Table of Contents
Journal of Petroleum Engineering
Volume 2013, Article ID 594368, 12 pages
http://dx.doi.org/10.1155/2013/594368
Research Article

Rethinking Petroleum Products Certification

1Programa de Engenharia Química/COPPE, Universidade Federal do Rio de Janeiro, 68502 Rio de Janeiro, RJ, Brazil
2Escola Politécnica, Universidade Federal do Rio de Janeiro, 68529 Rio de Janeiro, RJ, Brazil
3Departamento de Engenharia Química/EQ, Universidade Federal do Rio de Janeiro, 68542 Rio de Janeiro, RJ, Brazil
4PETROBRAS Petróleo Brasileiro S.A., Rio de Janeiro, RJ, Brazil
5Faculdade de Tecnologia de Resende, Universidade do Estado do Rio de Janeiro, Rodovia Presidente Dutra Km 298, Resende, RJ, Brazil
6Departamento de Engenharia Química, Universidade de São Paulo, São Paulo, SP, Brazil

Received 23 August 2013; Accepted 12 October 2013

Academic Editor: Alireza Bahadori

Copyright © 2013 Thiago Feital et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. R. Katzer, M. P. Ramage, and A. V. Sapre, “Petroleum refining: poised for profound changes,” Chemical Engineering Progress, vol. 96, no. 7, pp. 41–51, 2000. View at Google Scholar · View at Scopus
  2. S. Hu and X. X. Zhu, “A general framework for incorporating molecular modeling into overall refinery optimization,” Applied Thermal Engineering, vol. 21, no. 13-14, pp. 1331–1348, 2001. View at Publisher · View at Google Scholar
  3. L. F. L. Moro, “Optimization in the petroleum refining industry—the virtual refinery,” in 10th International Symposium on Process Systems Engineering—PSE 2009, R. M. D. B. Alves, C. A. O. do Nascimento, and E. C. Biscaia Jr., Eds., Elsevier, Salvador, Brazil, 2009. View at Google Scholar
  4. P. A. Pantoja, J. López-Gejo, G. A. C. Le Roux, F. H. Quina, and C. A. O. Nascimento, “Prediction of crude oil properties and chemical composition by means of steady-state and time-resolved fluorescence,” Energy & Fuels, vol. 25, no. 8, pp. 3598–3604, 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. A. Barsamian, “Gasoline blending: technology, operations, economics,” Technical Seminar, Refinery Automation Institute LLC, Morristown, NJ, USA, 2007. View at Google Scholar
  6. J. -P. Favennec, Petroleum Refining: Refinery Operation and Management, vol. 5, Editions Technip, Paris, France, 2001.
  7. M. Joly, “Refinery planning and scheduling: the refining core business,” Brazilian Journal of Chemical Engineering, vol. 29, no. 2, pp. 371–384, 2012. View at Publisher · View at Google Scholar
  8. Technip, “In Line certification of petroleum products,” Technical Seminar, Technip Advanced Systems Engineering, Paris, France, 2007. View at Google Scholar
  9. EPA, “40CFRPart80 regulation of fuel and fuel additives: gasoline and diesel fuel test methods,” EPA Report OAR2005-0048, Environmental Protection Agency, Washington, DC, USA, 2006. View at Google Scholar
  10. Y. Wu and N. Zhang, “Molecular characterization of gasoline and diesel streams,” Industrial and Engineering Chemistry Research, vol. 49, no. 24, pp. 12773–12782, 2010. View at Publisher · View at Google Scholar · View at Scopus
  11. M. M. S. Aye and N. Zhang, “A novel methodology in transforming bulk properties of refining streams into molecular information,” Chemical Engineering Science, vol. 60, no. 23, pp. 6702–6717, 2005. View at Publisher · View at Google Scholar · View at Scopus
  12. N. Zhang and M. Valleur, “Refinery planning and scheduling,” in ASTM Handbook of Petroleum Refining and Natural Gas Processing, chapter 18, ASTM International, Conshohocken, Pa, USA, 2009. View at Publisher · View at Google Scholar
  13. R. E. Morris, M. H. Hammond, J. A. Cramer et al., “Rapid fuel quality surveillance through chemometric modeling of near-infrared spectra,” Energy & Fuels, vol. 23, no. 3, pp. 1610–1618, 2009. View at Publisher · View at Google Scholar · View at Scopus
  14. D. J. Cookson, C. P. Lloyd, and B. E. Smith, “Investigation of the chemical basis of diesel fuel properties,” Energy & Fuels, vol. 2, no. 6, pp. 854–860, 1988. View at Google Scholar · View at Scopus
  15. A. Agoston, C. Ötsch, and B. Jakoby, “Viscosity sensors for engine oil condition monitoring—application and interpretation of results,” Sensors and Actuators A, vol. 121, no. 2, pp. 327–332, 2005. View at Publisher · View at Google Scholar · View at Scopus
  16. A. Agoston, N. Dörr, and B. Jakoby, “Corrosion sensors for engine oils—laboratory evaluation and field tests,” Sensors and Actuators B, vol. 127, no. 1, pp. 15–21, 2007. View at Publisher · View at Google Scholar · View at Scopus
  17. A. Barsamian, “Get the most out of your NIR analyzers,” Hydrocarbon Processing, vol. 80, no. 1, pp. 69–72, 2001. View at Google Scholar
  18. W. R. Gilbert, F. S. G. de Lima, and A. F. Bueno, “Comparison of NIR and NMR spectra chemometrics for FCC feed online characterization,” Studies in Surface Science and Catalysis, vol. 149, pp. 203–215, 2004. View at Google Scholar · View at Scopus
  19. A. Barsamian, “Consider near infrared methods for inline blending,” Hydrocarbon Processing, vol. 84, no. 6, pp. 97–100, 2005. View at Google Scholar · View at Scopus
  20. A. Barsamian, “Optimize fuels blending with advanced online analyzers,” Hydrocarbon Processing, vol. 87, no. 9, pp. 121–122, 2008. View at Google Scholar · View at Scopus
  21. A. G. Marshall and R. P. Rodgers, “Petroleomics: the next grand challenge for chemical analysis,” Accounts of Chemical Research, vol. 37, no. 1, pp. 53–59, 2004. View at Publisher · View at Google Scholar · View at Scopus
  22. F. C.-Y. Wang, K. Qian, and L. A. Green, “GC×MS of diesel: a two-dimensional separation approach,” Analytical Chemistry, vol. 77, no. 9, pp. 2777–2785, 2005. View at Publisher · View at Google Scholar · View at Scopus
  23. B. Creton, C. Dartiguelongue, T. De Bruin, and H. Toulhoat, “Prediction of the cetane number of diesel compounds using the quantitative structure property relationship,” Energy & Fuels, vol. 24, no. 10, pp. 5396–5403, 2010. View at Publisher · View at Google Scholar · View at Scopus
  24. D. A. Saldana, L. Starck, P. Mougin et al., “Flash point and cetane number predictions for fuel compounds using quantitative structure property relationship (QSPR) methods,” Energy & Fuels, vol. 25, no. 9, pp. 3900–3908, 2011. View at Publisher · View at Google Scholar · View at Scopus
  25. H. Yang, Z. Ring, Y. Briker, N. McLean, W. Friesen, and C. Fairbridge, “Neural network prediction of cetane number and density of diesel fuel from its chemical composition determined by LC and GC-MS,” Fuel, vol. 81, no. 1, pp. 65–74, 2002. View at Publisher · View at Google Scholar · View at Scopus
  26. T. N. Pranatyasto and S. J. Qin, “Sensor validation and process fault diagnosis for FCC units under MPC feedback,” Control Engineering Practice, vol. 9, no. 8, pp. 877–888, 2001. View at Publisher · View at Google Scholar · View at Scopus
  27. M. Hur, I. Yeo, E. Park et al., “Combination of statistical methods and Fourier transform ion cyclotron resonance mass spectrometry for more comprehensive, molecular-level interpretations of petroleum samples,” Analytical Chemistry, vol. 82, no. 1, pp. 211–218, 2010. View at Publisher · View at Google Scholar · View at Scopus
  28. J. P. Favennec, Le Raffinage du Petrole: Exploitation et Gestion de la Raffinerie, vol. 5, Tome 5, Technip Editions, Institut Francais du Petrole, Paris, France, 1998.