
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    • Rapid cetane number prediction method for petroleum liquids and pure hydrocarbons using proton NMR
    • No. 892073
    • Guider, O. L.; Glavincevski, B.; Kalloo, N. N. A Rapid Cetane Number Prediction Method for Petroleum Liquids and Pure Hydrocarbons Using Proton NMR. SAE Tech. Pap. Ser. 1989, No. 892073.
    • (1989) SAE Tech. Pap. Ser.
    • Guider, O.L.1    Glavincevski, B.2    Kalloo, N.N.A.3
  • 8
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    • Cookson, D. J.; Illiopoulos, P.; Smith, B. E. Composition-Property relations for jet and diesel fuels of variable boiling range. Fuel 1995, 74 (1), 70.
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    • Cookson, D.J.1    Illiopoulos, P.2    Smith, B.E.3
  • 10
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    • Yang, H.; Ring, Z.; Briker, Y.; McLean, N.; Friesen, W.; Fairbridge, C. Neural network prediction of cetane number and density of diesel fuel from its chemical composition determined by LC and GC-MS. Fuel 2002, 81, 65.
    • (2002) Fuel , vol.81 , pp. 65
    • Yang, H.1    Ring, Z.2    Briker, Y.3    McLean, N.4    Friesen, W.5    Fairbridge, C.6
  • 11
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    • Investigation of the chemical basis of diesel fuel properties
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.